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6 Commits

Author SHA1 Message Date
cyy b1c424d1a6 Init cmake commit
Signed-off-by: cyy <cyyever@outlook.com>
2025-07-30 16:10:36 +08:00
Kamil Iskra 593de54e52 NCCL 2.27.7-1
Prevent initialization failures in certain configurations when attempting
to load fp8-specific symmetric multicast kernels on GPUs older than
Blackwell.
2025-07-24 10:39:53 -07:00
Stephen Sachs 0d1ece2b43 Exclude ongoing issues from auto-closing logic
- Added a check to skip issues labeled "ongoing" in the close-old-issues script
- Adjusted the condition to compare both creation and update dates against six months ago
2025-07-17 21:50:05 +02:00
Stephen Sachs bfedf2629e Add issues templates and Github action to remove stale issues
We add 3 different issue types issue/question/RFE and add some predefined
questions to speed up the debugging process.

We also add a custom action which will close all issues create mode than 6
months ago which have not been updated for more than a month.
2025-07-16 17:56:12 +02:00
Kamil Iskra 7c12c627c6 NCCL 2.27.6-1
Improve support for DirectNIC (CX8)
* Add support for XDR speed detection.
* When DirectNIC is enabled, report only the RDMA interfaces.

Extend the P2C (PXN over C2C) support to send/receive operations.

Support compilation with GCC 14 (Issues #1743, #1751).

Fix the unloading of network plugins that also provide tuner capability.

Fix the change of the current device across the calls to ncclCommDestroy()
and ncclCommAbort().

A note for users on MNNVL systems: please ensure an adequate stack size for
NCCL threads.  While the default Linux stack size limit of 8192 KB is known
to be sufficient, we've seen crashes if the limit is changed to
"unlimited", as it causes the glibc library to unexpectedly *decrease* the
stack size of NCCL's background threads to just 2048 KB.  Use "ulimit -s"
in bash to print the current limit; if needed, reset it to 8192 KB using
"ulimit -s 8192" (one also needs to ensure that the new setting is
propagated to other nodes when launching a multi-node NCCL job).
2025-07-11 07:32:13 -07:00
Kamil Iskra 3ea7eedf3b NCCL 2.27.5-1
Improvements for GB200 systems
* Optimize the network performance by alternating the direction of the
  rings and the NIC to GPU assignment across communicators to limit
  unnecessary sharing.
* Fix the detection of C2C links in case GPU Direct RDMA is disabled
  between a GPU and a NIC.
* Fix PXN support on MNNVL systems, where NCCL would try (and fail) to
  share regular host memory across multiple nodes.
* Fix P2C (PXN over C2C), which is now preferred over regular PXN.  This
  support is currently preliminary and is disabled by default; use
  NCCL_PXN_C2C=1 to enable.

Further reduce the overheads of CUDA graph capturing, which increased in
NCCL 2.26.2 for large graphs.

Optimize the network performance on DGX B200 systems by adjusting the
bandwidths provided to the graph search algorithm.

Enable fp8 reductions in symmetric kernels on Blackwell with CUDA 12.8.

Restore the plugin name handling logic to make it possible to specify a
path to the plugin (Issue #1732).

Restore the ability to change NCCL_COLLNET_ENABLE during execution
(Issue #1741).

Add an example tuner plugin with CSV-based overrides.

Remove an x86 dependency from the example profiler.
2025-06-18 10:34:47 -07:00
54 changed files with 3622 additions and 214 deletions

77
.github/ISSUE_TEMPLATE/ISSUE.yaml vendored Normal file
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@ -0,0 +1,77 @@
name: NCCL issue or bug
description: Report an issue or failure when running NCCL code
title: "[Issue]: "
labels: ["triage"]
body:
- type: markdown
attributes:
value: |
Thanks for reaching out! Before reporting a new issue, please feel free to search for the behavior in the existing issues. If you found an issue which is already closed or you are unsure, open a new issue and reference the old one from it.
You can also check out the [troubleshooting section](https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/troubleshooting.html) in our user guide.
---
To ensure we can assist you quickly and accurately, we often need the following information:
- type: dropdown
id: type
attributes:
label: How is this issue impacting you?
description: What best describes your issue?
options:
- Lower performance than expected
- Application crash
- Data corruption
- Application hang
validations:
required: true
- type: textarea
id: log
attributes:
label: Share Your Debug Logs
description: |
The logs and topo-files are a great tool to pin down issues. You can create them by setting these environment variables before the run.
* `NCCL_DEBUG=INFO` and `NCCL_DEBUG_FILE=ncclDebug.%h.%p` to produce one file per rank
* `NCCL_TOPO_DUMP_FILE=ncclSystem.txt`
- type: textarea
id: repro
attributes:
label: Steps to Reproduce the Issue
description: |
* **Minimal Steps**: Please provide a simple way to recreate the issue (see [Minimal Bug Reports](https://matthewrocklin.com/minimal-bug-reports) for inspiration).
* **Environment Details**: Include software versions and relevant settings.
* **Intermittency**: Is this a sporadic issue? If so, how often does it occur?
* **Previous Success**: Did this work with an older NCCL version?
The easier we can reproduce on our side the more likely we are to be able to solve it in a timely manner.
- type: input
id: nccl_version
attributes:
label: NCCL Version
description: |
NCCL reports its version string in the debug logs.
You can also determine the version if you know which library was used by running `strings libnccl.so | grep 'NCCL version'`.
placeholder: "e.g. 2.27.1+cuda12.8"
validations:
required: true
- type: textarea
id: platform
attributes:
label: Your platform details
description: |
* **GPU & Network**: Share your architecture and topology (e.g., from `nvidia-smi`, `nvidia-smi topo -m`, `ibstatus`).
* **Environment**: Bare-metal, containers, or cloud?
* **Scalability**: Does this issue occur with a specific number of ranks/nodes?
- type: textarea
id: issue-description
attributes:
label: Error Message & Behavior
description: |
* **First Error**: What was the initial `NCCL WARN` message in your logs?
* **Expected vs. Actual**: Briefly describe the anticipated behavior versus what you're seeing.

15
.github/ISSUE_TEMPLATE/QUESTION.yaml vendored Normal file
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@ -0,0 +1,15 @@
name: NCCL question
description: Ask the NCCL team a question
title: "[Question]: "
labels: ["question"]
body:
- type: markdown
attributes:
value: |
Thanks for reaching out! To solve your problem, feel free to check out the [user guide](https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/index.html), in particular the troubleshooting section, and also the [release notes](https://docs.nvidia.com/deeplearning/nccl/release-notes/index.html).
---
- type: textarea
id: question
attributes:
label: Question

22
.github/ISSUE_TEMPLATE/RFE.yaml vendored Normal file
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@ -0,0 +1,22 @@
name: NCCL request for enhancement
description: Request for enhancement
title: "[RFE]: "
labels: ["enhancement"]
body:
- type: markdown
attributes:
value: |
Thanks for your feedback! Before reporting a new RFE you could quickly check if this already exists in our [existing requests](https://github.com/NVIDIA/nccl/issues?q=sort%3Aupdated-desc%20is%3Aissue%20is%3Aopen%20label%3Aenhancement).
---
- type: textarea
id: rfe-description
attributes:
label: Please provide the below details to ensure we understand your needs
description: |
* What is the goal of this request?
* Who will benefit from this feature?
* Is this request for a specific GPU architecture or network infrastructure?
* How will this feature improve current workflows or processes?
* What is the priority level of this request?

1
.github/ISSUE_TEMPLATE/config.yml vendored Normal file
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@ -0,0 +1 @@
blank_issues_enabled: false

79
.github/workflows/close-old-issues.js vendored Normal file
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@ -0,0 +1,79 @@
const { Octokit } = require("@octokit/rest");
const octokit = new Octokit({ auth: process.env.GITHUB_TOKEN });
const owner = process.env.REPO_OWNER;
const repo = process.env.REPO_NAME.split('/').pop(); // Handles owner/repo format
const now = new Date();
const sixMonthsAgo = new Date(now);
sixMonthsAgo.setMonth(now.getMonth() - 6);
const oneMonthAgo = new Date(now);
oneMonthAgo.setMonth(now.getMonth() - 1);
async function closeOldIssues() {
let page = 1;
let closedCount = 0;
// write a multiline comment into a variable:
let body = `### Issue Cleanup: Helping Us Focus on Current Challenges
We're [reviewing](https://github.com/NVIDIA/nccl/discussions/1761) older issues to ensure we prioritize the most relevant and active ones. Since this issue hasn't seen updates in over 6 months, we'll be closing it for now.
*This change helps us focus our efforts on addressing any current issues our users are facing.* If this issue still affects you, please don't hesitate to reopen it with a quick update (e.g., \"Still relevant on [version=X]\").
Thanks for your understanding and for contributing to NCCL.`;
while (true) {
const { data: issues } = await octokit.issues.listForRepo({
owner,
repo,
state: "open",
per_page: 100,
page,
});
if (issues.length === 0) break;
for (const issue of issues) {
// Ignore PRs
if (issue.pull_request) continue;
// Ignore issues with label "ongoing"
if (issue.labels.some(label => label.name === "ongoing")) continue;
const createdAt = new Date(issue.created_at);
const updatedAt = new Date(issue.updated_at);
if (createdAt < sixMonthsAgo && updatedAt < sixMonthsAgo) {
// Add a comment before closing
await octokit.issues.createComment({
owner,
repo,
issue_number: issue.number,
body: body,
});
await octokit.issues.update({
owner,
repo,
issue_number: issue.number,
state: "closed",
state_reason: "not_planned",
});
closedCount++;
console.log(`Closed issue #${issue.number}`);
// Break out if we have closed 100 issues
if (closedCount >= 100) {
console.log("Closed 100 issues, stopping.");
return;
}
}
}
page++;
}
console.log(`Total closed: ${closedCount}`);
}
closeOldIssues().catch(console.error);

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.github/workflows/close_old_issues.yaml vendored Normal file
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@ -0,0 +1,31 @@
name: Close Old Issues
on:
schedule:
- cron: '30 2 * * *' # Runs daily at 02:30 UTC
workflow_dispatch:
permissions:
issues: write
jobs:
close-old-issues:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Setup Node.js
uses: actions/setup-node@v4
with:
node-version: 20
- name: Install dependencies
run: npm install @octokit/rest@22.0.0
- name: Run close-old-issues script
run: node .github/workflows/close-old-issues.js
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
REPO_OWNER: ${{ github.repository_owner }}
REPO_NAME: ${{ github.event.repository.name || github.repository }}

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CMakeLists.txt Normal file
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cmake_minimum_required(VERSION 4.0)
project(nccl LANGUAGES CUDA CXX VERSION 2.27.7)
option(VERBOSE "VERBOSE" OFF)
option(KEEP "KEEP" OFF)
option(TRACE "TRACE" OFF)
option(PROFAPI "PROFAPI" OFF)
option(NVTX "NVTX" ON)
option(NET_PROFILER "NET_PROFILER" OFF)
set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
add_subdirectory(src)
install(
TARGETS nccl nccl_static
EXPORT NCCLConfig
FILE_SET public_headers
DESTINATION include)
install(
EXPORT NCCLConfig
DESTINATION lib/cmake/nccl
NAMESPACE NCCL::)

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cmake/common.cmake Normal file
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@ -0,0 +1,39 @@
function(nccl_add_target_options target)
target_compile_options(${target} PRIVATE $<$<CONFIG:Debug>:-ggdb3>)
target_compile_options(${target} PRIVATE $<$<NOT:$<CONFIG:Debug>>:-O3>)
target_compile_options(
${target} PRIVATE $<$<COMPILE_LANGUAGE:CUDA>:--expt-extended-lambda -Xptxas
-maxrregcount=96 -Xfatbin -compress-all -fPIC>)
target_compile_options(${target} PRIVATE -fPIC -Wall -Wno-unused-function
-Wno-sign-compare -Wvla)
set_property(TARGET ${target} PROPERTY CXX_STANDARD 17)
set_property(TARGET ${target} PROPERTY CUDA_STANDARD 17)
set_property(TARGET ${target} PROPERTY CXX_VISIBILITY_PRESET hidden)
set_property(TARGET ${target} PROPERTY VISIBILITY_INLINES_HIDDEN 1)
set_property(TARGET ${target} PROPERTY CUDA_RESOLVE_DEVICE_SYMBOLS ON)
if(VERBOSE)
target_compile_options(${target} PRIVATE $<$<COMPILE_LANGUAGE:CUDA>:-Xptxas
-v -Xcompiler -Wall,-Wextra>)
target_compile_options(${target} PRIVATE -Wall -Wextra)
endif()
if(TRACE)
target_compile_options(${target} PRIVATE ENABLE_TRACE)
endif()
if(NOT NVTX)
target_compile_options(${target} PRIVATE NVTX_DISABLE)
endif()
if(KEEP)
target_compile_options(${target} PRIVATE $<$<COMPILE_LANGUAGE:CUDA>:-keep>)
endif()
if(PROFAPI)
target_compile_options(${target} PRIVATE PROFAPI)
endif()
if(NET_PROFILER)
target_compile_options(${target} PRIVATE NET_PROFILER)
endif()
endfunction()

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@ -3,15 +3,20 @@
#
# See LICENSE.txt for license information
#
NCCL_HOME:=../../build/
CUDA_HOME:=/usr/local/cuda
INC:= -I$(NCCL_HOME)/include -I$(CUDA_HOME)/include -Inccl
PLUGIN_SO:=libnccl-net.so
.DEFAULT_GOAL: build
include ../../makefiles/common.mk
SRCDIR ?= $(abspath ../..)
BUILDDIR ?= .
NCCLDIR := $(BUILDDIR)
default: $(PLUGIN_SO)
SRC_FILES := $(wildcard *.c)
$(PLUGIN_SO): plugin.c
$(CC) $(INC) -fPIC -shared -o $@ -Wl,-soname,$(PLUGIN_SO) $^
build: ${BUILDDIR}/libnccl-net-example.so
${BUILDDIR}/libnccl-net-example.so: ${SRC_FILES}
@printf "Compiling %-35s > %s\n" $< $@
@mkdir -p ${BUILDDIR}
$(CC) -Inccl -fPIC -shared -o $@ $^
clean:
rm -f $(PLUGIN_SO)
rm -f ${BUILDDIR}/libnccl-net-example.so

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@ -3,14 +3,20 @@
#
# See LICENSE.txt for license information
#
NCCL_HOME := ../../build
INC := -I$(NCCL_HOME)/include -I$(CUDA_HOME)/include -Inccl
PLUGIN_SO := libnccl-profiler.so
.DEFAULT_GOAL: build
include ../../makefiles/common.mk
SRCDIR ?= $(abspath ../..)
BUILDDIR ?= .
NCCLDIR := $(BUILDDIR)
default: $(PLUGIN_SO)
SRC_FILES := $(wildcard *.c)
$(PLUGIN_SO): plugin.c event.c print_event.c
$(CXX) $(INC) -g -fPIC -shared -o $@ -Wl,-soname,$(PLUGIN_SO) $^
build: ${BUILDDIR}/libnccl-profiler-example.so
${BUILDDIR}/libnccl-profiler-example.so: ${SRC_FILES}
@printf "Compiling %-35s > %s\n" $< $@
@mkdir -p ${BUILDDIR}
$(CC) -Inccl -fPIC -shared -o $@ $^
clean:
rm -f $(PLUGIN_SO)
rm -f ${BUILDDIR}/libnccl-profiler-example.so

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@ -12,7 +12,7 @@
#include <sys/types.h>
#include <sys/syscall.h>
#include <unistd.h>
#include <x86intrin.h>
#include <time.h>
#include "event.h"
#include "print_event.h"
@ -41,22 +41,10 @@ static struct proxyOp* detachPool;
ncclDebugLogger_t logFn;
#define INFO(FLAGS, ...) logFn(NCCL_LOG_INFO, (FLAGS), __func__, __LINE__, __VA_ARGS__)
static double freq = -1;
__hidden void calibrate() {
struct timeval tv;
gettimeofday(&tv, NULL);
uint64_t timeCycles = __rdtsc();
double time = - tv.tv_sec*1e6 - tv.tv_usec;
uint64_t total = 0ULL;
for (int i = 0; i < 10000; i++) total += __rdtsc();
gettimeofday(&tv, NULL);
timeCycles = __rdtsc() - timeCycles;
time += tv.tv_sec*1e6 + tv.tv_usec;
freq = timeCycles / time;
}
__hidden double gettime(void) {
return __rdtsc() / freq;
struct timespec t;
clock_gettime(CLOCK_MONOTONIC, &t);
return (t.tv_sec*1e6 + (t.tv_nsec*1e-3));
}
static pthread_mutex_t lock = PTHREAD_MUTEX_INITIALIZER;
@ -98,8 +86,6 @@ __hidden ncclResult_t exampleProfilerInit(void** context, int* eActivationMask,
// process address space.
pid = getpid();
// calibrate and start timer
calibrate();
startTime = gettime();
}
pthread_mutex_unlock(&lock);

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# NCCL Tuner Plugin Development
This directory contains resources and examples for developing NCCL tuner plugins. Tuner plugins allow you to customize NCCL's algorithm and protocol selection behavior to optimize performance for specific workloads and hardware configurations.
## Overview
NCCL tuner plugins provide a way to influence NCCL's automatic algorithm and protocol selection by modifying the cost tables that NCCL uses to make decisions. This allows you to:
- Override default algorithm/protocol combinations for specific collective operations
- Customize tuning based on message size, topology, and other parameters
- Implement sophisticated tuning strategies without recompiling NCCL
- Optimize performance for specific hardware configurations or workloads
## Tuner Plugin Interface
NCCL tuner plugins must implement the `ncclTuner_t` interface defined in `nccl_tuner.h` within `nccl/src/include/plugin`. These definitions have been forked to `tuner.h` in each example plugin, and it is expected that any plugin implementor forks the internal NCCL definitions as well. The current interface includes:
```c
// Initialize the tuner plugin
ncclResult_t (*init)(size_t nRanks, size_t nNodes, ncclDebugLogger_t logFunction, void **context);
// Get and modify collective operation cost information
ncclResult_t (*getCollInfo)(void* context, ncclFunc_t collType, size_t nBytes,
int numPipeOps, float** collCostTable, int numAlgo, int numProto,
int regBuff, int* nChannels);
// Clean up plugin resources
ncclResult_t (*destroy)(void* context);
```
## Development Guidelines
### 1. Plugin Structure
A typical tuner plugin should:
- Include the necessary forked NCCL headers (`tuner.h`)
- Implement all required interface functions
- Export the plugin structure with appropriate version
- Handle all input parameters gracefully
### 2. Cost Table Modification
The `getCollInfo` function receives a cost table that maps algorithm/protocol combinations to performance costs. Lower costs indicate preferred combinations. You can:
- Set costs to `0.0` to make combinations highly preferred
- Set costs to `NCCL_ALGO_PROTO_IGNORE` to disable combinations
- Use relative costs to create preferences between options
### 3. Channel Management
The `nChannels` parameter allows you to:
- Set a specific number of channels to use
- Return the original value to preserve NCCL's default behavior
- Implement dynamic channel selection based on message size or topology
### 4. Error Handling
Always return appropriate `ncclResult_t` values:
- `ncclSuccess` for successful or ignored operations
- `ncclInternalError` for plugin-specific errors. Returning an error is only advisable on plugin initialization and destruction, as the penalty users can pay for the overhead of a failed plugin call can be immense.
- Other NCCL error codes as appropriate
## Getting Started
### Option 1: Start with the Example Plugin
If you're new to tuner plugin development, start with the `example/` directory:
```bash
cd example/
make
```
This provides a CSV-based configuration system that you can customize or use as a template.
## Building and Testing
### Build Requirements
- GCC or compatible C compiler
- NCCL headers (included in `nccl/` subdirectories)
- Make
## Option 2: Use the Basic Plugin
For more customized tuning needs, you might want to start with a clean baseline. In that case, base off the basic plugin in the `basic/` directory:
```bash
cd basic/
make
```
### Build Process
Each plugin directory contains a Makefile:
```bash
cd basic/ # or example/
make
```
This generates a shared library (`.so` file) that can be loaded by NCCL.
### Loading the Plugin
Set the `LD_LIBRARY_PATH` to include your plugin directory:
```bash
export LD_LIBRARY_PATH=/path/to/your/plugin:$LD_LIBRARY_PATH
```
Set `NCCL_TUNER_PLUGIN` to either the plugin name, or the absolute path to the plugin file. Any of the below can work:
```bash
export NCCL_TUNER_PLUGIN=example
export NCCL_TUNER_PLUGIN=libnccl-tuner-example.so
export NCCL_TUNER_PLUGIN=/path/to/your/plugin/libnccl-tuner-example.so
```
NCCL will automatically discover and load the plugin based on the exported symbol names.
## Advanced Topics
### Plugin Versioning
NCCL supports multiple plugin interface versions. Make sure your plugin exports the correct version:
```c
const ncclTuner_v4_t ncclTunerPlugin_v4 = {
.name = "YourPluginName",
.init = yourInitFunction,
.getCollInfo = yourGetCollInfoFunction,
.destroy = yourDestroyFunction
};
```
### Multi-GPU and Multi-Node Considerations
Your plugin receives topology information (`nRanks`, `nNodes`) during initialization. Use this to:
- Implement topology-aware tuning strategies
- Handle single-node vs. multi-node optimizations differently
- Scale channel counts based on available hardware
### Performance Optimization
- Keep plugin logic lightweight to avoid impacting NCCL performance
- Cache expensive computations when possible
- Use the logging system for debugging but avoid excessive output in production
## Debugging and Logging
Use NCCL's debug logging system:
```bash
export NCCL_DEBUG=INFO # General information
export NCCL_DEBUG_SUBSYS=TUNING
```
Within your plugin, use the provided `ncclDebugLogger_t` function for consistent logging.
## Best Practices
1. **Test thoroughly**: Verify your plugin works with various message sizes and topologies
2. **Handle edge cases**: Ensure your plugin behaves correctly with unusual input parameters
3. **Document your approach**: Clearly document your tuning strategy and configuration options
4. **Version your plugin**: Use meaningful version numbers and maintain backward compatibility
5. **Performance validation**: Measure the impact of your tuning decisions on real workloads
## Contributing
When developing new tuner plugins:
- Follow the existing code style and structure
- Include comprehensive documentation
- Add example configurations and test cases
- Consider contributing useful plugins back to the community
## Resources
- [NCCL Documentation](https://docs.nvidia.com/deeplearning/nccl/)
- Example plugin implementations in this directory
For questions and support, refer to the NCCL community resources and documentation.

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ext-tuner/basic/Makefile Normal file
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@ -0,0 +1,23 @@
#
# Copyright (c) 2015-2019, NVIDIA CORPORATION. All rights reserved.
#
# See LICENSE.txt for license information
#
.DEFAULT_GOAL: build
include ../../makefiles/common.mk
SRCDIR ?= $(abspath ../..)
BUILDDIR ?= .
NCCLDIR := $(BUILDDIR)
SRC_FILES := $(wildcard *.c)
DST_DIR := $(BUILDDIR)/test/unit/plugins
build: ${BUILDDIR}/libnccl-tuner-basic.so
${BUILDDIR}/libnccl-tuner-basic.so: ${SRC_FILES}
@printf "Compiling %-35s > %s\n" $< $@
@mkdir -p ${BUILDDIR}
$(CC) -Inccl -fPIC -shared -o $@ $^
clean:
rm -f ${BUILDDIR}/libnccl-tuner-basic.so

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@ -0,0 +1,197 @@
# Basic NCCL Tuner Plugin
This directory contains a minimal placeholder implementation of an NCCL tuner plugin. It serves as a starting point for developing custom tuner plugins by providing the essential function stubs and interface structure required by NCCL.
## Purpose
This basic plugin is designed to:
- Provide a minimal working example of the NCCL tuner plugin interface
- Serve as a template for developing custom tuner plugins
- Demonstrate the required function signatures and structure
- Implement placeholder functionality that can be extended
## Implementation Details
The plugin implements the following functions:
### `pluginInit`
```c
ncclResult_t pluginInit(size_t nRanks, size_t nNodes, ncclDebugLogger_t logFunction, void **context)
```
- **Purpose**: Initialize the plugin with communicator information
- **Current Implementation**: Simple placeholder that returns success
- **Parameters**:
- `nRanks`: Total number of ranks in the communicator
- `nNodes`: Total number of nodes in the communicator
- `logFunction`: NCCL debug logging function
- `context`: Plugin context pointer (output)
### `pluginGetCollInfo`
```c
ncclResult_t pluginGetCollInfo(void* context, ncclFunc_t collType, size_t nBytes,
int numPipeOps, float** collCostTable, int numAlgo, int numProto,
int regBuff, int* nChannels)
```
- **Purpose**: Modify cost tables for collective operations
- **Current Implementation**:
- Sets RING+SIMPLE algorithm to cost 0.0 (highest preference)
- Sets channel count to 1
- **Parameters**:
- `context`: Plugin context from init
- `collType`: Type of collective operation
- `nBytes`: Message size in bytes
- `numPipeOps`: Number of pipeline operations
- `collCostTable`: Cost table to modify
- `numAlgo`: Number of algorithms
- `numProto`: Number of protocols
- `regBuff`: Whether buffer can be registered
- `nChannels`: Number of channels to use (output)
### `pluginDestroy`
```c
ncclResult_t pluginDestroy(void* context)
```
- **Purpose**: Clean up plugin resources
- **Current Implementation**: Simple placeholder that returns success
## Cost Table Structure
The plugin demonstrates how to modify NCCL's cost tables:
```c
float (*table)[NCCL_NUM_PROTOCOLS] = (float (*)[NCCL_NUM_PROTOCOLS])collCostTable;
```
The cost table is a 2D array where:
- First dimension: Algorithm index (e.g., `NCCL_ALGO_RING`)
- Second dimension: Protocol index (e.g., `NCCL_PROTO_SIMPLE`)
- Values: Cost for that algorithm/protocol combination
### Cost Values
- **0.0**: Highest preference (lowest cost)
- **Positive values**: Relative costs (lower is better)
- **`NCCL_ALGO_PROTO_IGNORE`**: Disable this combination
## Building
```bash
make
```
This creates `libnccl-tuner-basic.so` which can be loaded by NCCL.
## Usage
### Loading the Plugin
```bash
export LD_LIBRARY_PATH=/path/to/basic:$LD_LIBRARY_PATH
mpirun -np 4 your_nccl_application
```
```bash
export NCCL_TUNER_PLUGIN=basic
export NCCL_TUNER_PLUGIN=libnccl-tuner-basic.so
export NCCL_TUNER_PLUGIN=/path/to/your/plugin/libnccl-tuner-basic.so
```
### Verifying Plugin Loading
Enable NCCL debug output to see if the plugin is loaded:
```bash
export NCCL_DEBUG=INFO
```
You should see messages indicating the tuner plugin is being used.
## Extending the Plugin
This basic plugin provides a foundation that you can extend:
### 1. Add Configuration Logic
Modify `pluginGetCollInfo` to implement your tuning strategy:
```c
__hidden ncclResult_t pluginGetCollInfo(void* context, ncclFunc_t collType, size_t nBytes,
int numPipeOps, float** collCostTable, int numAlgo, int numProto,
int regBuff, int* nChannels) {
// Your custom tuning logic here
if (nBytes < 1024) {
// Small message optimization
table[NCCL_ALGO_TREE][NCCL_PROTO_SIMPLE] = 0.0;
} else {
// Large message optimization
table[NCCL_ALGO_RING][NCCL_PROTO_LL128] = 0.0;
}
// Dynamic channel selection
*nChannels = (nBytes > 1024*1024) ? 4 : 1;
return ncclSuccess;
}
```
### 2. Add Context Management
Use the context pointer to store plugin state:
```c
struct pluginContext {
int initialized;
size_t nRanks;
size_t nNodes;
// Add your plugin-specific data here
};
```
### 3. Add File-Based Configuration
Read configuration from files, environment variables, or other sources.
### 4. Add Topology Awareness
Use the `nRanks` and `nNodes` parameters to implement topology-specific tuning.
## File Structure
```
basic/
├── README.md # This file
├── plugin.c # Plugin implementation
├── Makefile # Build configuration
└── nccl/ # NCCL header files
└── tuner.h # Tuner plugin interface definitions
```
## Next Steps
1. **Understand the Interface**: Study the function signatures and parameters
2. **Implement Your Logic**: Add your tuning strategy to `pluginGetCollInfo`
3. **Test Thoroughly**: Verify your plugin works with different message sizes and topologies
4. **Add Error Handling**: Implement proper error checking and resource management
5. **Document Your Changes**: Update this README with your specific implementation details
## Comparison with Example Plugin
- **Basic Plugin**: Minimal implementation, good for learning and simple use cases
- **Example Plugin**: Full-featured CSV-based configuration system, good for production use
Choose the basic plugin if you want to:
- Learn the tuner plugin interface
- Implement simple, hardcoded tuning strategies
- Build a custom plugin from scratch
Choose the example plugin if you want:
- File-based configuration
- Complex tuning strategies
- Production-ready features
## Resources
- [Parent Directory README](../README.md) - General tuner plugin development guide
- [Example Plugin](../example/README.md) - Fully featured implementation
This basic plugin provides the foundation you need to start developing custom NCCL tuner plugins. Extend it with your specific tuning logic and requirements.

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/*************************************************************************
* Copyright (c) 2024, NVIDIA CORPORATION. All rights reserved.
*
* See LICENSE.txt for license information
************************************************************************/
#ifndef COMMON_H_
#define COMMON_H_
typedef enum {NCCL_LOG_NONE=0, NCCL_LOG_VERSION=1, NCCL_LOG_WARN=2, NCCL_LOG_INFO=3, NCCL_LOG_ABORT=4, NCCL_LOG_TRACE=5} ncclDebugLogLevel;
typedef enum {NCCL_INIT=1, NCCL_COLL=2, NCCL_P2P=4, NCCL_SHM=8, NCCL_NET=16, NCCL_GRAPH=32, NCCL_TUNING=64, NCCL_ENV=128, NCCL_ALLOC=256, NCCL_CALL=512, NCCL_PROXY=1024, NCCL_NVLS=2048, NCCL_BOOTSTRAP=4096, NCCL_REG=8192, NCCL_ALL=~0} ncclDebugLogSubSys;
typedef void (*ncclDebugLogger_t)(ncclDebugLogLevel level, unsigned long flags, const char *file, int line, const char *fmt, ...);
#endif

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/*
* Copyright (c) 2017-2022, NVIDIA CORPORATION. All rights reserved.
*/
#ifndef NCCL_ERR_H_
#define NCCL_ERR_H_
/* Error type for plugins */
typedef enum { ncclSuccess = 0,
ncclUnhandledCudaError = 1,
ncclSystemError = 2,
ncclInternalError = 3,
ncclInvalidArgument = 4,
ncclInvalidUsage = 5,
ncclRemoteError = 6 } ncclResult_t;
#endif

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/*************************************************************************
* Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
* Copyright (c) 2023, Meta Platforms, Inc. and affiliates.
*
* See LICENSE.txt for license information
************************************************************************/
#ifndef NCCL_TUNER_H_
#define NCCL_TUNER_H_
#include <stdint.h>
#include <stdlib.h>
#include "common.h"
#include "err.h"
#define NCCL_NUM_FUNCTIONS 5 // Send/Recv not included for now
typedef enum {
ncclFuncBroadcast = 0,
ncclFuncReduce = 1,
ncclFuncAllGather = 2,
ncclFuncReduceScatter = 3,
ncclFuncAllReduce = 4,
ncclFuncSendRecv = 5,
ncclFuncSend = 6,
ncclFuncRecv = 7,
ncclNumFuncs = 8
} ncclFunc_t;
#define NCCL_NUM_ALGORITHMS 7 // Tree/Ring/CollNet*
#define NCCL_ALGO_UNDEF -1
#define NCCL_ALGO_TREE 0
#define NCCL_ALGO_RING 1
#define NCCL_ALGO_COLLNET_DIRECT 2
#define NCCL_ALGO_COLLNET_CHAIN 3
#define NCCL_ALGO_NVLS 4
#define NCCL_ALGO_NVLS_TREE 5
#define NCCL_ALGO_PAT 6
#define NCCL_NUM_PROTOCOLS 3 // Simple/LL/LL128
#define NCCL_PROTO_UNDEF -1
#define NCCL_PROTO_LL 0
#define NCCL_PROTO_LL128 1
#define NCCL_PROTO_SIMPLE 2
#define NCCL_ALGO_PROTO_IGNORE -1.0
// API to be implemented by external tuner
typedef struct {
// Name of the tuner
const char* name;
// Initializes tuner states.
// Inputs:
// - nRanks: number of ranks in current communicator. Each communicator initialize its own tuner.
// - nNodes: number of nodes in current communicator.
// - logFunction: a logFunction can be useful to integrate logging together with NCCL core.
// Outputs:
// - context: tuner context object
ncclResult_t (*init)(size_t nRanks, size_t nNodes, ncclDebugLogger_t logFunction, void **context);
// Gets info (algo, protocol, number of ctas and threads) for a given collective.
// Inputs:
// - context: tuner context object
// - collType: collective type , e.g., allreduce, allgather…
// - nBytes: collective size in bytes
// - numPipeOps: number of operations in the group
// - numAlgo: number of algorithms in collCostTable
// - numProto: number of protocols in collCostTable
// - regBuff: can register user buffer
//
// Outputs:
// - nChannels: number of channels (hence SMs) to be used.
//
// InOut:
// - collCostTable: collective cost table, generated by NCCL core, containing algo|proto|time entries for collType.
// NCCL core sets ignored algo/proto cost table entries to -1.0 (NCCL_ALGO_PROTO_IGNORE).
//
// If getCollInfo() does not return ncclSuccess, NCCL will fall back to the
// default tuning for the given collective.
// Also, the plugin is allowed to not set any output, or set only the
// algorithm and protocol, but not only the algorithm or only the protocol.
// Unset fields will be set automatically by NCCL.
ncclResult_t (*getCollInfo)(void* context, ncclFunc_t collType, size_t nBytes,
int numPipeOps, float** collCostTable, int numAlgo, int numProto,
int regBuff, int* nChannels);
// Terminates the plugin and cleans up any resources that the plugin allocated.
// context: tuner context object
ncclResult_t (*destroy)(void* context);
} ncclTuner_v4_t;
typedef ncclTuner_v4_t ncclTuner_t;
#define NCCL_TUNER_PLUGIN_SYMBOL "ncclTunerPlugin_v4"
#endif

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ext-tuner/basic/plugin.c Normal file
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/*************************************************************************
* Copyright (c) 2015-2019, NVIDIA CORPORATION. All rights reserved.
*
* See LICENSE.txt for license information
************************************************************************/
#include "tuner.h"
#define __hidden __attribute__ ((visibility("hidden")))
__hidden ncclResult_t pluginInit(size_t nRanks, size_t nNodes, ncclDebugLogger_t logFunction, void **context) { return ncclSuccess; }
__hidden ncclResult_t pluginGetCollInfo(void* context, ncclFunc_t collType, size_t nBytes,
int numPipeOps, float** collCostTable, int numAlgo, int numProto,
int regBuff, int* nChannels) {
// Update NCCL core generated cost table. Updated table will be evaluated by NCCL to pick the best algo/proto combo
float (*table)[NCCL_NUM_PROTOCOLS] = (float (*)[NCCL_NUM_PROTOCOLS])collCostTable;
if (table[NCCL_ALGO_RING][NCCL_PROTO_SIMPLE] != NCCL_ALGO_PROTO_IGNORE) {
table[NCCL_ALGO_RING][NCCL_PROTO_SIMPLE] = 0.0;
}
*nChannels = 1;
return ncclSuccess;
}
__hidden ncclResult_t pluginDestroy(void* context) { return ncclSuccess; }
#define PLUGIN_NAME "Basic"
const ncclTuner_v4_t ncclTunerPlugin_v4 = {
.name = PLUGIN_NAME,
.init = pluginInit,
.getCollInfo = pluginGetCollInfo,
.destroy = pluginDestroy
};

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@ -3,15 +3,53 @@
#
# See LICENSE.txt for license information
#
NCCL_HOME:=../../build/
CUDA_HOME:=/usr/local/cuda
INC:= -I$(NCCL_HOME)/include -I$(CUDA_HOME)/include -Inccl
PLUGIN_SO:=libnccl-tuner.so
default: $(PLUGIN_SO)
.DEFAULT_GOAL: build
PLUGIN_SO:=libnccl-tuner-example.so
include ../../makefiles/common.mk
SRCDIR ?= $(abspath ../..)
BUILDDIR ?= .
NCCLDIR := $(BUILDDIR)
$(PLUGIN_SO): plugin.c
$(CC) $(INC) -fPIC -shared -o $@ -Wl,-soname,$(PLUGIN_SO) $^
SRC_FILES := $(wildcard *.c)
DST_DIR := $(BUILDDIR)/test/unit/plugins
default: ${BUILDDIR}/$(PLUGIN_SO)
build: ${BUILDDIR}/$(PLUGIN_SO)
${BUILDDIR}/$(PLUGIN_SO): plugin.c
@printf "Compiling %-35s > %s\n" $< $@
@mkdir -p ${BUILDDIR}
$(CC) -Inccl $(INC) -fPIC -shared -o $@ -Wl,-soname,$(PLUGIN_SO) $^
# Test targets - delegate to test directory
test:
$(MAKE) -C test test TEST_CASE=$(TEST_CASE)
test-verbose:
$(MAKE) -C test test-verbose TEST_CASE=$(TEST_CASE)
# Build tests
test-build:
$(MAKE) -C test all
# Optimize configurations from performance data
optimize-config:
@if [ -z "$(CSV_FILE)" ]; then \
echo "Usage: make optimize-config CSV_FILE=path/to/data.csv [OUTPUT=config.conf] [METRIC=latency_us]"; \
echo "Example: make optimize-config CSV_FILE=scripts/sample_performance_data.csv"; \
exit 1; \
fi
python3 scripts/optimize_config.py $(CSV_FILE) \
$(if $(OUTPUT),-o $(OUTPUT)) \
$(if $(METRIC),-m $(METRIC)) \
$(if $(SIZE_RANGES),--size-ranges $(SIZE_RANGES)) \
$(if $(DRY_RUN),--dry-run) \
$(if $(NO_HEADER),--no-header)
clean:
rm -f $(PLUGIN_SO)
rm -f ${BUILDDIR}/$(PLUGIN_SO)
$(MAKE) -C test clean
.PHONY: test test-verbose test-build optimize-config clean

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# NCCL Example Tuner Plugin
This example plugin shows a practical example of a CSV file-based tuning approach, allowing selective overrides for tuning parameters based on all tuning inputs without recompiling.
## Features
- **File-based Configuration**: Read tuning parameters from a CSV configuration file
- **Size-based Tuning**: Specify different configurations based on message size ranges
- **Dimension-aware Tuning**: Match configurations based on number of nodes and ranks
- **Optional Channels Configuration**: Set specific channel counts or use -1 to keep NCCL's default
- **Environment Variable Support**: Specify config file location via `NCCL_TUNER_CONFIG_FILE`
- **Fallback Behavior**: Gracefully handles missing config files and invalid entries
## Building
```bash
make
```
This will create `libnccl-tuner-example.so` that can be loaded by NCCL.
## Configuration File Format
The configuration file uses CSV (Comma-Separated Values) format with one configuration per line:
```
collective_type,min_bytes,max_bytes,algorithm,protocol,channels,nNodes,nRanks,numPipeOps,regBuff
```
### Parameters
- **collective_type**: The collective operation type
- `broadcast`, `reduce`, `allgather`, `reducescatter`, `allreduce`
- **min_bytes/max_bytes**: The message size range (in bytes) for which this config applies
- Use `0` for minimum and `4294967295` for maximum (covers all sizes)
- **algorithm**: The NCCL algorithm to use
- `tree`, `ring`, `collnet_direct`, `collnet_chain`, `nvls`, `nvls_tree`, `pat`
- **protocol**: The NCCL protocol to use
- `ll`, `ll128`, `simple`
- **channels**: Number of channels (SMs) to use
- Use a positive integer to specify exact channel count
- Use `-1` to keep NCCL's default channel selection
- **nNodes**: Number of nodes to match
- Use a positive integer to match specific node count
- Use `-1` to match any number of nodes
- **nRanks**: Number of ranks to match
- Use a positive integer to match specific rank count
- Use `-1` to match any number of ranks
- **numPipeOps**: Number of pipeline operations to match (optional)
- Use a positive integer to match specific pipeline operation count
- Use `-1` to match any number of pipeline operations
- If omitted, configuration will match any numPipeOps value
- **regBuff**: Whether user buffer can be registered (optional)
- Use `0` to match only non-registered buffers
- Use `1` to match only registered buffers
- Use `-1` to match either registered or non-registered buffers
- If omitted, configuration will match any regBuff value
### Example Configuration
```csv
# Single-node, small allreduce: use tree algorithm, registered buffers only
allreduce,0,65536,tree,simple,2,1,-1,-1,1
# 4-node, 32-rank setup: medium allreduce, single pipeline op, non-registered buffers
allreduce,65537,1048576,ring,simple,4,4,32,1,0
# Any topology: large allreduce with LL128, multiple pipeline ops, any buffer type
allreduce,1048577,4294967295,ring,ll128,-1,-1,-1,4,-1
# Single-node broadcast: prefer tree, any pipeOps, registered buffers (backward compatible)
broadcast,0,32768,tree,simple,-1,1,-1
# Multi-node broadcast: optimized for non-registered buffers, single pipeline op
broadcast,32769,4294967295,ring,simple,2,-1,-1,1,0
```
Comments start with `#` and empty lines are ignored. The CSV format makes it easy to edit configurations in spreadsheet applications like Excel, Google Sheets, or LibreOffice Calc.
### Backward Compatibility
Configurations without the numPipeOps and/or regBuff parameters are fully supported:
- 8 fields: matches any numPipeOps and regBuff values
- 9 fields: matches any regBuff value
- 10 fields: full parameter specification
This ensures existing configuration files continue to work without modification.
## Usage
### Method 1: Default Config File
Place your configuration in `nccl_tuner.conf` in the current working directory.
### Method 2: Environment Variable
Set the `NCCL_TUNER_CONFIG_FILE` environment variable to specify the config file path:
```bash
export NCCL_TUNER_CONFIG_FILE=/path/to/your/tuner.conf
mpirun -np 4 your_nccl_application
```
## Editing Configuration Files
### Generating Configuration Files from Raw Data
A python script to generate valid CSV configs has been provided. [Using optimize_config.py](scripts/README.md).
### Spreadsheet Tips:
- Use column headers: `collective_type,min_bytes,max_bytes,algorithm,protocol,channels,nNodes,nRanks,numPipeOps,regBuff`
- Save as CSV format (not Excel format) for the plugin to read
- Use data validation to prevent typos in algorithm/protocol names
## Logging
The plugin uses NCCL's logging system. To see tuner-related messages:
```bash
export NCCL_DEBUG=INFO
```
This will show when configurations are loaded and applied, including the topology information.
For detailed debugging output during tuning decisions:
```bash
export NCCL_DEBUG=TRACE
```
This will show verbose information about which configurations are being evaluated and matched.
## Dimension Matching
Configurations are only applied when the topology matches:
- **Exact Match**: Configuration specifies `nNodes=4,nRanks=32`, only applied when communicator has exactly 4 nodes and 32 ranks
- **Wildcard Nodes**: Configuration specifies `nNodes=-1,nRanks=8`, applied to any topology with exactly 8 ranks
- **Wildcard Ranks**: Configuration specifies `nNodes=2,nRanks=-1`, applied to any 2-node topology regardless of ranks per node
- **Wildcard Both**: Configuration specifies `nNodes=-1,nRanks=-1`, applied to any topology
This allows you to create specialized configurations for different cluster setups while maintaining flexibility.
## Default Behavior
If no configuration file is found or no matching configuration exists for a collective operation, the plugin falls back to preferring the ring algorithm with simple protocol. All configured algorithm/protocol combinations are given a low cost (0.0) to make them preferred by NCCL's selection logic.
When channels is set to `-1`, NCCL's default channel selection logic is preserved, allowing the system to automatically determine the optimal number of channels based on hardware and message size.
## Troubleshooting
1. **Config file not found**: Check the file path and permissions
2. **Configurations not applied**: Verify the collective type, size ranges, algorithm/protocol names, and topology parameters
3. **Plugin not loaded**: Ensure `LD_LIBRARY_PATH` includes the plugin directory and that `NCCL_TUNER_PLUGIN` either specifies the plugin name, or an absolute path to the plugin shared library.
4. **No effect on performance**: Check that NCCL is actually using the tuner plugin with `NCCL_DEBUG=INFO`
5. **Topology mismatch**: Verify that nNodes and nRanks match your actual setup, or use -1 for wildcards
6. **CSV parsing errors**: Ensure no spaces after commas, or quote fields containing spaces

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# NCCL Tuner Configuration File (CSV Format)
# Format: collective_type,min_bytes,max_bytes,algorithm,protocol,channels,nNodes,nRanks,numPipeOps,regBuff
#
# Collective types: broadcast, reduce, allgather, reducescatter, allreduce
# Algorithms: tree, ring, collnet_direct, collnet_chain, nvls, nvls_tree, pat
# Protocols: ll, ll128, simple
# Channels: number of channels to use, or -1 to keep default
# nNodes: number of nodes to match, or -1 for any number of nodes
# nRanks: number of ranks to match, or -1 for any number of ranks
# numPipeOps: number of pipeline operations to match, or -1 for any number (optional)
# regBuff: whether user buffer can be registered (0=no, 1=yes, -1=any) (optional)
#
# Note: numPipeOps and regBuff parameters are optional - configurations without them will match any value
#
# Examples:
# For single-node configurations with registered buffers
# Small allreduce operations on single node - use tree algorithm, registered buffers
allreduce,0,65536,tree,simple,2,1,-1,-1,1
# For multi-node configurations with 4 nodes, 32 total ranks, single pipeline op, non-registered buffers
# Medium allreduce operations - use ring algorithm
allreduce,65537,1048576,ring,simple,4,4,32,1,0
# For any topology - large allreduce operations with LL128 protocol, multiple pipeline ops, any buffer type
allreduce,1048577,4294967295,ring,ll128,-1,-1,-1,4,-1
# Broadcast operations - different configs for different topologies, pipeline complexity, and buffer types
# Single node broadcast - prefer tree, any pipeOps, registered buffers only
broadcast,0,32768,tree,simple,-1,1,-1,-1,1
# Multi-node broadcast with single pipeline operation, non-registered buffers - use ring
broadcast,32769,4294967295,ring,simple,2,-1,-1,1,0
# AllGather operations - optimized for 2-node configurations, any pipeOps, any buffer type
allgather,0,4294967295,ring,simple,4,2,-1
# ReduceScatter operations
# Small messages on single node, single pipeline op, registered buffers
reducescatter,0,131072,tree,simple,2,1,-1,1,1
# Large messages on any topology, multiple pipeline ops, non-registered buffers
reducescatter,131073,4294967295,ring,simple,-1,-1,-1,2,0
# Reduce operations - any topology, keep default channels, any pipeOps, any buffer type
reduce,0,4294967295,tree,simple,-1,-1,-1

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@ -5,24 +5,443 @@
************************************************************************/
#include "tuner.h"
#include <stdio.h>
#include <string.h>
#include <stdlib.h>
#define __hidden __attribute__ ((visibility("hidden")))
#define MAX_LINE_LENGTH 256
__hidden ncclResult_t pluginInit(size_t nRanks, size_t nNodes, ncclDebugLogger_t logFunction, void **context) { return ncclSuccess; }
// CSV field indices for configuration parsing
// Format: colltype,minbytes,maxbytes,algorithm,protocol,channels,nNodes,nRanks,numPipeOps,regBuff
#define CONFIG_FIELD_COLLTYPE 0
#define CONFIG_FIELD_MINBYTES 1
#define CONFIG_FIELD_MAXBYTES 2
#define CONFIG_FIELD_ALGORITHM 3
#define CONFIG_FIELD_PROTOCOL 4
#define CONFIG_FIELD_CHANNELS 5
#define CONFIG_FIELD_NNODES 6
#define CONFIG_FIELD_NRANKS 7
#define CONFIG_FIELD_PIPEOPS 8 // Optional field
#define CONFIG_FIELD_REGBUFF 9 // Optional field
// Field count constants
#define CONFIG_FIELDS_REQUIRED 8 // Minimum required fields (up to nRanks)
#define CONFIG_FIELDS_WITH_PIPEOPS 9 // Fields including numPipeOps
#define CONFIG_FIELDS_WITH_REGBUFF 10 // Fields including both numPipeOps and regBuff
#define CONFIG_FIELDS_MAX 10 // Maximum number of fields supported
typedef struct {
ncclFunc_t collType;
size_t minBytes;
size_t maxBytes;
int algorithm;
int protocol;
int nChannels;
int nNodes;
int nRanks;
int numPipeOps;
int regBuff;
} TuningConfig;
typedef struct {
TuningConfig* configs; // Changed from static array to dynamic pointer
int numConfigs;
int maxConfigs; // Added to track allocated size
size_t nRanks;
size_t nNodes;
ncclDebugLogger_t logFunction;
} TunerContext;
// Parse collective type from string
static ncclFunc_t parseCollType(const char* str) {
if (strcmp(str, "broadcast") == 0) return ncclFuncBroadcast;
if (strcmp(str, "reduce") == 0) return ncclFuncReduce;
if (strcmp(str, "allgather") == 0) return ncclFuncAllGather;
if (strcmp(str, "reducescatter") == 0) return ncclFuncReduceScatter;
if (strcmp(str, "allreduce") == 0) return ncclFuncAllReduce;
return ncclFuncAllReduce; // default
}
// Convert collective type to string
static const char* collTypeToString(ncclFunc_t collType) {
switch (collType) {
case ncclFuncBroadcast: return "broadcast";
case ncclFuncReduce: return "reduce";
case ncclFuncAllGather: return "allgather";
case ncclFuncReduceScatter: return "reducescatter";
case ncclFuncAllReduce: return "allreduce";
default: return "unknown";
}
}
// Parse algorithm from string
static int parseAlgorithm(const char* str) {
if (strcmp(str, "tree") == 0) return NCCL_ALGO_TREE;
if (strcmp(str, "ring") == 0) return NCCL_ALGO_RING;
if (strcmp(str, "collnet_direct") == 0) return NCCL_ALGO_COLLNET_DIRECT;
if (strcmp(str, "collnet_chain") == 0) return NCCL_ALGO_COLLNET_CHAIN;
if (strcmp(str, "nvls") == 0) return NCCL_ALGO_NVLS;
if (strcmp(str, "nvls_tree") == 0) return NCCL_ALGO_NVLS_TREE;
if (strcmp(str, "pat") == 0) return NCCL_ALGO_PAT;
return NCCL_ALGO_RING; // default
}
// Convert algorithm to string
static const char* algorithmToString(int algorithm) {
switch (algorithm) {
case NCCL_ALGO_TREE: return "tree";
case NCCL_ALGO_RING: return "ring";
case NCCL_ALGO_COLLNET_DIRECT: return "collnet_direct";
case NCCL_ALGO_COLLNET_CHAIN: return "collnet_chain";
case NCCL_ALGO_NVLS: return "nvls";
case NCCL_ALGO_NVLS_TREE: return "nvls_tree";
case NCCL_ALGO_PAT: return "pat";
default: return "unknown";
}
}
// Parse protocol from string
static int parseProtocol(const char* str) {
if (strcmp(str, "ll") == 0) return NCCL_PROTO_LL;
if (strcmp(str, "ll128") == 0) return NCCL_PROTO_LL128;
if (strcmp(str, "simple") == 0) return NCCL_PROTO_SIMPLE;
return NCCL_PROTO_SIMPLE; // default
}
// Convert protocol to string
static const char* protocolToString(int protocol) {
switch (protocol) {
case NCCL_PROTO_LL: return "ll";
case NCCL_PROTO_LL128: return "ll128";
case NCCL_PROTO_SIMPLE: return "simple";
default: return "unknown";
}
}
// Helper function to count valid configuration lines in file
static int countConfigLines(const char* filename) {
FILE* file = fopen(filename, "r");
if (!file) {
return 0;
}
char line[MAX_LINE_LENGTH];
int count = 0;
while (fgets(line, sizeof(line), file)) {
// Skip comments and empty lines
if (line[0] == '#' || line[0] == '\n') continue;
// Remove trailing newline
line[strcspn(line, "\n")] = 0;
// Check if line has content
if (strlen(line) > 0) {
count++;
}
}
fclose(file);
return count;
}
// Load configuration from file
static ncclResult_t loadConfig(TunerContext* ctx, const char* filename) {
FILE* file = fopen(filename, "r");
if (!file) {
if (ctx->logFunction) {
ctx->logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Config file %s not found, using defaults", filename);
}
return ncclSuccess; // Not finding config file is not an error
}
// First pass: count valid configuration lines
int configCount = countConfigLines(filename);
if (configCount == 0) {
if (ctx->logFunction) {
ctx->logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: No valid configurations found in %s", filename);
}
fclose(file);
return ncclSuccess;
}
// Allocate memory for configurations based on actual count
ctx->configs = (TuningConfig*)malloc(configCount * sizeof(TuningConfig));
if (!ctx->configs) {
if (ctx->logFunction) {
ctx->logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Failed to allocate memory for %d configurations", configCount);
}
fclose(file);
return ncclSystemError;
}
ctx->maxConfigs = configCount;
ctx->numConfigs = 0;
if (ctx->logFunction) {
ctx->logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Allocated memory for %d configurations", configCount);
}
// Reset file pointer to beginning
fseek(file, 0, SEEK_SET);
char line[MAX_LINE_LENGTH];
while (fgets(line, sizeof(line), file) && ctx->numConfigs < ctx->maxConfigs) {
// Skip comments and empty lines
if (line[0] == '#' || line[0] == '\n') continue;
// Remove trailing newline
line[strcspn(line, "\n")] = 0;
// Parse CSV format: colltype,minbytes,maxbytes,algorithm,protocol,channels,nNodes,nRanks,numPipeOps,regBuff
char* token;
char* tokens[CONFIG_FIELDS_MAX];
int tokenCount = 0;
// Make a copy of the line for tokenizing
char lineCopy[MAX_LINE_LENGTH];
strncpy(lineCopy, line, sizeof(lineCopy));
lineCopy[sizeof(lineCopy) - 1] = '\0';
// Tokenize by comma
token = strtok(lineCopy, ",");
while (token != NULL && tokenCount < CONFIG_FIELDS_MAX) {
// Trim whitespace
while (*token == ' ' || *token == '\t') token++;
char* end = token + strlen(token) - 1;
while (end > token && (*end == ' ' || *end == '\t')) {
*end = '\0';
end--;
}
tokens[tokenCount++] = token;
token = strtok(NULL, ",");
}
// Validate field count: support required fields (8), with pipeOps (9), or with regBuff (10)
if (tokenCount >= CONFIG_FIELDS_REQUIRED && tokenCount <= CONFIG_FIELDS_MAX) {
TuningConfig* config = &ctx->configs[ctx->numConfigs];
config->collType = parseCollType(tokens[CONFIG_FIELD_COLLTYPE]);
config->minBytes = (size_t)strtoull(tokens[CONFIG_FIELD_MINBYTES], NULL, 10);
config->maxBytes = (size_t)strtoull(tokens[CONFIG_FIELD_MAXBYTES], NULL, 10);
config->algorithm = parseAlgorithm(tokens[CONFIG_FIELD_ALGORITHM]);
config->protocol = parseProtocol(tokens[CONFIG_FIELD_PROTOCOL]);
config->nChannels = atoi(tokens[CONFIG_FIELD_CHANNELS]);
config->nNodes = atoi(tokens[CONFIG_FIELD_NNODES]);
config->nRanks = atoi(tokens[CONFIG_FIELD_NRANKS]);
// numPipeOps is optional (9th field, index 8)
if (tokenCount >= CONFIG_FIELDS_WITH_PIPEOPS) {
config->numPipeOps = atoi(tokens[CONFIG_FIELD_PIPEOPS]);
} else {
config->numPipeOps = -1; // -1 means match any numPipeOps
}
// regBuff is optional (10th field, index 9)
if (tokenCount >= CONFIG_FIELDS_WITH_REGBUFF) {
config->regBuff = atoi(tokens[CONFIG_FIELD_REGBUFF]);
} else {
config->regBuff = -1; // -1 means match any regBuff value
}
ctx->numConfigs++;
if (ctx->logFunction) {
if (config->numPipeOps == -1 && config->regBuff == -1) {
ctx->logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Loaded config: %s [%zu-%zu] %s/%s channels=%d nodes=%d ranks=%d pipeOps=any regBuff=any",
tokens[CONFIG_FIELD_COLLTYPE], config->minBytes, config->maxBytes,
tokens[CONFIG_FIELD_ALGORITHM], tokens[CONFIG_FIELD_PROTOCOL],
config->nChannels, config->nNodes, config->nRanks);
} else if (config->regBuff == -1) {
ctx->logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Loaded config: %s [%zu-%zu] %s/%s channels=%d nodes=%d ranks=%d pipeOps=%d regBuff=any",
tokens[CONFIG_FIELD_COLLTYPE], config->minBytes, config->maxBytes,
tokens[CONFIG_FIELD_ALGORITHM], tokens[CONFIG_FIELD_PROTOCOL],
config->nChannels, config->nNodes, config->nRanks, config->numPipeOps);
} else if (config->numPipeOps == -1) {
ctx->logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Loaded config: %s [%zu-%zu] %s/%s channels=%d nodes=%d ranks=%d pipeOps=any regBuff=%d",
tokens[CONFIG_FIELD_COLLTYPE], config->minBytes, config->maxBytes,
tokens[CONFIG_FIELD_ALGORITHM], tokens[CONFIG_FIELD_PROTOCOL],
config->nChannels, config->nNodes, config->nRanks, config->regBuff);
} else {
ctx->logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Loaded config: %s [%zu-%zu] %s/%s channels=%d nodes=%d ranks=%d pipeOps=%d regBuff=%d",
tokens[CONFIG_FIELD_COLLTYPE], config->minBytes, config->maxBytes,
tokens[CONFIG_FIELD_ALGORITHM], tokens[CONFIG_FIELD_PROTOCOL],
config->nChannels, config->nNodes, config->nRanks, config->numPipeOps, config->regBuff);
}
}
}
}
fclose(file);
if (ctx->logFunction) {
ctx->logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Loaded %d tuning configurations from %s", ctx->numConfigs, filename);
}
return ncclSuccess;
}
__hidden ncclResult_t pluginInit(size_t nRanks, size_t nNodes, ncclDebugLogger_t logFunction, void **context) {
TunerContext* ctx = (TunerContext*)malloc(sizeof(TunerContext));
if (!ctx) return ncclSystemError;
ctx->configs = NULL; // Initialize to NULL
ctx->numConfigs = 0;
ctx->maxConfigs = 0; // Initialize to 0
ctx->nRanks = nRanks;
ctx->nNodes = nNodes;
ctx->logFunction = logFunction;
if (logFunction) {
logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Initializing tuner for %zu nodes, %zu ranks", nNodes, nRanks);
}
// Try to load config file from environment variable or default location
const char* configFile = getenv("NCCL_TUNER_CONFIG_FILE");
if (!configFile) {
configFile = "nccl_tuner.conf"; // default config file name
}
ncclResult_t result = loadConfig(ctx, configFile);
if (result != ncclSuccess) {
if (ctx->configs) {
free(ctx->configs); // Clean up allocated memory on error
}
free(ctx);
return result;
}
*context = ctx;
return ncclSuccess;
}
__hidden ncclResult_t pluginGetCollInfo(void* context, ncclFunc_t collType, size_t nBytes,
int numPipeOps, float** collCostTable, int numAlgo, int numProto,
int regBuff, int* nChannels) {
// Update NCCL core generated cost table. Updated table will be evaluated by NCCL to pick the best algo/proto combo
float (*table)[NCCL_NUM_PROTOCOLS] = (float (*)[NCCL_NUM_PROTOCOLS])collCostTable;
if (table[NCCL_ALGO_RING][NCCL_PROTO_SIMPLE] != NCCL_ALGO_PROTO_IGNORE) {
table[NCCL_ALGO_RING][NCCL_PROTO_SIMPLE] = 0.0;
}
TunerContext* ctx = (TunerContext*)context;
if (!ctx) return ncclInternalError;
// Default channels
*nChannels = 1;
if (ctx->logFunction) {
ctx->logFunction(NCCL_LOG_TRACE, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: pluginGetCollInfo called - collType=%s, nBytes=%zu, numPipeOps=%d, regBuff=%d, numConfigs=%d",
collTypeToString(collType), nBytes, numPipeOps, regBuff, ctx->numConfigs);
}
// Look for matching configuration
for (int i = 0; i < ctx->numConfigs; i++) {
TuningConfig* config = &ctx->configs[i];
if (ctx->logFunction) {
ctx->logFunction(NCCL_LOG_TRACE, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Checking config %d - collType=%s, minBytes=%zu, maxBytes=%zu, algo=%s, proto=%s, nNodes=%d, nRanks=%d, numPipeOps=%d, regBuff=%d",
i, collTypeToString(config->collType), config->minBytes, config->maxBytes, algorithmToString(config->algorithm), protocolToString(config->protocol),
config->nNodes, config->nRanks, config->numPipeOps, config->regBuff);
}
// Check if this config matches the current collective, size range, topology, pipeline ops, and regBuff
if (config->collType == collType &&
nBytes >= config->minBytes &&
nBytes <= config->maxBytes &&
(config->nNodes == -1 || config->nNodes == (int)ctx->nNodes) &&
(config->nRanks == -1 || config->nRanks == (int)ctx->nRanks) &&
(config->numPipeOps == -1 || config->numPipeOps == numPipeOps) &&
(config->regBuff == -1 || config->regBuff == regBuff)) {
if (ctx->logFunction) {
ctx->logFunction(NCCL_LOG_TRACE, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Config matches. Applying algo=%s, proto=%s, channels=%d",
algorithmToString(config->algorithm), protocolToString(config->protocol), config->nChannels);
}
// Check bounds
if (config->algorithm < numAlgo && config->protocol < numProto) {
if (collCostTable[config->algorithm][config->protocol] != NCCL_ALGO_PROTO_IGNORE) {
if (ctx->logFunction) {
ctx->logFunction(NCCL_LOG_TRACE, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Setting cost table[%s][%s] (%p) = 0.0 (was %.1f)",
algorithmToString(config->algorithm), protocolToString(config->protocol),
&collCostTable[config->algorithm][config->protocol], collCostTable[config->algorithm][config->protocol]);
}
collCostTable[config->algorithm][config->protocol] = 0.0; // Set low cost to prefer this configuration
// Only override channels if not set to -1 (keep default)
if (config->nChannels != -1) {
*nChannels = config->nChannels;
}
if (ctx->logFunction) {
if (config->nChannels == -1) {
ctx->logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Applied config for collType=%s, bytes=%zu, pipeOps=%d, regBuff=%d: algo=%s, proto=%s, channels=default (nodes=%d, ranks=%d)",
collTypeToString(config->collType), nBytes, numPipeOps, regBuff, algorithmToString(config->algorithm), protocolToString(config->protocol),
config->nNodes, config->nRanks);
} else {
ctx->logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Applied config for collType=%s, bytes=%zu, pipeOps=%d, regBuff=%d: algo=%s, proto=%s, channels=%d (nodes=%d, ranks=%d)",
collTypeToString(config->collType), nBytes, numPipeOps, regBuff, algorithmToString(config->algorithm), protocolToString(config->protocol),
config->nChannels, config->nNodes, config->nRanks);
}
}
return ncclSuccess;
} else {
if (ctx->logFunction) {
ctx->logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Algorithm/protocol combination [%s][%s] is marked as IGNORE",
algorithmToString(config->algorithm), protocolToString(config->protocol));
}
}
} else {
if (ctx->logFunction) {
ctx->logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Algorithm/protocol out of bounds - algo=%s (max %d), proto=%s (max %d)",
algorithmToString(config->algorithm), numAlgo, protocolToString(config->protocol), numProto);
}
}
} else {
if (ctx->logFunction) {
ctx->logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: Config does not match - collType match=%d, size match=%d, nodes match=%d, ranks match=%d, pipeOps match=%d, regBuff match=%d",
config->collType == collType,
(nBytes >= config->minBytes && nBytes <= config->maxBytes),
(config->nNodes == -1 || config->nNodes == (int)ctx->nNodes),
(config->nRanks == -1 || config->nRanks == (int)ctx->nRanks),
(config->numPipeOps == -1 || config->numPipeOps == numPipeOps),
(config->regBuff == -1 || config->regBuff == regBuff));
}
}
}
// If no specific config found, apply default behavior
if (ctx->logFunction) {
ctx->logFunction(NCCL_LOG_INFO, NCCL_TUNING, __FILE__, __LINE__,
"TUNER/ExamplePlugin: No matching config found");
}
return ncclSuccess;
}
__hidden ncclResult_t pluginDestroy(void* context) { return ncclSuccess; }
__hidden ncclResult_t pluginDestroy(void* context) {
if (context) {
TunerContext* ctx = (TunerContext*)context;
if (ctx->configs) {
free(ctx->configs); // Free dynamically allocated configs array
}
free(context);
}
return ncclSuccess;
}
#define PLUGIN_NAME "Example"

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# NCCL Tuner Configuration Scripts
This directory contains scripts for optimizing NCCL tuner configurations based on performance data.
## optimize_config.py
A Python script that reads performance data from CSV files and generates optimal NCCL tuner configurations.
### Usage
```bash
python scripts/optimize_config.py [options] <input_csv_file>
```
### Options
- `-o, --output FILE`: Output NCCL tuner config file (default: `nccl_tuner.conf`)
- `-m, --metric METRIC`: Optimization metric (`cost_metric`, `bandwidth_gbps`, `latency_us`)
- `--no-header`: Don't add header comments to output file
- `--dry-run`: Print configurations without writing to file
### CSV Input Format
The input CSV file should have the following columns:
```csv
collective,size_bytes,algorithm,protocol,channels,nodes,ranks,pipeOps,regBuff,cost_metric,bandwidth_gbps,latency_us
```
**Required columns:**
- `collective`: NCCL collective type (`allreduce`, `broadcast`, `reduce`, etc.)
- `size_bytes`: Message size in bytes
- `algorithm`: NCCL algorithm (`tree`, `ring`, `nvls`, etc.)
- `protocol`: NCCL protocol (`simple`, `ll`, `ll128`)
- `channels`: Number of channels (or `-1` for default)
- `nodes`: Number of nodes (or `-1` for any)
- `ranks`: Number of ranks (or `-1` for any)
- `pipeOps`: Number of pipeline operations (or `-1` for any)
- `regBuff`: Registered buffer flag (`0`, `1`, or `-1` for any)
**Optional metrics (must have at least one present):**
- `bandwidth_gbps`: Bandwidth in GB/s (higher is better)
- `latency_us`: Latency in microseconds (lower is better)
### Examples
**Basic usage with cost optimization:**
```bash
python scripts/optimize_config.py sample_performance_data.csv
```
**Optimize for bandwidth and write to custom file:**
```bash
python scripts/optimize_config.py -m bandwidth_gbps -o my_tuner.conf performance_data.csv
```
**Preview configurations without writing:**
```bash
python scripts/optimize_config.py --dry-run performance_data.csv
```
### How It Works
1. **Data Loading**: Reads CSV performance data and validates format
2. **Grouping**: Groups data by collective type, topology (nodes/ranks), and other parameters
3. **Size Ranges**: Automatically bins data into size ranges for optimization
4. **Optimization**: Finds the best performing configuration for each group/size combination
5. **Output**: Generates NCCL tuner config format and appends to specified file
### Default Size Ranges
The script uses these default size ranges (in bytes):
- Small: 0 - 1,024
- Medium: 1,025 - 65,536
- Large: 65,537 - 1,048,576
- XLarge: 1,048,577 - 16,777,216
- XXLarge: 16,777,217 - 4,294,967,295
### Sample Data
See `sample_performance_data.csv` for an example of the expected input format.
### Integration with NCCL
The generated configuration file can be used directly with the NCCL tuner plugin:
```bash
export NCCL_TUNER_CONFIG_FILE=/path/to/optimized_config.conf
export NCCL_TUNER_PLUGIN=/path/to/libnccl-tuner.so
mpirun -np 8 your_nccl_application
```
### Performance Data Collection
To collect performance data for optimization, you can:
1. **Use NCCL benchmarks** with different algorithm/protocol combinations
2. **Profile your applications** with various tuner settings
3. **Run systematic sweeps** across parameter combinations
4. **Use NCCL debug output** to collect timing information
The key is to have comprehensive data covering:
- Different message sizes (small to large)
- Various topologies (single node, multi-node)
- All relevant algorithm/protocol combinations
- Different channel counts and pipeline configurations

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#!/usr/bin/env python3
"""
NCCL Tuner Configuration Optimizer
Reads a CSV file containing performance data across different tuning parameters
and generates optimal NCCL tuner configurations based on the best performing
combinations.
By default, creates growing size ranges that interpolate between the actual data sizes
for each unique dimension (node count, rank count combination). This ensures that
different cluster configurations get their own optimized size boundaries, as
performance characteristics often vary significantly between topologies.
Each dimension gets its own set of ranges starting from 0 and extending to the maximum
size for that dimension, with boundaries at midpoints between consecutive data sizes.
CSV Input Format:
collective,size_bytes,algorithm,protocol,channels,nodes,ranks,pipeOps,regBuff,bandwidth_gbps,latency_us
Output Format (NCCL Tuner Config):
collective_type,min_bytes,max_bytes,algorithm,protocol,channels,nNodes,nRanks,numPipeOps,regBuff
Usage Examples:
# Auto-create dimension-specific interpolated ranges (default)
python3 optimize_config.py data.csv
# Use custom size ranges (applied to all topologies)
python3 optimize_config.py data.csv --size-ranges "0-1024,1025-65536,65537-1048576"
# Use hardcoded default ranges (applied to all topologies)
python3 optimize_config.py data.csv --no-auto-ranges
"""
import csv
import argparse
import sys
import os
from collections import defaultdict
from typing import Dict, List, Tuple, Any
class PerformanceData:
def __init__(self, row: Dict[str, str]):
self.collective = row['collective']
self.size_bytes = int(row['size_bytes'])
self.algorithm = row['algorithm']
self.protocol = row['protocol']
self.channels = int(row['channels']) if row['channels'] != '-1' else -1
self.nodes = int(row['nodes']) if row['nodes'] != '-1' else -1
self.ranks = int(row['ranks']) if row['ranks'] != '-1' else -1
self.pipeOps = int(row['pipeOps']) if row['pipeOps'] != '-1' else -1
self.regBuff = int(row['regBuff']) if row['regBuff'] != '-1' else -1
# Performance metrics
self.bandwidth_gbps = float(row.get('bandwidth_gbps', 0)) # Higher is better
self.latency_us = float(row.get('latency_us', 0)) # Lower is better
def get_config_key(self) -> Tuple:
"""Generate a key for grouping similar configurations"""
return (self.collective, self.nodes, self.ranks, self.pipeOps, self.regBuff)
def get_size_range_key(self, topology_size_ranges: Dict[Tuple[int, int], List[Tuple[int, int]]]) -> Tuple[int, int]:
"""Find which size range this data point belongs to for its dimension"""
topology_key = (self.nodes, self.ranks)
# Get size ranges for this dimension, or fall back to default
if topology_key in topology_size_ranges:
size_ranges = topology_size_ranges[topology_key]
elif (-1, -1) in topology_size_ranges:
size_ranges = topology_size_ranges[(-1, -1)]
else:
# Fallback to first available dimension ranges
size_ranges = next(iter(topology_size_ranges.values()))
for min_size, max_size in size_ranges:
if min_size <= self.size_bytes <= max_size:
return (min_size, max_size)
# If no range found, create a single-point range
return (self.size_bytes, self.size_bytes)
class ConfigOptimizer:
def __init__(self, optimization_metric: str = 'latency_us'):
self.optimization_metric = optimization_metric
# Default size ranges - will be overridden by auto-detection
self.size_ranges = [
(0, 1024),
(1025, 64*1024),
(64*1024+1, 1024*1024),
(1024*1024+1, 16*1024*1024),
(16*1024*1024+1, 4*1024*1024*1024-1)
]
self.auto_size_ranges = True
def set_size_ranges(self, ranges: List[Tuple[int, int]]):
"""Set custom size ranges for optimization"""
self.size_ranges = ranges
self.auto_size_ranges = False
def auto_determine_size_ranges(self, data: List[PerformanceData]) -> Dict[Tuple[int, int], List[Tuple[int, int]]]:
"""Create growing size ranges for each unique (nodes, ranks) dimension"""
if not data:
return {(-1, -1): self.size_ranges}
# Group data by dimension (nodes, ranks)
topology_data = defaultdict(list)
for item in data:
topology_key = (item.nodes, item.ranks)
topology_data[topology_key].append(item)
topology_ranges = {}
for topology_key, items in topology_data.items():
nodes, ranks = topology_key
# Extract unique sizes for this dimension and sort them
unique_sizes = sorted(set(item.size_bytes for item in items))
if len(unique_sizes) <= 1:
# Only one size, create a single range from 0 to that size
size = unique_sizes[0] if unique_sizes else 0
ranges = [(0, size)]
else:
# Create growing ranges that interpolate between data points
ranges = []
for i, size in enumerate(unique_sizes):
if i == 0:
# First range: 0 to midpoint between first and second size
if len(unique_sizes) > 1:
next_size = unique_sizes[i + 1]
max_size = (size + next_size) // 2
else:
max_size = size
min_size = 0
elif i == len(unique_sizes) - 1:
# Last range: previous max + 1 to current size (and beyond)
min_size = ranges[-1][1] + 1
max_size = size
else:
# Intermediate ranges: previous max + 1 to midpoint with next size
min_size = ranges[-1][1] + 1
next_size = unique_sizes[i + 1]
max_size = (size + next_size) // 2
ranges.append((min_size, max_size))
topology_ranges[topology_key] = ranges
print(f"Dimension {nodes} nodes, {ranks} ranks: {len(ranges)} size ranges from {len(unique_sizes)} unique sizes:")
for i, (min_size, max_size) in enumerate(ranges):
# Count data points that fall in this range for this dimension
count = sum(1 for item in items if min_size <= item.size_bytes <= max_size)
actual_sizes = sorted(set(item.size_bytes for item in items if min_size <= item.size_bytes <= max_size))
if actual_sizes:
size_list = ', '.join(f"{s:,}" for s in actual_sizes[:3])
if len(actual_sizes) > 3:
size_list += f", ... (+{len(actual_sizes)-3} more)"
print(f" Range {i+1}: {min_size:,} - {max_size:,} bytes ({count} data points, sizes: {size_list})")
return topology_ranges
def load_data(self, csv_file: str) -> List[PerformanceData]:
"""Load performance data from CSV file"""
data = []
try:
with open(csv_file, 'r') as f:
reader = csv.DictReader(f)
for row in reader:
try:
data.append(PerformanceData(row))
except (ValueError, KeyError) as e:
print(f"Warning: Skipping invalid row: {row} - {e}")
except FileNotFoundError:
print(f"Error: File {csv_file} not found")
sys.exit(1)
except Exception as e:
print(f"Error reading {csv_file}: {e}")
sys.exit(1)
print(f"Loaded {len(data)} performance data points")
# Auto-determine size ranges if enabled
if self.auto_size_ranges and data:
self.topology_size_ranges = self.auto_determine_size_ranges(data)
else:
# Use default ranges for all topologies
self.topology_size_ranges = {(-1, -1): self.size_ranges}
return data
def is_better(self, new_data: PerformanceData, current_best: PerformanceData) -> bool:
"""Determine if new_data is better than current_best"""
if self.optimization_metric == 'bandwidth_gbps':
return new_data.bandwidth_gbps > current_best.bandwidth_gbps
elif self.optimization_metric == 'latency_us':
return new_data.latency_us < current_best.latency_us
else:
# Default to latency
return new_data.latency_us < current_best.latency_us
def optimize_configurations(self, data: List[PerformanceData]) -> List[str]:
"""Find optimal configurations and return as NCCL config strings"""
# Group data by configuration key and size range
grouped_data = defaultdict(lambda: defaultdict(list))
for item in data:
config_key = item.get_config_key()
size_range = item.get_size_range_key(self.topology_size_ranges)
grouped_data[config_key][size_range].append(item)
# Store optimal configurations before combining ranges
optimal_configs = []
for config_key, size_ranges_dict in grouped_data.items():
collective, nodes, ranks, pipeOps, regBuff = config_key
for (min_size, max_size), items in size_ranges_dict.items():
if not items:
continue
# Find the best performing configuration for this size range
best_item = items[0]
for item in items[1:]:
if self.is_better(item, best_item):
best_item = item
# Store the optimal configuration with its range
optimal_configs.append({
'collective': collective,
'min_size': min_size,
'max_size': max_size,
'algorithm': best_item.algorithm,
'protocol': best_item.protocol,
'channels': best_item.channels,
'nodes': best_item.nodes,
'ranks': best_item.ranks,
'pipeOps': best_item.pipeOps,
'regBuff': best_item.regBuff,
'metric_value': getattr(best_item, self.optimization_metric)
})
# Combine sequential ranges with identical tunings
combined_configs = self.combine_sequential_ranges(optimal_configs)
# Generate config strings
configs = []
for config in combined_configs:
config_str = f"{config['collective']},{config['min_size']},{config['max_size']},{config['algorithm']},{config['protocol']},{config['channels']},{config['nodes']},{config['ranks']},{config['pipeOps']},{config['regBuff']}"
configs.append(config_str)
print(f"Optimal for {config['collective']} [{config['min_size']}-{config['max_size']}] nodes={config['nodes']} ranks={config['ranks']}: "
f"{config['algorithm']}/{config['protocol']} channels={config['channels']} "
f"({self.optimization_metric}={config['metric_value']:.3f})")
return configs
def combine_sequential_ranges(self, configs: List[Dict]) -> List[Dict]:
"""Combine sequential ranges that have identical tuning parameters"""
if not configs:
return configs
# Group by collective and topology (nodes, ranks)
topology_groups = defaultdict(list)
for config in configs:
topology_key = (config['collective'], config['nodes'], config['ranks'],
config['pipeOps'], config['regBuff'])
topology_groups[topology_key].append(config)
combined_configs = []
for topology_key, topology_configs in topology_groups.items():
# Sort by min_size to ensure proper ordering
topology_configs.sort(key=lambda x: x['min_size'])
# Group by tuning parameters (algorithm, protocol, channels)
tuning_groups = defaultdict(list)
for config in topology_configs:
tuning_key = (config['algorithm'], config['protocol'], config['channels'])
tuning_groups[tuning_key].append(config)
# For each tuning group, combine sequential ranges
for tuning_key, tuning_configs in tuning_groups.items():
if not tuning_configs:
continue
# Sort by min_size
tuning_configs.sort(key=lambda x: x['min_size'])
# Combine sequential ranges
current_config = tuning_configs[0].copy()
for next_config in tuning_configs[1:]:
# Check if ranges are adjacent or overlapping
if current_config['max_size'] + 1 >= next_config['min_size']:
# Extend the current range
current_config['max_size'] = max(current_config['max_size'], next_config['max_size'])
# Update metric value to the better one
if self.optimization_metric == 'bandwidth_gbps':
if next_config['metric_value'] > current_config['metric_value']:
current_config['metric_value'] = next_config['metric_value']
else: # latency_us or default
if next_config['metric_value'] < current_config['metric_value']:
current_config['metric_value'] = next_config['metric_value']
else:
# Gap between ranges, save current and start new one
combined_configs.append(current_config)
current_config = next_config.copy()
# Add the last configuration
combined_configs.append(current_config)
# Sort final configs by collective, nodes, ranks, then min_size
combined_configs.sort(key=lambda x: (x['collective'], x['nodes'], x['ranks'], x['min_size']))
original_count = len(configs)
combined_count = len(combined_configs)
if combined_count < original_count:
print(f"Combined {original_count} ranges into {combined_count} ranges "
f"(reduced by {original_count - combined_count})")
return combined_configs
def append_to_config_file(self, configs: List[str], config_file: str, add_header: bool = True):
"""Append optimized configurations to NCCL tuner config file"""
try:
# Create directory if it doesn't exist
config_dir = os.path.dirname(config_file)
if config_dir and not os.path.exists(config_dir):
os.makedirs(config_dir)
print(f"Created directory: {config_dir}")
# Check if file exists and has content
file_exists = os.path.exists(config_file)
add_separator = False
if file_exists:
with open(config_file, 'r') as f:
content = f.read().strip()
add_separator = len(content) > 0
print(f"Appending to existing file: {config_file}")
else:
print(f"Creating new file: {config_file}")
with open(config_file, 'a') as f:
if add_separator:
f.write("\n\n")
if add_header:
f.write(f"# Optimized configurations generated by optimize_config.py\n")
f.write(f"# Optimization metric: {self.optimization_metric}\n")
f.write(f"# Format: collective_type,min_bytes,max_bytes,algorithm,protocol,channels,nNodes,nRanks,numPipeOps,regBuff\n")
for config in configs:
f.write(f"{config}\n")
if file_exists:
print(f"Appended {len(configs)} optimized configurations to {config_file}")
else:
print(f"Created {config_file} with {len(configs)} optimized configurations")
except PermissionError:
print(f"Error: Permission denied writing to {config_file}")
print("Try running with appropriate permissions or choose a different output location")
sys.exit(1)
except OSError as e:
print(f"Error: Cannot create/write to {config_file}: {e}")
print("Check that the path is valid and you have write permissions")
sys.exit(1)
except Exception as e:
print(f"Unexpected error writing to {config_file}: {e}")
sys.exit(1)
def main():
parser = argparse.ArgumentParser(description="Optimize NCCL tuner configurations from performance data")
parser.add_argument("csv_file", help="Input CSV file with performance data")
parser.add_argument("-o", "--output", default="nccl_tuner.conf",
help="Output NCCL tuner config file (default: nccl_tuner.conf)")
parser.add_argument("-m", "--metric", choices=['bandwidth_gbps', 'latency_us'],
default='latency_us', help="Optimization metric (default: latency_us)")
parser.add_argument("--no-header", action="store_true",
help="Don't add header comments to output file")
parser.add_argument("--dry-run", action="store_true",
help="Print configurations without writing to file")
parser.add_argument("--no-auto-ranges", action="store_true",
help="Disable automatic size range determination (use default ranges)")
parser.add_argument("--size-ranges", type=str,
help="Custom size ranges as comma-separated pairs: 'min1-max1,min2-max2,...'")
args = parser.parse_args()
optimizer = ConfigOptimizer(args.metric)
# Handle size range configuration
if args.size_ranges:
# Parse custom size ranges
try:
ranges = []
for range_str in args.size_ranges.split(','):
min_size, max_size = map(int, range_str.split('-'))
ranges.append((min_size, max_size))
optimizer.set_size_ranges(ranges)
print(f"Using custom size ranges: {ranges}")
except ValueError:
print("Error: Invalid size ranges format. Use 'min1-max1,min2-max2,...'")
sys.exit(1)
elif args.no_auto_ranges:
# Disable auto-ranging
optimizer.auto_size_ranges = False
print("Using default hardcoded size ranges")
else:
# Auto-ranging is enabled by default - creates one bucket per unique size
optimizer.auto_size_ranges = True
print("Auto-ranging enabled: will create one bucket per unique size in data")
# Load and optimize data
data = optimizer.load_data(args.csv_file)
if not data:
print("No valid data found in CSV file")
sys.exit(1)
configs = optimizer.optimize_configurations(data)
if args.dry_run:
print("\nGenerated configurations:")
for config in configs:
print(config)
else:
optimizer.append_to_config_file(configs, args.output, not args.no_header)
if __name__ == "__main__":
main()

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collective,size_bytes,algorithm,protocol,channels,nodes,ranks,pipeOps,regBuff,cost_metric,bandwidth_gbps,latency_us
allreduce,1024,tree,simple,2,1,8,-1,-1,0.15,45.2,12.5
allreduce,1024,ring,simple,4,1,8,-1,-1,0.12,52.1,10.8
allreduce,1024,tree,ll,2,1,8,-1,-1,0.18,41.3,15.2
allreduce,1024,ring,ll,4,1,8,-1,-1,0.14,48.7,12.1
allreduce,32768,tree,simple,2,1,8,-1,-1,0.25,156.8,25.3
allreduce,32768,ring,simple,4,1,8,-1,-1,0.18,189.2,18.4
allreduce,32768,ring,ll128,8,1,8,-1,-1,0.16,201.5,16.2
allreduce,1048576,ring,simple,4,1,8,-1,-1,0.45,425.6,45.1
allreduce,1048576,ring,ll128,8,1,8,-1,-1,0.38,482.3,38.7
allreduce,1048576,nvls,simple,16,1,8,-1,-1,0.32,551.2,32.1
broadcast,1024,tree,simple,2,1,8,-1,-1,0.08,89.4,8.2
broadcast,1024,ring,simple,4,1,8,-1,-1,0.12,71.3,12.1
broadcast,32768,tree,simple,2,1,8,-1,-1,0.18,234.7,18.5
broadcast,32768,ring,ll128,4,1,8,-1,-1,0.15,267.8,15.2
broadcast,1048576,ring,simple,4,1,8,-1,-1,0.35,612.4,35.1
broadcast,1048576,ring,ll128,8,1,8,-1,-1,0.28,702.1,28.3
allreduce,1024,tree,simple,2,2,16,-1,-1,0.22,38.1,22.4
allreduce,1024,ring,simple,4,2,16,-1,-1,0.19,42.7,19.6
allreduce,32768,ring,simple,4,2,16,-1,-1,0.28,145.2,28.1
allreduce,32768,ring,ll128,8,2,16,-1,-1,0.24,167.8,24.3
allreduce,1048576,ring,simple,4,2,16,-1,-1,0.58,387.5,58.2
allreduce,1048576,ring,ll128,8,2,16,-1,-1,0.48,456.9,48.1
allreduce,1048576,nvls,simple,16,2,16,-1,-1,0.42,512.6,42.3
1 collective size_bytes algorithm protocol channels nodes ranks pipeOps regBuff cost_metric bandwidth_gbps latency_us
2 allreduce 1024 tree simple 2 1 8 -1 -1 0.15 45.2 12.5
3 allreduce 1024 ring simple 4 1 8 -1 -1 0.12 52.1 10.8
4 allreduce 1024 tree ll 2 1 8 -1 -1 0.18 41.3 15.2
5 allreduce 1024 ring ll 4 1 8 -1 -1 0.14 48.7 12.1
6 allreduce 32768 tree simple 2 1 8 -1 -1 0.25 156.8 25.3
7 allreduce 32768 ring simple 4 1 8 -1 -1 0.18 189.2 18.4
8 allreduce 32768 ring ll128 8 1 8 -1 -1 0.16 201.5 16.2
9 allreduce 1048576 ring simple 4 1 8 -1 -1 0.45 425.6 45.1
10 allreduce 1048576 ring ll128 8 1 8 -1 -1 0.38 482.3 38.7
11 allreduce 1048576 nvls simple 16 1 8 -1 -1 0.32 551.2 32.1
12 broadcast 1024 tree simple 2 1 8 -1 -1 0.08 89.4 8.2
13 broadcast 1024 ring simple 4 1 8 -1 -1 0.12 71.3 12.1
14 broadcast 32768 tree simple 2 1 8 -1 -1 0.18 234.7 18.5
15 broadcast 32768 ring ll128 4 1 8 -1 -1 0.15 267.8 15.2
16 broadcast 1048576 ring simple 4 1 8 -1 -1 0.35 612.4 35.1
17 broadcast 1048576 ring ll128 8 1 8 -1 -1 0.28 702.1 28.3
18 allreduce 1024 tree simple 2 2 16 -1 -1 0.22 38.1 22.4
19 allreduce 1024 ring simple 4 2 16 -1 -1 0.19 42.7 19.6
20 allreduce 32768 ring simple 4 2 16 -1 -1 0.28 145.2 28.1
21 allreduce 32768 ring ll128 8 2 16 -1 -1 0.24 167.8 24.3
22 allreduce 1048576 ring simple 4 2 16 -1 -1 0.58 387.5 58.2
23 allreduce 1048576 ring ll128 8 2 16 -1 -1 0.48 456.9 48.1
24 allreduce 1048576 nvls simple 16 2 16 -1 -1 0.42 512.6 42.3

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#
# Makefile for NCCL Tuner Plugin Unit Tests
#
CC := gcc
CFLAGS := -Wall -Wextra -g -std=c99 -fPIC
INC := -I. -I../nccl
TARGET := test_plugin
SOURCES := test_plugin.c
# Default target
all: $(TARGET)
# Build the test executable
$(TARGET): $(SOURCES)
$(CC) $(CFLAGS) $(INC) -o $(TARGET) $(SOURCES)
# Run the tests
test: $(TARGET)
./$(TARGET) $(TEST_CASE)
# Run tests with verbose output
test-verbose: $(TARGET)
NCCL_DEBUG=INFO ./$(TARGET) $(TEST_CASE)
# Clean build artifacts
clean:
rm -f $(TARGET) *.o *.gcov *.gcda *.gcno test_*.conf
.PHONY: all test test-verbose clean

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# NCCL Tuner Plugin Unit Tests
This directory contains comprehensive unit tests for the NCCL tuner plugin. The tests verify all major functionality including configuration parsing, matching logic, and cost table updates.
## Test Structure
```
test/
├── test_plugin.c # Main unit test file
├── Makefile # Build system for tests
└── README.md # This file
```
## Building and Running Tests
### Quick Start
```bash
# Build and run all tests
make test
# Or step by step
make # Build test executable
./test_plugin # Run tests
```
### Advanced Testing
```bash
# Run with memory leak detection (requires valgrind)
make test-memory
# Run with verbose logging
make test-verbose
# Generate code coverage report (requires gcov)
make coverage
# Create sample test configuration files
make test-configs
```
## Test Coverage
The unit tests cover the following functionality:
### 1. **Plugin Initialization (`test_plugin_init`)**
- Tests successful plugin initialization
- Verifies context allocation
- Tests cleanup on destroy
### 2. **Configuration Parsing (`test_config_parsing_valid`, `test_config_parsing_invalid`)**
- Valid CSV format parsing
- Comment and empty line handling
- Invalid format graceful handling
- Environment variable configuration
### 3. **Collective Type Matching (`test_collective_matching`)**
- Correct matching of allreduce, broadcast, etc.
- Algorithm/protocol selection
- Channel configuration
### 4. **Size Range Matching (`test_size_matching`)**
- Small, medium, large message size handling
- Proper range boundary checking
- Multiple size-based configurations
### 5. **Topology Matching (`test_topology_matching`)**
- Single-node vs multi-node configurations
- Exact nNodes/nRanks matching
- Wildcard matching (-1 values)
### 6. **Default Channels (`test_default_channels`)**
- Proper handling of -1 channel specification
- Preservation of NCCL default behavior
### 7. **Registered Buffer Matching (`test_regbuff_matching`)**
- Configurations based on regBuff parameter
- Registered vs non-registered buffer handling
- Backward compatibility with configs missing regBuff
### 8. **Pipeline Operations Matching (`test_pipeops_matching`)**
- Configurations based on numPipeOps parameter
- Single vs multiple pipeline operation handling
- Backward compatibility with configs missing numPipeOps
### 9. **Fallback Behavior (`test_no_match_fallback`)**
- Default behavior when no config matches
- Ring/Simple algorithm fallback
## Test Output
Successful test run:
```
Running NCCL Tuner Plugin Unit Tests
=====================================
PASS: test_plugin_init
PASS: test_config_parsing_valid
PASS: test_config_parsing_invalid
PASS: test_collective_matching
PASS: test_size_matching
PASS: test_topology_matching
PASS: test_default_channels
PASS: test_regbuff_matching
PASS: test_pipeops_matching
PASS: test_no_match_fallback
=====================================
Test Results: 9/9 tests passed
All tests PASSED!
```
Failed test example:
```
FAIL: test_collective_matching - Tree/Simple should have low cost
Test Results: 8/9 tests passed
Some tests FAILED!
```
## Mock NCCL Implementation
The tests use the actual NCCL header files from the `../nccl/` directory:
- `tuner.h` - Complete NCCL tuner interface and type definitions
- `common.h` - Common NCCL types and logging functions
- `err.h` - NCCL error codes
This allows testing with the real NCCL interface definitions while still being able to run tests without the full NCCL library installation.
## Integration with CI/CD
```bash
# Install tests for CI/CD pipeline
make install-test
# Run as part of automated testing
make test && echo "Tests passed" || echo "Tests failed"
```
## Memory Testing
The tests can be run with valgrind for memory leak detection:
```bash
make test-memory
```
This will detect:
- Memory leaks
- Invalid memory access
- Use of uninitialized memory
## Code Coverage
Generate code coverage reports to ensure comprehensive testing:
```bash
make coverage
# Creates test_plugin.c.gcov with line-by-line coverage
```
## Adding New Tests
To add a new test:
1. Create a new test function in `test_plugin.c`:
```c
int test_new_feature() {
// Test setup
TEST_ASSERT(condition, "description");
// Test cleanup
TEST_PASS();
}
```
2. Add the test to the main function:
```c
total++; passed += test_new_feature();
```
3. Rebuild and run:
```bash
make test
```
## Debugging Tests
For debugging failed tests:
```bash
# Compile with debug symbols
make CFLAGS="-g -O0 -DDEBUG"
# Run with gdb
gdb ./test_plugin
```
## Cleaning Up
```bash
# Remove all build artifacts and temporary files
make clean
```
This comprehensive test suite ensures the NCCL tuner plugin works correctly across all supported configurations and edge cases.

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/*************************************************************************
* Unit tests for NCCL Tuner Plugin
************************************************************************/
#define _GNU_SOURCE // Enable setenv/unsetenv and other GNU extensions
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <assert.h>
#include <unistd.h>
#include <sys/stat.h>
#include <stdarg.h>
// Include NCCL tuner header (which includes common.h and err.h)
#include "tuner.h"
// Include plugin source for testing
#include "../plugin.c"
// Test framework macros
#define TEST_ASSERT(condition, message) \
do { \
if (!(condition)) { \
printf("FAIL: %s - %s\n", __func__, message); \
return 0; \
} \
} while(0)
#define TEST_PASS() \
do { \
printf("PASS: %s\n", __func__); \
return 1; \
} while(0)
// Global test state
static int test_log_count = 0;
// Mock logger function
void mock_logger(ncclDebugLogLevel level, unsigned long flags,
const char* file, int line, const char* fmt, ...) {
(void)flags; // Suppress unused parameter warning
test_log_count++;
// Check if we should print based on NCCL_DEBUG level
const char* debug_level = getenv("NCCL_DEBUG");
int should_print = 0;
if (debug_level) {
if (strcmp(debug_level, "TRACE") == 0) {
should_print = 1; // Print everything
} else if (strcmp(debug_level, "INFO") == 0 && level <= NCCL_LOG_INFO) {
should_print = 1; // Print INFO and below
} else if (strcmp(debug_level, "WARN") == 0 && level <= NCCL_LOG_WARN) {
should_print = 1; // Print WARN and below
}
}
if (!should_print) return;
// Convert log level to string
const char* level_str;
switch(level) {
case NCCL_LOG_NONE: level_str = "NONE"; break;
case NCCL_LOG_VERSION: level_str = "VERSION"; break;
case NCCL_LOG_WARN: level_str = "WARN"; break;
case NCCL_LOG_INFO: level_str = "INFO"; break;
case NCCL_LOG_ABORT: level_str = "ABORT"; break;
case NCCL_LOG_TRACE: level_str = "TRACE"; break;
default: level_str = "UNKNOWN"; break;
}
// Print log header
printf("[TUNER:%s:%s:%d] ", level_str, file, line);
// Print formatted message
va_list args;
va_start(args, fmt);
vprintf(fmt, args);
va_end(args);
printf("\n");
}
// Helper function to create test config file
void create_test_config(const char* filename, const char* content) {
FILE* f = fopen(filename, "w");
if (f) {
fprintf(f, "%s", content);
fclose(f);
}
}
// Test 1: Plugin initialization
int test_plugin_init() {
void* context = NULL;
// Test successful initialization
ncclResult_t result = pluginInit(8, 2, mock_logger, &context);
TEST_ASSERT(result == ncclSuccess, "Plugin init should succeed");
TEST_ASSERT(context != NULL, "Context should be allocated");
// Clean up
pluginDestroy(context);
TEST_PASS();
}
// Test 2: Configuration file parsing - valid CSV
int test_config_parsing_valid() {
const char* test_config =
"# Test configuration\n"
"allreduce,0,65536,tree,simple,2,1,-1,-1,-1\n"
"broadcast,0,32768,ring,ll128,4,2,16,-1,-1\n"
"# Comment line\n"
"\n" // Empty line
"reduce,1024,2048,tree,simple,-1,-1,-1,-1,-1\n";
create_test_config("test_valid.conf", test_config);
// Set environment variable to use our test config
setenv("NCCL_TUNER_CONFIG_FILE", "test_valid.conf", 1);
void* context = NULL;
ncclResult_t result = pluginInit(16, 2, mock_logger, &context);
TEST_ASSERT(result == ncclSuccess, "Plugin init with valid config should succeed");
// Clean up
pluginDestroy(context);
unlink("test_valid.conf");
unsetenv("NCCL_TUNER_CONFIG_FILE");
TEST_PASS();
}
// Test 3: Configuration file parsing - invalid CSV
int test_config_parsing_invalid() {
const char* test_config =
"allreduce,0,65536,tree,simple,2,1 # Missing nRanks and other fields\n"
"invalid_collective,0,1024,ring,simple,1,1,1,-1,-1\n"
"broadcast,abc,def,ring,simple,1,1,1,-1,-1\n"; // Invalid numbers
create_test_config("test_invalid.conf", test_config);
setenv("NCCL_TUNER_CONFIG_FILE", "test_invalid.conf", 1);
void* context = NULL;
ncclResult_t result = pluginInit(8, 1, mock_logger, &context);
// Should still succeed but with no valid configs loaded
TEST_ASSERT(result == ncclSuccess, "Plugin init should succeed even with invalid config");
// Clean up
pluginDestroy(context);
unlink("test_invalid.conf");
unsetenv("NCCL_TUNER_CONFIG_FILE");
TEST_PASS();
}
// Test 4: Collective type matching
int test_collective_matching() {
const char* test_config =
"allreduce,0,65536,tree,simple,8,1,-1,-1,-1\n"
"broadcast,0,32768,ring,ll128,4,-1,-1,-1,-1\n";
create_test_config("test_match.conf", test_config);
setenv("NCCL_TUNER_CONFIG_FILE", "test_match.conf", 1);
void* context = NULL;
pluginInit(8, 1, mock_logger, &context);
// Create mock cost table
float cost_table[NCCL_NUM_ALGORITHMS][NCCL_NUM_PROTOCOLS];
float* cost_table_ptr[NCCL_NUM_ALGORITHMS];
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
cost_table_ptr[i] = cost_table[i];
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0; // Default high cost
}
}
int nChannels;
// Test allreduce matching (should match first config)
ncclResult_t result = pluginGetCollInfo(context, ncclFuncAllReduce, 32768, 1,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
0, &nChannels);
TEST_ASSERT(result == ncclSuccess, "GetCollInfo should succeed");
mock_logger(NCCL_LOG_INFO, NCCL_ALL, __FILE__, __LINE__,
"DEBUG: Checking cost_table[TREE][SIMPLE] (%p) = %.1f (expecting 0.0)",
&cost_table[NCCL_ALGO_TREE][NCCL_PROTO_SIMPLE], cost_table[NCCL_ALGO_TREE][NCCL_PROTO_SIMPLE]);
TEST_ASSERT(cost_table[NCCL_ALGO_TREE][NCCL_PROTO_SIMPLE] == 0.0, "Tree/Simple should have low cost");
TEST_ASSERT(nChannels == 8, "Should set 8 channels");
// Test broadcast matching (should match second config)
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0; // Reset costs
}
}
result = pluginGetCollInfo(context, ncclFuncBroadcast, 16384, 1,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
0, &nChannels);
TEST_ASSERT(result == ncclSuccess, "GetCollInfo should succeed");
mock_logger(NCCL_LOG_INFO, NCCL_ALL, __FILE__, __LINE__,
"DEBUG: Checking cost_table[RING][LL128] (%p) = %.1f (expecting 0.0)",
&cost_table[NCCL_ALGO_RING][NCCL_PROTO_LL128], cost_table[NCCL_ALGO_RING][NCCL_PROTO_LL128]);
TEST_ASSERT(cost_table[NCCL_ALGO_RING][NCCL_PROTO_LL128] == 0.0, "Ring/LL128 should have low cost");
TEST_ASSERT(nChannels == 4, "Should set 4 channels");
// Clean up
pluginDestroy(context);
unlink("test_match.conf");
unsetenv("NCCL_TUNER_CONFIG_FILE");
TEST_PASS();
}
// Test 5: Size range matching
int test_size_matching() {
const char* test_config =
"allreduce,0,1024,tree,simple,2,-1,-1,-1,-1\n"
"allreduce,1025,65536,ring,simple,4,-1,-1,-1,-1\n"
"allreduce,65537,4294967295,ring,ll128,8,-1,-1,-1,-1\n";
create_test_config("test_size.conf", test_config);
setenv("NCCL_TUNER_CONFIG_FILE", "test_size.conf", 1);
void* context = NULL;
pluginInit(8, 1, mock_logger, &context);
float cost_table[NCCL_NUM_ALGORITHMS][NCCL_NUM_PROTOCOLS];
float* cost_table_ptr[NCCL_NUM_ALGORITHMS];
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
cost_table_ptr[i] = cost_table[i];
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0;
}
}
int nChannels = 1;
pluginGetCollInfo(context, ncclFuncAllReduce, 512, 1,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
0, &nChannels);
mock_logger(NCCL_LOG_INFO, NCCL_ALL, __FILE__, __LINE__,
"DEBUG: Small message - checking cost_table[TREE][SIMPLE] (%p) = %.1f (expecting 0.0)",
&cost_table[NCCL_ALGO_TREE][NCCL_PROTO_SIMPLE], cost_table[NCCL_ALGO_TREE][NCCL_PROTO_SIMPLE]);
TEST_ASSERT(cost_table[NCCL_ALGO_TREE][NCCL_PROTO_SIMPLE] == 0.0, "Small: Tree/Simple should have low cost");
TEST_ASSERT(nChannels == 2, "Small: Should set 2 channels");
// Test medium message (should match second config)
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0;
}
}
pluginGetCollInfo(context, ncclFuncAllReduce, 32768, 1,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
0, &nChannels);
mock_logger(NCCL_LOG_INFO, NCCL_ALL, __FILE__, __LINE__,
"DEBUG: Medium message - checking cost_table[RING][SIMPLE] (%p) = %.1f (expecting 0.0)",
&cost_table[NCCL_ALGO_RING][NCCL_PROTO_SIMPLE], cost_table[NCCL_ALGO_RING][NCCL_PROTO_SIMPLE]);
TEST_ASSERT(cost_table[NCCL_ALGO_RING][NCCL_PROTO_SIMPLE] == 0.0, "Medium: Ring/Simple should have low cost");
TEST_ASSERT(nChannels == 4, "Medium: Should set 4 channels");
// Test large message (should match third config)
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0;
}
}
pluginGetCollInfo(context, ncclFuncAllReduce, 1048576, 1,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
0, &nChannels);
mock_logger(NCCL_LOG_INFO, NCCL_ALL, __FILE__, __LINE__,
"DEBUG: Large message - checking cost_table[RING][LL128] (%p) = %.1f (expecting 0.0)",
&cost_table[NCCL_ALGO_RING][NCCL_PROTO_LL128], cost_table[NCCL_ALGO_RING][NCCL_PROTO_LL128]);
TEST_ASSERT(cost_table[NCCL_ALGO_RING][NCCL_PROTO_LL128] == 0.0, "Large: Ring/LL128 should have low cost");
TEST_ASSERT(nChannels == 8, "Large: Should set 8 channels");
// Clean up
pluginDestroy(context);
unlink("test_size.conf");
unsetenv("NCCL_TUNER_CONFIG_FILE");
TEST_PASS();
}
// Test 6: Topology matching
int test_topology_matching() {
const char* test_config =
"allreduce,0,65536,tree,simple,2,1,-1,-1,-1\n" // Single node only
"allreduce,0,65536,ring,simple,4,4,32,-1,-1\n" // 4 nodes, 32 ranks exactly
"allreduce,0,65536,ring,ll128,8,-1,-1,-1,-1\n"; // Any topology
create_test_config("test_topo.conf", test_config);
setenv("NCCL_TUNER_CONFIG_FILE", "test_topo.conf", 1);
// Test with single node setup
void* context1 = NULL;
pluginInit(8, 1, mock_logger, &context1); // 8 ranks, 1 node
float cost_table[NCCL_NUM_ALGORITHMS][NCCL_NUM_PROTOCOLS];
float* cost_table_ptr[NCCL_NUM_ALGORITHMS];
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
cost_table_ptr[i] = cost_table[i];
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0;
}
}
int nChannels;
pluginGetCollInfo(context1, ncclFuncAllReduce, 32768, 1,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
0, &nChannels);
TEST_ASSERT(cost_table[NCCL_ALGO_TREE][NCCL_PROTO_SIMPLE] == 0.0, "Single node: Should match tree config");
TEST_ASSERT(nChannels == 2, "Single node: Should set 2 channels");
pluginDestroy(context1);
// Test with 4 nodes, 32 ranks setup
void* context2 = NULL;
pluginInit(32, 4, mock_logger, &context2); // 32 ranks, 4 nodes
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0;
}
}
pluginGetCollInfo(context2, ncclFuncAllReduce, 32768, 1,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
0, &nChannels);
TEST_ASSERT(cost_table[NCCL_ALGO_RING][NCCL_PROTO_SIMPLE] == 0.0, "4-node: Should match ring/simple config");
TEST_ASSERT(nChannels == 4, "4-node: Should set 4 channels");
// Clean up
unlink("test_topo.conf");
unsetenv("NCCL_TUNER_CONFIG_FILE");
TEST_PASS();
}
// Test 7: Default channels behavior (-1)
int test_default_channels() {
const char* test_config =
"allreduce,0,65536,tree,simple,-1,-1,-1,-1,-1\n"; // Use default channels
create_test_config("test_default.conf", test_config);
setenv("NCCL_TUNER_CONFIG_FILE", "test_default.conf", 1);
void* context = NULL;
pluginInit(8, 1, mock_logger, &context);
float cost_table[NCCL_NUM_ALGORITHMS][NCCL_NUM_PROTOCOLS];
float* cost_table_ptr[NCCL_NUM_ALGORITHMS];
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
cost_table_ptr[i] = cost_table[i];
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0;
}
}
int nChannels = 99; // Set to known value
pluginGetCollInfo(context, ncclFuncAllReduce, 32768, 1,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
0, &nChannels);
TEST_ASSERT(cost_table[NCCL_ALGO_TREE][NCCL_PROTO_SIMPLE] == 0.0, "Should apply algorithm/protocol");
TEST_ASSERT(nChannels == 1, "Should keep default channels (1) when config has -1");
// Clean up
pluginDestroy(context);
unlink("test_default.conf");
unsetenv("NCCL_TUNER_CONFIG_FILE");
TEST_PASS();
}
// Test 8: regBuff matching
int test_regbuff_matching() {
const char* test_config =
"allreduce,0,65536,tree,simple,2,-1,-1,-1,1\n" // Registered buffers only
"allreduce,0,65536,ring,simple,4,-1,-1,-1,0\n" // Non-registered buffers only
"allreduce,0,65536,ring,ll128,8,-1,-1,-1,-1\n"; // Any buffer type (backward compatible)
create_test_config("test_regbuff.conf", test_config);
setenv("NCCL_TUNER_CONFIG_FILE", "test_regbuff.conf", 1);
void* context = NULL;
pluginInit(8, 1, mock_logger, &context);
float cost_table[NCCL_NUM_ALGORITHMS][NCCL_NUM_PROTOCOLS];
float* cost_table_ptr[NCCL_NUM_ALGORITHMS];
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
cost_table_ptr[i] = cost_table[i];
}
int nChannels;
// Test registered buffer (should match first config)
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0;
}
}
pluginGetCollInfo(context, ncclFuncAllReduce, 32768, 1,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
1, &nChannels); // regBuff = 1 (registered)
TEST_ASSERT(cost_table[NCCL_ALGO_TREE][NCCL_PROTO_SIMPLE] == 0.0, "Registered buffer: Tree/Simple should have low cost");
TEST_ASSERT(nChannels == 2, "Registered buffer: Should set 2 channels");
// Test non-registered buffer (should match second config)
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0;
}
}
pluginGetCollInfo(context, ncclFuncAllReduce, 32768, 1,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
0, &nChannels); // regBuff = 0 (non-registered)
TEST_ASSERT(cost_table[NCCL_ALGO_RING][NCCL_PROTO_SIMPLE] == 0.0, "Non-registered buffer: Ring/Simple should have low cost");
TEST_ASSERT(nChannels == 4, "Non-registered buffer: Should set 4 channels");
// Test backward compatibility - config without regBuff should match any regBuff value
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0;
}
}
// First try with regBuff=2 (unusual value, should match third config)
pluginGetCollInfo(context, ncclFuncAllReduce, 32768, 1,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
2, &nChannels); // regBuff = 2 (only third config should match)
TEST_ASSERT(cost_table[NCCL_ALGO_RING][NCCL_PROTO_LL128] == 0.0, "Any regBuff: Ring/LL128 should have low cost");
TEST_ASSERT(nChannels == 8, "Any regBuff: Should set 8 channels");
// Clean up
pluginDestroy(context);
unlink("test_regbuff.conf");
unsetenv("NCCL_TUNER_CONFIG_FILE");
TEST_PASS();
}
// Test 9: numPipeOps matching
int test_pipeops_matching() {
const char* test_config =
"allreduce,0,65536,tree,simple,2,-1,-1,1,-1\n" // Single pipeline op
"allreduce,0,65536,ring,simple,4,-1,-1,4,-1\n" // Multiple pipeline ops
"allreduce,0,65536,ring,ll128,8,-1,-1,-1,-1\n"; // Any pipeline ops (backward compatible)
create_test_config("test_pipeops.conf", test_config);
setenv("NCCL_TUNER_CONFIG_FILE", "test_pipeops.conf", 1);
void* context = NULL;
pluginInit(8, 1, mock_logger, &context);
float cost_table[NCCL_NUM_ALGORITHMS][NCCL_NUM_PROTOCOLS];
float* cost_table_ptr[NCCL_NUM_ALGORITHMS];
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
cost_table_ptr[i] = cost_table[i];
}
int nChannels;
// Test single pipeline op (should match first config)
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0;
}
}
pluginGetCollInfo(context, ncclFuncAllReduce, 32768, 1,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
0, &nChannels);
TEST_ASSERT(cost_table[NCCL_ALGO_TREE][NCCL_PROTO_SIMPLE] == 0.0, "Single pipeOp: Tree/Simple should have low cost");
TEST_ASSERT(nChannels == 2, "Single pipeOp: Should set 2 channels");
// Test multiple pipeline ops (should match second config)
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0;
}
}
pluginGetCollInfo(context, ncclFuncAllReduce, 32768, 4,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
0, &nChannels);
TEST_ASSERT(cost_table[NCCL_ALGO_RING][NCCL_PROTO_SIMPLE] == 0.0, "Multiple pipeOps: Ring/Simple should have low cost");
TEST_ASSERT(nChannels == 4, "Multiple pipeOps: Should set 4 channels");
// Test different number of pipeline ops (should match third config - backward compatible)
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0;
}
}
pluginGetCollInfo(context, ncclFuncAllReduce, 32768, 2,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
0, &nChannels);
TEST_ASSERT(cost_table[NCCL_ALGO_RING][NCCL_PROTO_LL128] == 0.0, "Any pipeOps: Ring/LL128 should have low cost");
TEST_ASSERT(nChannels == 8, "Any pipeOps: Should set 8 channels");
// Clean up
pluginDestroy(context);
unlink("test_pipeops.conf");
unsetenv("NCCL_TUNER_CONFIG_FILE");
TEST_PASS();
}
// Test 10: No matching configuration (fallback behavior)
int test_no_match_fallback() {
const char* test_config =
"broadcast,0,1024,tree,simple,2,-1,-1,-1,-1\n"; // Only broadcast config
create_test_config("test_fallback.conf", test_config);
setenv("NCCL_TUNER_CONFIG_FILE", "test_fallback.conf", 1);
void* context = NULL;
pluginInit(8, 1, mock_logger, &context);
float cost_table[NCCL_NUM_ALGORITHMS][NCCL_NUM_PROTOCOLS];
float* cost_table_ptr[NCCL_NUM_ALGORITHMS];
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
cost_table_ptr[i] = cost_table[i];
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0;
}
}
int nChannels;
// Try allreduce (should not match, use fallback)
pluginGetCollInfo(context, ncclFuncAllReduce, 32768, 1,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
0, &nChannels);
mock_logger(NCCL_LOG_INFO, NCCL_ALL, __FILE__, __LINE__,
"DEBUG: Fallback test - checking cost_table[RING][SIMPLE] (%p) = %.1f (expecting 0.0)",
&cost_table[NCCL_ALGO_RING][NCCL_PROTO_SIMPLE], cost_table[NCCL_ALGO_RING][NCCL_PROTO_SIMPLE]);
TEST_ASSERT(cost_table[NCCL_ALGO_RING][NCCL_PROTO_SIMPLE] == 1.0, "Should use pass through unmodified");
TEST_ASSERT(nChannels == 1, "Should use default channels");
// Clean up
pluginDestroy(context);
unlink("test_fallback.conf");
unsetenv("NCCL_TUNER_CONFIG_FILE");
TEST_PASS();
}
// Test 11: Large configuration files (testing dynamic allocation)
int test_large_config() {
const char* large_config_file = "test_large.conf";
// Create a large configuration file with many entries
// This tests the dynamic allocation functionality
FILE* f = fopen(large_config_file, "w");
TEST_ASSERT(f != NULL, "Should be able to create large config file");
// Write header comment
fprintf(f, "# Large configuration file for testing dynamic allocation\n");
fprintf(f, "# This file contains many configurations to test memory allocation\n");
// Generate a large number of configurations (much more than the old MAX_CONFIGS=100)
const int num_configs = 500; // 5x the old static limit
const char* collectives[] = {"allreduce", "broadcast", "reduce", "allgather", "reducescatter"};
const char* algorithms[] = {"tree", "ring", "collnet_direct", "nvls"};
const char* protocols[] = {"simple", "ll", "ll128"};
for (int i = 0; i < num_configs; i++) {
// Vary the configurations to create realistic test data
const char* coll = collectives[i % 5];
const char* algo = algorithms[i % 4];
const char* proto = protocols[i % 3];
size_t min_bytes = (i * 1024) % 1048576; // Vary from 0 to 1MB
size_t max_bytes = min_bytes + 65536; // 64KB range
int channels = (i % 8) + 1; // 1-8 channels
int nodes = (i % 4) == 0 ? -1 : (i % 4); // Mix of -1 and 1-3 nodes
int ranks = (i % 8) == 0 ? -1 : (i % 32) + 1; // Mix of -1 and 1-32 ranks
int pipeOps = (i % 3) == 0 ? -1 : (i % 4) + 1; // Mix of -1 and 1-4 pipeOps
int regBuff = (i % 3) == 0 ? -1 : (i % 2); // Mix of -1, 0, 1
fprintf(f, "%s,%zu,%zu,%s,%s,%d,%d,%d,%d,%d\n",
coll, min_bytes, max_bytes, algo, proto, channels, nodes, ranks, pipeOps, regBuff);
}
fclose(f);
// Set environment to use our large config file
setenv("NCCL_TUNER_CONFIG_FILE", large_config_file, 1);
// Initialize plugin with large config
void* context = NULL;
ncclResult_t result = pluginInit(16, 4, mock_logger, &context);
TEST_ASSERT(result == ncclSuccess, "Plugin init with large config should succeed");
TEST_ASSERT(context != NULL, "Context should be allocated");
// Verify that configurations were loaded
TunerContext* ctx = (TunerContext*)context;
TEST_ASSERT(ctx->numConfigs == num_configs, "Should load all configurations from large file");
TEST_ASSERT(ctx->maxConfigs == num_configs, "maxConfigs should match allocated size");
TEST_ASSERT(ctx->configs != NULL, "Configs array should be dynamically allocated");
// Test that we can access configurations throughout the array
// (This would have failed with the old static MAX_CONFIGS=100 limit)
for (int i = 0; i < ctx->numConfigs; i++) {
TuningConfig* config = &ctx->configs[i];
// Basic sanity checks on the loaded configurations
TEST_ASSERT(config->collType >= ncclFuncBroadcast && config->collType <= ncclFuncAllReduce,
"Collective type should be valid");
TEST_ASSERT(config->maxBytes >= config->minBytes, "maxBytes should be >= minBytes");
TEST_ASSERT(config->nChannels > 0, "nChannels should be positive");
}
// Test specific configuration access at various indices
// Index 0 (first config)
TuningConfig* first_config = &ctx->configs[0];
TEST_ASSERT(first_config != NULL, "First config should be accessible");
// Index in middle
TuningConfig* mid_config = &ctx->configs[num_configs / 2];
TEST_ASSERT(mid_config != NULL, "Middle config should be accessible");
// Index near end (this would have crashed with static array of 100)
TuningConfig* late_config = &ctx->configs[num_configs - 1];
TEST_ASSERT(late_config != NULL, "Last config should be accessible");
// Test memory allocation size - verify we didn't over-allocate
mock_logger(NCCL_LOG_INFO, NCCL_ALL, __FILE__, __LINE__,
"Successfully loaded %d configurations (dynamic allocation)", ctx->numConfigs);
mock_logger(NCCL_LOG_INFO, NCCL_ALL, __FILE__, __LINE__,
"Memory allocated for %d configurations (%zu bytes total)",
ctx->maxConfigs, ctx->maxConfigs * sizeof(TuningConfig));
// Test that the plugin can still find matching configurations from the large set
float cost_table[NCCL_NUM_ALGORITHMS][NCCL_NUM_PROTOCOLS];
float* cost_table_ptr[NCCL_NUM_ALGORITHMS];
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
cost_table_ptr[i] = cost_table[i];
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0; // Default high cost
}
}
int nChannels;
// Try to find a matching configuration - should work with large config set
result = pluginGetCollInfo(context, ncclFuncAllReduce, 32768, 1,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
0, &nChannels);
TEST_ASSERT(result == ncclSuccess, "GetCollInfo should work with large config set");
// Clean up
pluginDestroy(context);
unlink(large_config_file);
unsetenv("NCCL_TUNER_CONFIG_FILE");
TEST_PASS();
}
// Test 12: Very large configuration stress test
int test_very_large_config_stress() {
const char* stress_config_file = "test_stress.conf";
// Create an even larger configuration file to stress test the implementation
FILE* f = fopen(stress_config_file, "w");
TEST_ASSERT(f != NULL, "Should be able to create stress test config file");
fprintf(f, "# Stress test configuration with very large number of entries\n");
// Generate an extremely large number of configurations
const int stress_configs = 2000; // 20x the old static limit
for (int i = 0; i < stress_configs; i++) {
// Create varied but valid configurations
fprintf(f, "allreduce,%d,%d,ring,simple,4,-1,-1,-1,-1\n",
i * 512, (i * 512) + 1024);
}
fclose(f);
setenv("NCCL_TUNER_CONFIG_FILE", stress_config_file, 1);
// Test initialization with stress config
void* context = NULL;
ncclResult_t result = pluginInit(8, 2, mock_logger, &context);
TEST_ASSERT(result == ncclSuccess, "Plugin should handle very large config files");
TunerContext* ctx = (TunerContext*)context;
TEST_ASSERT(ctx->numConfigs == stress_configs, "Should load all stress test configurations");
TEST_ASSERT(ctx->configs != NULL, "Stress test configs should be allocated");
mock_logger(NCCL_LOG_INFO, NCCL_ALL, __FILE__, __LINE__,
"Stress test - loaded %d configurations successfully", stress_configs);
mock_logger(NCCL_LOG_INFO, NCCL_ALL, __FILE__, __LINE__,
"Memory usage: %zu bytes for configuration array",
stress_configs * sizeof(TuningConfig));
// Verify we can access configurations throughout the entire range
for (int i = 0; i < stress_configs; i += 100) { // Sample every 100th config
TuningConfig* config = &ctx->configs[i];
TEST_ASSERT(config->collType == ncclFuncAllReduce, "Config should have correct collective type");
TEST_ASSERT(config->minBytes == (size_t)(i * 512), "Config should have correct minBytes");
}
// Clean up
pluginDestroy(context);
unlink(stress_config_file);
unsetenv("NCCL_TUNER_CONFIG_FILE");
TEST_PASS();
}
// Test 13: Edge case - empty config file
int test_empty_config() {
const char* empty_config_file = "test_empty.conf";
// Create empty config file (only comments)
create_test_config(empty_config_file,
"# Empty configuration file\n"
"# No actual configurations\n"
"\n"
"\n");
setenv("NCCL_TUNER_CONFIG_FILE", empty_config_file, 1);
void* context = NULL;
ncclResult_t result = pluginInit(8, 2, mock_logger, &context);
TEST_ASSERT(result == ncclSuccess, "Plugin should handle empty config files");
TunerContext* ctx = (TunerContext*)context;
TEST_ASSERT(ctx->numConfigs == 0, "Should have zero configurations");
TEST_ASSERT(ctx->maxConfigs == 0, "Should have zero max configurations");
TEST_ASSERT(ctx->configs == NULL, "Should not allocate memory for empty config");
// Test that plugin still works with no configurations (fallback behavior)
float cost_table[NCCL_NUM_ALGORITHMS][NCCL_NUM_PROTOCOLS];
float* cost_table_ptr[NCCL_NUM_ALGORITHMS];
for (int i = 0; i < NCCL_NUM_ALGORITHMS; i++) {
cost_table_ptr[i] = cost_table[i];
for (int j = 0; j < NCCL_NUM_PROTOCOLS; j++) {
cost_table[i][j] = 1.0;
}
}
int nChannels;
result = pluginGetCollInfo(context, ncclFuncAllReduce, 32768, 1,
cost_table_ptr, NCCL_NUM_ALGORITHMS, NCCL_NUM_PROTOCOLS,
0, &nChannels);
TEST_ASSERT(result == ncclSuccess, "GetCollInfo should work with empty config");
// Clean up
pluginDestroy(context);
unlink(empty_config_file);
unsetenv("NCCL_TUNER_CONFIG_FILE");
TEST_PASS();
}
// Test runner function pointer type
typedef int (*TestFunction)(void);
// Test registry
typedef struct {
const char* name;
TestFunction func;
const char* description;
} TestCase;
// All available tests
TestCase test_cases[] = {
{"init", test_plugin_init, "Plugin initialization"},
{"config-valid", test_config_parsing_valid, "Valid configuration parsing"},
{"config-invalid", test_config_parsing_invalid, "Invalid configuration parsing"},
{"collective", test_collective_matching, "Collective type matching"},
{"size", test_size_matching, "Size range matching"},
{"topology", test_topology_matching, "Topology matching"},
{"channels", test_default_channels, "Default channels behavior"},
{"regbuff", test_regbuff_matching, "Registered buffer matching"},
{"pipeops", test_pipeops_matching, "Pipeline operations matching"},
{"fallback", test_no_match_fallback, "Fallback behavior"},
{"large-config", test_large_config, "Large configuration files (dynamic allocation)"},
{"stress-config", test_very_large_config_stress, "Very large configuration stress test"},
{"empty-config", test_empty_config, "Empty configuration file handling"},
{NULL, NULL, NULL} // End marker
};
// Show help/usage information
void show_help(const char* program_name) {
printf("Usage: %s [test_name ...]\n\n", program_name);
printf("Available tests:\n");
for (int i = 0; test_cases[i].name != NULL; i++) {
printf(" %-15s - %s\n", test_cases[i].name, test_cases[i].description);
}
printf("\nExamples:\n");
printf(" %s # Run all tests\n", program_name);
printf(" %s init # Run only initialization test\n", program_name);
printf(" %s init collective # Run initialization and collective tests\n", program_name);
printf(" %s --help # Show this help\n", program_name);
}
// Find test by name
TestFunction find_test(const char* name) {
for (int i = 0; test_cases[i].name != NULL; i++) {
if (strcmp(test_cases[i].name, name) == 0) {
return test_cases[i].func;
}
}
return NULL;
}
// Main test runner
int main(int argc, char* argv[]) {
int passed = 0, total = 0;
// Check for help
if (argc > 1 && (strcmp(argv[1], "--help") == 0 || strcmp(argv[1], "-h") == 0)) {
show_help(argv[0]);
return 0;
}
printf("Running NCCL Tuner Plugin Unit Tests\n");
printf("=====================================\n");
if (argc == 1) {
// No arguments - run all tests
for (int i = 0; test_cases[i].name != NULL; i++) {
total++;
passed += test_cases[i].func();
}
} else {
// Run specific tests
for (int arg = 1; arg < argc; arg++) {
TestFunction test_func = find_test(argv[arg]);
if (test_func) {
total++;
passed += test_func();
} else {
printf("ERROR: Unknown test '%s'\n", argv[arg]);
printf("Use --help to see available tests\n");
return 1;
}
}
}
printf("\n=====================================\n");
printf("Test Results: %d/%d tests passed\n", passed, total);
if (passed == total) {
printf("All tests PASSED!\n");
return 0;
} else {
printf("Some tests FAILED!\n");
return 1;
}
}

View File

@ -40,10 +40,12 @@ ifeq ($(shell test "0$(CUDA_MAJOR)" -lt 12; echo $$?),0)
CUDA8_GENCODE += -gencode=arch=compute_35,code=sm_35
endif
CUDA9_GENCODE = -gencode=arch=compute_70,code=sm_70
CUDA10_GENCODE = -gencode=arch=compute_75,code=sm_75
CUDA11_GENCODE = -gencode=arch=compute_80,code=sm_80
CUDA12_GENCODE = -gencode=arch=compute_90,code=sm_90
CUDA13_GENCODE = -gencode=arch=compute_100,code=sm_100 \
-gencode=arch=compute_120,code=sm_120
CUDA12_8_GENCODE = -gencode=arch=compute_100,code=sm_100 \
-gencode=arch=compute_120,code=sm_120
CUDA13_GENCODE = -gencode=arch=compute_110,code=sm_110
CUDA8_PTX = -gencode=arch=compute_61,code=compute_61
CUDA9_PTX = -gencode=arch=compute_70,code=compute_70
@ -53,10 +55,10 @@ CUDA13_PTX = -gencode=arch=compute_120,code=compute_120
ifeq ($(shell test "0$(CUDA_MAJOR)" -ge 13; echo $$?),0)
# Prior to SM75 is deprecated from CUDA13.0 onwards
NVCC_GENCODE ?= $(CUDA11_GENCODE) $(CUDA12_GENCODE) $(CUDA13_GENCODE) $(CUDA13_PTX)
NVCC_GENCODE ?= $(CUDA10_GENCODE) $(CUDA11_GENCODE) $(CUDA12_GENCODE) $(CUDA12_8_GENCODE) $(CUDA13_GENCODE) $(CUDA13_PTX)
else ifeq ($(shell test "0$(CUDA_MAJOR)" -eq 12 -a "0$(CUDA_MINOR)" -ge 8; echo $$?),0)
# Include Blackwell support if we're using CUDA12.8 or above
NVCC_GENCODE ?= $(CUDA8_GENCODE) $(CUDA9_GENCODE) $(CUDA11_GENCODE) $(CUDA12_GENCODE) $(CUDA13_GENCODE) $(CUDA13_PTX)
NVCC_GENCODE ?= $(CUDA8_GENCODE) $(CUDA9_GENCODE) $(CUDA11_GENCODE) $(CUDA12_GENCODE) $(CUDA12_8_GENCODE) $(CUDA13_PTX)
else ifeq ($(shell test "0$(CUDA_MAJOR)" -eq 11 -a "0$(CUDA_MINOR)" -ge 8 -o "0$(CUDA_MAJOR)" -gt 11; echo $$?),0)
# Include Hopper support if we're using CUDA11.8 or above
NVCC_GENCODE ?= $(CUDA8_GENCODE) $(CUDA9_GENCODE) $(CUDA11_GENCODE) $(CUDA12_GENCODE) $(CUDA12_PTX)
@ -74,7 +76,7 @@ $(info NVCC_GENCODE is ${NVCC_GENCODE})
ifeq ($(shell test "0$(CUDA_MAJOR)" -ge 13; echo $$?),0)
CXXSTD ?= -std=c++17
else
CXXSTD ?= -std=c++11
CXXSTD ?= -std=c++14
endif
CXXFLAGS := -DCUDA_MAJOR=$(CUDA_MAJOR) -DCUDA_MINOR=$(CUDA_MINOR) -fPIC -fvisibility=hidden \

View File

@ -1,6 +1,6 @@
##### version
NCCL_MAJOR := 2
NCCL_MINOR := 27
NCCL_PATCH := 3
NCCL_PATCH := 7
NCCL_SUFFIX :=
PKG_REVISION := 1

51
src/CMakeLists.txt Normal file
View File

@ -0,0 +1,51 @@
include(../cmake/common.cmake)
find_package(CUDAToolkit REQUIRED)
set(nccl_Major ${nccl_VERSION_MAJOR})
set(nccl_Minor ${nccl_VERSION_MINOR})
set(nccl_Patch ${nccl_VERSION_PATCH})
# NCCL_VERSION(X,Y,Z) ((X) * 10000 + (Y) * 100 + (Z))
math(
EXPR
nccl_Version
"${nccl_VERSION_MAJOR} * 10000 + ${nccl_VERSION_MINOR} * 100 + ${nccl_VERSION_PATCH}"
)
set(nccl_Suffix)
configure_file(${CMAKE_CURRENT_SOURCE_DIR}/nccl.h.in
${CMAKE_CURRENT_SOURCE_DIR}/include/nccl.h)
file(
GLOB
SRC_FILES
"${CMAKE_CURRENT_SOURCE_DIR}/*.cc"
"${CMAKE_CURRENT_SOURCE_DIR}/misc/*.cc"
"${CMAKE_CURRENT_SOURCE_DIR}/transport/*.cc"
"${CMAKE_CURRENT_SOURCE_DIR}/collectives/*.cc"
"${CMAKE_CURRENT_SOURCE_DIR}/graph/*.cc")
set(HEADER_FILES "${CMAKE_CURRENT_SOURCE_DIR}/include/nccl.h")
set(NCCL_LIBS nccl;nccl_static)
add_library(nccl SHARED ${SRC_FILES})
add_library(nccl_static STATIC ${SRC_FILES})
foreach(lib_name IN LISTS NCCL_LIBS)
nccl_add_target_options(${lib_name})
target_include_directories(
${lib_name}
PRIVATE $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/include>
$<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/include/plugin>)
target_include_directories(${lib_name} PRIVATE "${CUDAToolkit_INCLUDE_DIRS}")
target_sources(
${lib_name}
PUBLIC FILE_SET
public_headers
TYPE
HEADERS
BASE_DIRS
"${CMAKE_CURRENT_SOURCE_DIR}"
FILES
${HEADER_FILES})
endforeach()

35
src/device/CMakeLists.txt Normal file
View File

@ -0,0 +1,35 @@
set(CU_FILES onerank_reduce.cu functions.cu)
add_library(colldevice OBJECT ${CU_FILES})
set(datatypes "i8;u8;i32;u32;i64;u64;f16;f32;f64")
if(CMAKE_CUDA_COMPILER_VERSION VERSION_GREATER_EQUAL "11")
list(APPEND datatypes bf16)
endif()
set(ops "sum;prod;min;max;premulsum;sumpostdiv")
list(LENGTH ops op_num)
math(EXPR op_num "${op_num} - 1")
list(LENGTH datatypes datatype_num)
math(EXPR datatype_num "${datatype_num} - 1")
set(base_files "sendrecv;all_reduce;all_gather;broadcast;reduce;reduce_scatter")
foreach(base IN LISTS base_files)
foreach(opn RANGE ${op_num})
list(GET ops ${opn} op)
foreach(dtn RANGE ${datatype_num})
list(GET datatypes ${dtn} dt)
set(new_file ${CMAKE_CURRENT_BINARY_DIR}/${base}_${op}_${dt}.cu)
configure_file(${CMAKE_CURRENT_SOURCE_DIR}/${base}.cu ${new_file}
COPYONLY)
set_property(SOURCE ${new_file} PROPERTY COMPILE_DEFINITIONS
NCCL_OP=${opn} NCCL_TYPE=${dtn})
target_sources(colldevice PRIVATE ${new_file})
endforeach()
endforeach()
endforeach()
target_include_directories(
colldevice PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/../../include
${CMAKE_CURRENT_SOURCE_DIR})
# Compiled kernels and collectives with relocatable device code ...
set_property(TARGET colldevice PROPERTY CUDA_SEPARABLE_COMPILATION ON)

View File

@ -36,9 +36,8 @@ define COMPILE
$(call COMPILE$(or $3,$(suffix $2)),$1,$2)
endef
ifeq ($(shell echo "$$((1000*$(CUDA_MAJOR) + 10*$(CUDA_MINOR) >= 12080))"),1)
NVCC_GENCODE_LDMC_FP8 = -gencode=arch=compute_100a,code=sm_100a \
-gencode=arch=compute_120a,code=sm_120a
ifeq ($(shell echo "$$((1000*$(CUDA_MAJOR) + 10*$(CUDA_MINOR) >= 12090))"),1)
NVCC_GENCODE_LDMC_FP8 = -gencode=arch=compute_100f,code=sm_100f
else ifeq ($(shell echo "$$((1000*$(CUDA_MAJOR) + 10*$(CUDA_MINOR) >= 12070))"),1)
NVCC_GENCODE_LDMC_FP8 = -gencode=arch=compute_100a,code=sm_100a
else

View File

@ -1009,7 +1009,7 @@ struct Apply_LoadMultimem {
DEFINE_Apply_LoadMultimem_minmax_v4_and_xparts(__nv_bfloat16, bf16x2, 4)
#endif
#if NCCL_CUDA_ARCH_FAMILY_SPECIFIC == 1000 || NCCL_CUDA_ARCH_FAMILY_SPECIFIC == 1010 || NCCL_CUDA_ARCH_SPECIFIC == 1200 || NCCL_CUDA_ARCH_SPECIFIC == 1210
#if NCCL_CUDA_ARCH_SPECIFIC == 1000 || NCCL_CUDA_ARCH_SPECIFIC == 1010 || NCCL_CUDA_ARCH_FAMILY_SPECIFIC == 1000 || NCCL_CUDA_ARCH_FAMILY_SPECIFIC == 1010 || NCCL_CUDA_ARCH_SPECIFIC == 1200 || NCCL_CUDA_ARCH_SPECIFIC == 1210
DEFINE_Apply_LoadMultimem_sum_v4_and_xparts(__nv_fp8_e4m3, e4m3x4, 4)
DEFINE_Apply_LoadMultimem_minmax_v4_and_xparts(__nv_fp8_e4m3, e4m3x4, 4)
DEFINE_Apply_LoadMultimem_sum_v4_and_xparts(__nv_fp8_e5m2, e5m2x4, 4)

View File

@ -108,7 +108,7 @@ def required_cuda(k):
if k.algo in ldmc_algos:
cudart = 12070
arch = None
specific_sms = [100, 120]
specific_sms = ["100a", "101a", "100f", "101f", "120a", "121a"]
return (cudart, arch, specific_sms)
################################################################################
@ -145,7 +145,7 @@ def kernel_conds(k):
if not specific_sms:
arch_cond = "__CUDA_ARCH__ >= %d"%arch
else:
arch_cond = " || ".join(["0"] + ["NCCL_CUDA_ARCH_SPECIFIC==%d"%(10*sm) for sm in specific_sms])
arch_cond = " || ".join(["0"] + ["NCCL_CUDA_ARCH_%sSPECIFIC==%d"%("FAMILY_" if sm[-1] == "f" else "", 10*int(sm.replace('a', '').replace('f', ''))) for sm in specific_sms])
return cudart_cond, arch_cond
def instantiate(k):

View File

@ -38,12 +38,9 @@ ncclResult_t ncclInitKernelsForDevice(int cudaArch, int maxSharedMem, size_t* ma
if (fn == nullptr) continue;
cudaError_t errcode = cudaFuncGetAttributes(&attr, fn);
if (errcode == cudaErrorNoKernelImageForDevice) continue;
CUDACHECKGOTO(errcode, result, ignore0);
if (errcode != cudaSuccess) continue; // Silently ignore failures
if (maxStackSize) {
if (attr.localSizeBytes > *maxStackSize) *maxStackSize = attr.localSizeBytes;
ignore0:;
}
if (carveout) {
CUDACHECKGOTO(cudaFuncSetAttribute(fn,

View File

@ -175,6 +175,13 @@ ncclResult_t ncclGetLocalCpu(struct ncclTopoSystem* system, int gpu, int* retCpu
return ncclSuccess;
}
static int mergePathType(int type0, int type1){
int max = std::max(type0,type1);
int min = std::min(type0,type1);
if(max == PATH_PHB && min == PATH_C2C) return PATH_P2C;
else return max;
}
static ncclResult_t addInterStep(struct ncclTopoSystem* system, int tx, int ix, int t1, int i1, int t2, int i2) {
struct ncclTopoNode* cpuNode = system->nodes[tx].nodes+ix;
struct ncclTopoNode* srcNode = system->nodes[t1].nodes+i1;
@ -187,7 +194,7 @@ static ncclResult_t addInterStep(struct ncclTopoSystem* system, int tx, int ix,
// Update path characteristics
srcNode->paths[t2][i2].count = l;
srcNode->paths[t2][i2].type = std::max(srcNode->paths[tx][ix].type, cpuNode->paths[t2][i2].type);
srcNode->paths[t2][i2].type = mergePathType(srcNode->paths[tx][ix].type, cpuNode->paths[t2][i2].type);
if (tx == GPU) srcNode->paths[t2][i2].type = PATH_PXN;
srcNode->paths[t2][i2].bw = std::min(srcNode->paths[tx][ix].bw, cpuNode->paths[t2][i2].bw);
return ncclSuccess;
@ -674,9 +681,9 @@ ncclResult_t ncclTopoComputePaths(struct ncclTopoSystem* system, struct ncclComm
int c;
NCCLCHECK(ncclGetLocalCpu(system, g, &c));
if (c == -1) continue;
if (gpuNode->paths[NET][n].type == PATH_PHB && gpuNode->paths[CPU][c].type == PATH_C2C) {
gpuNode->paths[NET][n].type = PATH_P2C;
netNode->paths[GPU][g].type = PATH_P2C;
if (mergePathType(gpuNode->paths[CPU][c].type, netNode->paths[CPU][c].type) == PATH_P2C) {
gpuNode->paths[NET][n].type = std::min(PATH_P2C, gpuNode->paths[NET][n].type);
netNode->paths[GPU][g].type = std::min(PATH_P2C, netNode->paths[GPU][g].type);
}
}
}
@ -695,16 +702,15 @@ ncclResult_t ncclTopoComputePaths(struct ncclTopoSystem* system, struct ncclComm
// PXN = PCI + NVLink.
struct ncclTopoNode* peerNode = system->nodes[GPU].nodes+localGpuIndex;
// Only use PXN for NIC n if remote GPU p ...
if (/* (1) is either connected to the NIC with PXB*/
(peerNode->paths[NET][n].type <= PATH_PXB ||
/* or with P2C and PxN over C2C is enabled */
(ncclParamPxnC2c() && peerNode->paths[NET][n].type == PATH_P2C)) &&
int pxnType = ncclParamPxnC2c() ? PATH_P2C : PATH_PXB;
if (/* (1) is connected to the NIC with PxN type*/
peerNode->paths[NET][n].type <= pxnType &&
/* and (2) is connected to us through NVLink */
peerNode->paths[GPU][g].type <= PATH_NVL &&
/* and (3) is on the same node as us */
NCCL_TOPO_ID_SYSTEM_ID(peerNode->id) == NCCL_TOPO_ID_SYSTEM_ID(gpu->id) &&
/* and (4) has either higher bw to that NIC or avoid going through the CPU*/
(peerNode->paths[NET][n].bw > gpu->paths[NET][n].bw || gpu->paths[NET][n].type > PATH_PXB))
/* and (4) has either higher bw to that NIC or avoid going through the CPU (path.type is > PATH_PXN)*/
(peerNode->paths[NET][n].bw > gpu->paths[NET][n].bw || gpu->paths[NET][n].type > PATH_PXN))
// We can use that GPU as relay to communicate with that NIC.
// Only enabling it in the GPU->NIC direction for now to favor
// receiving locally and sending remotely (consistent with net.cc)
@ -725,6 +731,12 @@ ncclResult_t ncclTopoComputePaths(struct ncclTopoSystem* system, struct ncclComm
}
}
}
// Pre-compute NET local gpus to accelerate search
for (int n=0; n<system->nodes[NET].count; n++) {
struct ncclTopoNode* net = system->nodes[NET].nodes+n;
NCCLCHECK(ncclTopoGetLocalGpu(system, net->id, &net->net.localGpu));
}
return ncclSuccess;
}

View File

@ -437,6 +437,65 @@ ncclResult_t ncclTopoCompareGraphs(struct ncclTopoSystem* system, struct ncclTop
return ncclSuccess;
}
// Add the preferred NICs ordered by GPU first
static ncclResult_t ncclTopoPrefNetsGpuFirst(struct ncclTopoSystem* system, int gpu, int nets[NCCL_TOPO_MAX_NODES], int* netCount) {
const int nGpus = (gpu == -1) ? system->nodes[GPU].count : 1;
int gpuCount = nGpus;
int gpuIds[NCCL_TOPO_MAX_NODES] = {gpu};
int firstNets[NCCL_TOPO_MAX_NODES];
if (gpu == -1)
for (int g = 0; g < nGpus; g++) gpuIds[g] = g;
for (int c = 0; c < MAXCHANNELS; c++) {
for (int g = 0; g < nGpus; g++) {
if (gpuIds[g] == -1) continue;
int localNet;
int64_t netId;
struct ncclTopoNode* gpu = system->nodes[GPU].nodes + gpuIds[g];
NCCLCHECK(ncclTopoGetLocalNet(system, gpu->gpu.rank, c, &netId, NULL));
NCCLCHECK(ncclTopoIdToIndex(system, NET, netId, &localNet));
// store the first net found for each GPU in case of duplicates
if(c == 0) firstNets[g] = localNet;
// if the NET has already been returned for channel 0, that GPU is done
if (c > 0 && firstNets[g] == localNet) {
gpuIds[g] = -1;
gpuCount--;
continue;
}
// only add it to the list if it doesn't already exist
int found = 0;
while (found < (*netCount) && nets[found] != localNet) found++;
if (found == (*netCount)) nets[(*netCount)++] = localNet;
}
if (gpuCount == 0) break;
}
return ncclSuccess;
}
// Add the preferred NICs ordered by channels first
static ncclResult_t ncclTopoPrefNetsChannelFirst(struct ncclTopoSystem* system, int gpu, int nets[NCCL_TOPO_MAX_NODES], int* netCount) {
for (int g = 0; g < system->nodes[GPU].count; g++) {
if (gpu != -1 && gpu != g) continue;
int localNetCount = 0, localNets[MAXCHANNELS];
struct ncclTopoNode* gpu = system->nodes[GPU].nodes + g;
for (int c = 0; c < MAXCHANNELS; c++) {
int64_t netId;
NCCLCHECK(ncclTopoGetLocalNet(system, gpu->gpu.rank, c, &netId, NULL));
NCCLCHECK(ncclTopoIdToIndex(system, NET, netId, localNets + localNetCount));
if (localNetCount > 0 && localNets[localNetCount] == localNets[0]) break;
localNetCount++;
}
// Append NICs to list
for (int i = 0; i < localNetCount; i++) {
int n = localNets[i];
int found = 0;
while (found < (*netCount) && nets[found] != n) found++;
if (found == (*netCount)) nets[(*netCount)++] = n;
}
}
return ncclSuccess;
}
// Build a sorted list of the NETs to try.
//
// "gpu" can be set to -1 to build a list suitable for all GPUs (search start) or to a given gpu
@ -445,39 +504,25 @@ ncclResult_t ncclTopoCompareGraphs(struct ncclTopoSystem* system, struct ncclTop
// The list is built the following way:
// 1. Select NETs starting with those close to GPU(s), based on paths[n].type.
// 2. add other NETs satisfying typeInter but not already in the list.
NCCL_PARAM(ScatterEnable, "MNNVL_SCATTER_NETS_ENABLE", 1);
ncclResult_t ncclTopoSelectNets(struct ncclTopoSystem* system, int typeInter, int gpu, int nets[NCCL_TOPO_MAX_NODES], int* netCountRet) {
ncclResult_t ret = ncclSuccess;
int netCount = 0;
int localNetCount;
int localNets[MAXCHANNELS];
// First add the preferred NICs
for (int g=0; g<system->nodes[GPU].count; g++) {
if (gpu != -1 && gpu != g) continue;
localNetCount = 0;
struct ncclTopoNode* gpu = system->nodes[GPU].nodes+g;
for (int c = 0; c<MAXCHANNELS; c++) {
int64_t netId;
NCCLCHECK(ncclTopoGetLocalNet(system, gpu->gpu.rank, c, &netId, NULL));
NCCLCHECK(ncclTopoIdToIndex(system, NET, netId, localNets+localNetCount));
if (localNetCount > 0 && localNets[localNetCount] == localNets[0]) break;
localNetCount++;
}
// Append NICs to list
for (int i=0; i<localNetCount; i++) {
int n = localNets[i];
int found = 0;
while (found<netCount && nets[found] != n) found++;
if (found == netCount) nets[netCount++] = n;
}
// First add the preferred NETs.
if (system->nHosts > 1 && ncclParamScatterEnable()) {
// For MNNVL systems, we sort the devices by GPU first, then by channel
NCCLCHECK(ncclTopoPrefNetsGpuFirst(system, gpu, nets, &netCount));
} else {
// For other systems, we sort the devices by channel first, then by GPU
NCCLCHECK(ncclTopoPrefNetsChannelFirst(system, gpu, nets, &netCount));
}
// Then add others satisfying typeInter
for (int t=0; t <= typeInter; t++) {
for (int g=0; g<system->nodes[GPU].count; g++) {
for (int g = 0; g < system->nodes[GPU].count; g++) {
if (gpu != -1 && gpu != g) continue;
localNetCount = 0;
int localNetCount = 0, localNets[MAXCHANNELS];
struct ncclTopoNode* gpu = system->nodes[GPU].nodes+g;
struct ncclTopoLinkList* paths = gpu->paths[NET];
for (int n=0; n<system->nodes[NET].count && n<MAXCHANNELS; n++) {
@ -625,8 +670,7 @@ ncclResult_t ncclTopoSearchRecNet(struct ncclTopoSystem* system, struct ncclTopo
if (graph->pattern == NCCL_TOPO_PATTERN_NVLS || graph->pattern == NCCL_TOPO_PATTERN_COLLNET_DIRECT) {
// NVLS search only tries to find NIC:GPU combinations to compute the heads.
if (graph->nChannels < netCount) {
int gpu;
NCCLCHECK(ncclTopoGetLocalGpu(system, net->id, &gpu));
int gpu = net->net.localGpu;
if (gpu != -1) {
int duplicate = 0;
// check whether there is duplicate head when one GPU connects with multiple NICs
@ -643,13 +687,12 @@ ncclResult_t ncclTopoSearchRecNet(struct ncclTopoSystem* system, struct ncclTopo
}
}
} else {
if (graph->nChannels > 0) {
if (graph->nChannels > 0 && graph->sameChannels == 1) {
// Try to replay the last channel
int g;
NCCLCHECK(ncclTopoReplayGetGpu(system, graph, -1, &g));
NCCLCHECK(ncclTopoSearchTryGpu(system, graph, saveGraph, 0, backToNet, backToFirstRank, FORCED_ORDER_REPLAY, time, NET, n, g));
}
if (graph->nChannels == 0 || graph->sameChannels == 0) {
} else {
if (graph->nChannels == 0 && system->nodes[NVS].count == 0) {
// Always try the PCI order first to set a reference, but don't count in the timeout nor let it run for long
int t = 1 << 10;
@ -658,11 +701,16 @@ ncclResult_t ncclTopoSearchRecNet(struct ncclTopoSystem* system, struct ncclTopo
}
// Then try the most local GPUs
int localGpu = net->net.localGpu;
if (localGpu != -1) {
NCCLCHECK(ncclTopoSearchTryGpu(system, graph, saveGraph, 0, backToNet, backToFirstRank, 0, time, NET, n, localGpu));
}
int localGpus[NCCL_TOPO_MAX_NODES], localGpuCount, pathType;
NCCLCHECK(ncclTopoGetLocal(system, NET, n, GPU, localGpus, &localGpuCount, &pathType));
// if no GPUs are connected, skip this net
if (pathType == PATH_DIS) continue;
for (int g = 0; g < localGpuCount; ++g) {
if (localGpus[g] == localGpu) continue; // We already tried this one
NCCLCHECK(ncclTopoSearchTryGpu(system, graph, saveGraph, 0, backToNet, backToFirstRank, 0, time, NET, n, localGpus[g]));
}
}
@ -749,8 +797,8 @@ struct kvDict kvDictLinkType[] = {
{ "NVB", PATH_NVB },
{ "PIX", PATH_PIX },
{ "PXB", PATH_PXB },
{ "PXN", PATH_PXN },
{ "P2C", PATH_P2C },
{ "PXN", PATH_PXN },
{ "PHB", PATH_PHB },
{ "SYS", PATH_SYS },
{ NULL, 0 }
@ -798,8 +846,10 @@ ncclResult_t ncclTopoGetGraphFromXmlSub(struct ncclXmlNode *xmlGraph, struct ncc
NCCLCHECK(xmlGetAttrInt(xmlGraph, "nchannels", &graph->nChannels));
NCCLCHECK(xmlGetAttrFloat(xmlGraph, "speedintra", &graph->bwIntra));
NCCLCHECK(xmlGetAttrFloat(xmlGraph, "speedinter", &graph->bwInter));
if (xmlGetAttrFloat(xmlGraph, "latencyinter", &graph->latencyInter) != ncclSuccess) graph->latencyInter = 0.0;
const char* str;
NCCLCHECK(xmlGetAttr(xmlGraph, "latencyinter", &str));
if (!str) INFO(NCCL_GRAPH, "latencyinter not found in graph, using 0.0");
graph->latencyInter = str ? strtof(str, NULL) : 0.0;
NCCLCHECK(xmlGetAttr(xmlGraph, "typeintra", &str));
NCCLCHECK(kvConvertToInt(str, &graph->typeIntra, kvDictLinkType));
NCCLCHECK(xmlGetAttr(xmlGraph, "typeinter", &str));
@ -910,7 +960,7 @@ float sm90SpeedArrayInter[] = { 48.0, 45.0, 42.0, 40.0, 30.0, 24.0, 22.0, 20.0,
#define NSPEEDSINTER_SM90 (sizeof(sm90SpeedArrayInter)/sizeof(float))
float sm100SpeedArrayIntra[] = { 90.0, 80.0, 70.0, 60.0, 50.0, 40.0, 30.0, 24.0, 20.0, 19.0, 18.0 };
float sm100SpeedArrayInter[] = { 47.9, 45.0, 42.0, 40.0, 30.0, 24.0, 22.0, 20.0, 17.5, 15.0, 12.0, 6.0, 3.0, 2.4, 1.2, 0.24, 0.12 };
float sm100SpeedArrayInter[] = { 96.0, 48.0, 45.1, 42.0, 40.0, 30.0, 24.0, 22.0, 20.0, 17.5, 15.0, 12.0, 6.0, 3.0, 2.4, 1.2, 0.24, 0.12 };
#define NSPEEDSINTRA_SM100 (sizeof(sm100SpeedArrayIntra)/sizeof(float))
#define NSPEEDSINTER_SM100 (sizeof(sm100SpeedArrayInter)/sizeof(float))
@ -1136,8 +1186,12 @@ ncclResult_t ncclTopoPrintGraph(struct ncclTopoSystem* system, struct ncclTopoGr
offset = strlen(line);
}
for (int i=0; i<ngpus; i++) {
sprintf(line+offset, " %s/%d", topoNodeTypeStr[GPU], graph->intra[ngpus*c+i]);
int g;
ncclTopoRankToIndex(system, graph->intra[ngpus * c + i], &g, true);
int64_t topoId = system->nodes[GPU].nodes[g].id;
sprintf(line + offset, " %s/%lx-%lx", topoNodeTypeStr[GPU], NCCL_TOPO_ID_SYSTEM_ID(topoId), NCCL_TOPO_ID_LOCAL_ID(topoId));
offset = strlen(line);
if (graph->id == 3) break; // NVLS graphs only use the first GPU
}
if (system->nodes[NET].count > 0) {
sprintf(line+offset, " %s/%lx-%lx", topoNodeTypeStr[NET], NCCL_TOPO_ID_SYSTEM_ID(graph->inter[2*c+1]), NCCL_TOPO_ID_LOCAL_ID(graph->inter[2*c+1]));
@ -1253,7 +1307,8 @@ ncclResult_t ncclTopoGetNetDev(struct ncclComm* comm, int rank, struct ncclTopoG
NCCLCHECK(ncclTopoGetLocalGpu(comm->topo, netId, &g2));
if (g2 != -1) {
struct ncclTopoNode* peerGpu = comm->topo->nodes[GPU].nodes+g2;
if (peerGpu->paths[GPU][g1].type <= PATH_NVL && peerGpu->paths[NET][n].type <= PATH_PXB) {
int pxnType = ncclParamPxnC2c() ? PATH_P2C : PATH_PXB;
if (peerGpu->paths[GPU][g1].type <= PATH_NVL && peerGpu->paths[NET][n].type <= pxnType) {
*proxyRank = peerGpu->gpu.rank;
if (dev) *dev = netDev;
if (id) *id = netId;

View File

@ -21,7 +21,7 @@
const char* topoNodeTypeStr[] = { "GPU", "PCI", "NVS", "CPU", "NIC", "NET" };
const char* topoLinkTypeStr[] = { "LOC", "NVL", "", "C2C", "PCI", "", "", "", "", "SYS", "NET" };
const char* topoPathTypeStr[] = { "LOC", "NVL", "NVB", "C2C", "PIX", "PXB", "PXN", "P2C", "PHB", "SYS", "NET", "DIS" };
const char* topoPathTypeStr[] = { "LOC", "NVL", "NVB", "C2C", "PIX", "PXB", "P2C", "PXN", "PHB", "SYS", "NET", "DIS" };
/******************************************************************/
/******************* Graph Creation Functions *********************/
@ -677,7 +677,14 @@ ncclResult_t ncclTopoGetSystemFromXml(struct ncclXml* xml, struct ncclTopoSystem
struct ncclXmlNode* node = topNode->subs[s];
if (strcmp(node->name, "cpu") == 0) NCCLCHECK(ncclTopoAddCpu(node, *topoSystem));
}
for (int systemId=0; systemId<system->nHosts; systemId++) if (system->hostHashes[systemId] == localHostHash) system->systemId = systemId;
int systemId = 0;
while (systemId < system->nHosts && system->hostHashes[systemId] != localHostHash) systemId++;
system->systemId = systemId;
if(systemId == system->nHosts){
WARN("localHostHash = 0x%lx not found in the list of system hostHashes",localHostHash);
return ncclInvalidArgument;
}
NCCLCHECK(ncclTopoAddNvLinks(topNode, *topoSystem, NULL, 0));
NCCLCHECK(ncclTopoAddC2c(topNode, *topoSystem, NULL, 0));
@ -1143,8 +1150,8 @@ struct kvDict nicPathKvList[] = {
{ "PORT", PATH_PORT },
{ "PIX", PATH_PIX },
{ "PXB", PATH_PXB },
{ "PXN", PATH_PXN },
{ "P2C", PATH_P2C },
{ "PXN", PATH_PXN },
{ "PHB", PATH_PHB },
{ "SYS", PATH_SYS },
{ NULL, 0 }
@ -1421,7 +1428,7 @@ ncclResult_t ncclTopoGetSystem(struct ncclComm* comm, struct ncclTopoSystem** sy
}
// Only update our topo tracking structure if we aren't dumping (separate steps)
if (dumpXmlFile == NULL) NCCLCHECKGOTO(ncclTopoGetSystemFromXml(xml, system, comm->peerInfo[comm->rank].hostHash), ret, fail);
if (dumpXmlFile == NULL) NCCLCHECKGOTO(ncclTopoGetSystemFromXml(xml, system, getHostHash()), ret, fail);
exit:
if (!comm->MNNVL && localRanks) free(localRanks);

View File

@ -18,7 +18,7 @@
#define SM80_NVLINK_BW 20.0
#define SM90_NVLINK_BW 20.6
#define SM86_NVLINK_BW 12.0
#define SM100_NVLINK_BW 40.0
#define SM100_NVLINK_BW 40.1
#define PCI_BW 12.0 // PCI Gen3 x16
#define AMD_BW 16.0
#define BDW_QPI_BW 6.0
@ -76,11 +76,11 @@ extern const char* topoLinkTypeStr[];
// Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
#define PATH_PXB 5
// Connection between a GPU and a NIC using an intermediate GPU. Used to enable rail-local, aggregated network send/recv operations.
#define PATH_PXN 6
// Connection between a GPU and a NIC using the C2C connection to the CPU and the PCIe connection to the NIC
#define PATH_P2C 7
#define PATH_P2C 6
// Connection between a GPU and a NIC using an intermediate GPU. Used to enable rail-local, aggregated network send/recv operations.
#define PATH_PXN 7
// Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
#define PATH_PHB 8
@ -98,6 +98,8 @@ extern const char* topoLinkTypeStr[];
#define PATH_DIS 11
extern const char* topoPathTypeStr[];
extern int64_t ncclParamPxnC2c();
struct ncclTopoNode;
struct ncclTopoLink {
int type;
@ -143,6 +145,7 @@ struct ncclTopoNode {
int gdrSupport;
int collSupport;
int maxChannels;
int localGpu;
}net;
struct {
int arch;

View File

@ -455,9 +455,16 @@ ncclResult_t ncclTopoTuneModel(struct ncclComm* comm, int minCompCap, int maxCom
for (int c=0; c<NCCL_NUM_FUNCTIONS; c++) for (int a=0; a<NCCL_NUM_ALGORITHMS; a++) for (int p=0; p<NCCL_NUM_PROTOCOLS; p++) {
int pEnable = protoEnable[c*NCCL_NUM_PROTOCOLS+p];
if (pEnable == 2 && p == NCCL_PROTO_LL128) {
// Enable LL128 by default only on Volta/Ampere/Hopper/Blackwell+NVLink. Other cases are not tested and may cause silent data corruption.
pEnable = 1;
pEnable &= (graphs[a]->typeInter <= PATH_PXB || (minCompCap >= 90 && graphs[a]->typeInter <= (ncclParamLl128C2c() ? PATH_P2C : PATH_PXN)));
if (ncclParamLl128C2c() && minCompCap >= 90) {
// Enable LL128 by default only on Hopper/Blackwell for all connections up to P2C and PXN.
pEnable &= (graphs[a]->typeInter <= PATH_PXN);
} else {
// Enable LL128 only up to PXB. Don't enable LL128 over PxN because PxN can encapsulate PxB or P2C links.
pEnable &= (graphs[a]->typeInter <= PATH_PXB);
if (!ncclParamLl128C2c() && minCompCap >= 90)
INFO(NCCL_GRAPH, "Disabling LL128 over all PxN connections (PXB and C2C). This ensures that no C2C link will be used by LL128.");
}
pEnable &= (graphs[a]->typeIntra <= PATH_NVB);
pEnable &= (minCompCap == maxCompCap);
pEnable &= !(minCompCap < 70 || (minCompCap == 90 && CUDART_VERSION == 11080 && c == ncclFuncAllReduce && a == NCCL_ALGO_RING && comm->nRanks == 2));

View File

@ -9,6 +9,7 @@
#include <stdint.h>
#include <sys/types.h>
#include <unistd.h>
#include <string.h>
#if __GNUC__ >= 3
# define __attribute_const __attribute__((const))
@ -39,7 +40,7 @@ union ibv_gid {
#define vext_field_avail(type, fld, sz) (offsetof(type, fld) < (sz))
/*XXX:__VERBS_ABI_IS_EXTENDED produces warning "integer operation result is out of range" with g++ 4.8.2*/
//static void *__VERBS_ABI_IS_EXTENDED = ((uint8_t *)NULL) - 1;
static void *__VERBS_ABI_IS_EXTENDED = ((uint8_t *)NULL) - 1;
enum ibv_node_type {
IBV_NODE_UNKNOWN = -1,
@ -208,7 +209,9 @@ struct ibv_port_attr {
uint8_t active_speed;
uint8_t phys_state;
uint8_t link_layer;
uint8_t reserved;
uint8_t flags;
uint16_t port_cap_flags2;
uint32_t active_speed_ex;
};
enum ibv_event_type {
@ -993,37 +996,50 @@ enum verbs_context_mask {
struct verbs_context {
/* "grows up" - new fields go here */
int (*_reserved_2) (void);
int (*destroy_flow) (struct ibv_flow *flow);
int (*_reserved_1) (void);
struct ibv_flow * (*create_flow) (struct ibv_qp *qp,
struct ibv_flow_attr *flow_attr);
int (*query_port)(struct ibv_context *context, uint8_t port_num,
struct ibv_port_attr *port_attr,
size_t port_attr_len);
int (*_reserved[25]) (void);
struct verbs_ex_private *priv;
int (*query_device_ex)(struct ibv_context *context,
const struct ibv_query_device_ex_input *input,
struct ibv_device_attr_ex *attr,
size_t attr_size);
int (*ibv_destroy_flow) (struct ibv_flow *flow);
void (*ABI_placeholder2) (void); /* DO NOT COPY THIS GARBAGE */
struct ibv_flow * (*ibv_create_flow) (struct ibv_qp *qp,
struct ibv_flow_attr *flow_attr);
void (*ABI_placeholder1) (void); /* DO NOT COPY THIS GARBAGE */
struct ibv_qp * (*open_qp)(struct ibv_context *context,
struct ibv_qp_open_attr *attr);
struct ibv_qp * (*create_qp_ex)(struct ibv_context *context,
struct ibv_qp_init_attr_ex *qp_init_attr_ex);
int (*get_srq_num)(struct ibv_srq *srq, uint32_t *srq_num);
struct ibv_srq * (*create_srq_ex)(struct ibv_context *context,
struct ibv_srq_init_attr_ex *srq_init_attr_ex);
struct ibv_xrcd * (*open_xrcd)(struct ibv_context *context,
struct ibv_xrcd_init_attr *xrcd_init_attr);
int (*close_xrcd)(struct ibv_xrcd *xrcd);
uint64_t has_comp_mask;
size_t sz; /* Must be immediately before struct ibv_context */
struct ibv_context context;/* Must be last field in the struct */
struct ibv_srq * (*create_srq_ex)(struct ibv_context *context,
struct ibv_srq_init_attr_ex *srq_init_attr_ex);
struct ibv_xrcd * (*open_xrcd)(struct ibv_context *context,
struct ibv_xrcd_init_attr *xrcd_init_attr);
int (*close_xrcd)(struct ibv_xrcd *xrcd);
uint64_t _ABI_placeholder3;
size_t sz; /* Must be immediately before struct ibv_context */
struct ibv_context context; /* Must be last field in the struct */
};
/*XXX:__VERBS_ABI_IS_EXTENDED produces warning "integer operation result is out of range" with g++ 4.8.2*/
/*static inline struct verbs_context *verbs_get_ctx(struct ibv_context *ctx)
static inline struct verbs_context *verbs_get_ctx(struct ibv_context *ctx)
{
return (!ctx || (ctx->abi_compat != __VERBS_ABI_IS_EXTENDED)) ?
NULL : container_of(ctx, struct verbs_context, context);
if (ctx->abi_compat != __VERBS_ABI_IS_EXTENDED)
return NULL;
/* open code container_of to not pollute the global namespace */
return (struct verbs_context *)(((uintptr_t)ctx) -
offsetof(struct verbs_context,
context));
}
#define verbs_get_ctx_op(ctx, op) ({ \
struct verbs_context *_vctx = verbs_get_ctx(ctx); \
(!_vctx || (_vctx->sz < sizeof(*_vctx) - offsetof(struct verbs_context, op)) || \
!_vctx->op) ? NULL : _vctx; })*/
struct verbs_context *__vctx = verbs_get_ctx(ctx); \
(!__vctx || (__vctx->sz < sizeof(*__vctx) - offsetof(struct verbs_context, op)) || \
!__vctx->op) ? NULL : __vctx; })
#define verbs_set_ctx_op(_vctx, op, ptr) ({ \
struct verbs_context *vctx = _vctx; \
@ -1055,4 +1071,20 @@ struct ibv_ece {
uint32_t comp_mask;
};
/**
* ibv_query_port_ex - Get (extended) port properties
*/
static inline int ibv_query_port_ex(struct ibv_context *context,
uint8_t port_num,
struct ibv_port_attr *port_attr)
{
struct verbs_context *vctx = verbs_get_ctx_op(context, query_port);
if (vctx) {
return vctx->query_port(context, port_num, port_attr, sizeof(*port_attr));
}
return -1;
}
#endif // NCCL_IBV_CORE_H_

View File

@ -9,10 +9,16 @@
#include "nccl.h"
enum ncclPluginType {
ncclPluginTypeNet,
ncclPluginTypeTuner,
ncclPluginTypeProfiler,
};
void* ncclOpenNetPluginLib(const char* name);
void* ncclOpenTunerPluginLib(const char* name);
void* ncclOpenProfilerPluginLib(const char* name);
void* ncclGetNetPluginLib(void);
ncclResult_t ncclClosePluginLib(void* handle);
void* ncclGetNetPluginLib(enum ncclPluginType type);
ncclResult_t ncclClosePluginLib(void* handle, enum ncclPluginType type);
#endif

View File

@ -1507,7 +1507,7 @@ static ncclResult_t envConfigOverride(ncclComm_t comm) {
int minCTAsEnv;
int maxCTAsEnv;
int splitShareEnv;
int collnetEnableEnv;
const char* collnetEnableEnv;
int ctaPolicyEnv;
int shrinkShareEnv;
int nvlsCTAsEnv;
@ -1561,9 +1561,15 @@ static ncclResult_t envConfigOverride(ncclComm_t comm) {
comm->config.shrinkShare = shrinkShareEnv;
}
collnetEnableEnv = ncclParamCollnetEnable();
if (collnetEnableEnv != NCCL_CONFIG_UNDEF_INT) {
comm->config.collnetEnable = collnetEnableEnv;
// NCCL_COLLNET_ENABLE needs to be reloaded each time for comm init
// since users might change the env on the fly to enable/disable collnet
collnetEnableEnv = ncclGetEnv("NCCL_COLLNET_ENABLE");
if (collnetEnableEnv != NULL) {
int collnetEnableInt = (int)strtol(collnetEnableEnv, NULL, 0);
if (collnetEnableInt != NCCL_CONFIG_UNDEF_INT) {
comm->config.collnetEnable = collnetEnableInt;
INFO(NCCL_ENV, "NCCL_COLLNET_ENABLE set by environment to %d.", collnetEnableInt);
}
}
ctaPolicyEnv = ncclParamCtaPolicy();
@ -2164,6 +2170,7 @@ ncclResult_t ncclCommDestroy(ncclComm_t comm) {
NVTX3_PAYLOAD(comm->commHash, nranks, rank, cudaDev));
TRACE(NCCL_INIT, "comm %p rank %d nRanks %d cudaDev %d busId %lx", comm, rank, nranks, cudaDev, comm->busId);
NCCLCHECK(ncclGroupStartInternal());
// Try and prevent a double free of the comm struct (user error)
if (comm->rank == -1 || comm->nRanks == -1 || comm->cudaDev == -1 || comm->busId == -1) {
WARN("comm %p has already been destroyed", comm);
@ -2178,6 +2185,8 @@ ncclResult_t ncclCommDestroy(ncclComm_t comm) {
NCCLCHECKGOTO(ncclAsyncLaunch((struct ncclAsyncJob*)job, commReclaim, NULL, free, comm), res, fail);
exit:
ncclGroupErrCheck(res);
NCCLCHECK(ncclGroupEndInternal());
return res;
fail:
goto exit;
@ -2201,6 +2210,7 @@ ncclResult_t ncclCommAbort(ncclComm_t comm) {
if (comm == NULL) {
return ncclSuccess;
}
NCCLCHECK(ncclGroupStartInternal());
// Ask anything that might still be running on the device to quit
NCCLCHECK(setCommAbortFlags(comm,1));
comm->destroyFlag = 1;
@ -2223,7 +2233,9 @@ ncclResult_t ncclCommAbort(ncclComm_t comm) {
NCCLCHECKGOTO(ncclAsyncLaunch((struct ncclAsyncJob*)job, commReclaim, NULL, free, comm), res, fail);
exit:
return ncclSuccess;
ncclGroupErrCheck(res);
NCCLCHECK(ncclGroupEndInternal());
return res;
fail:
goto exit;
}

View File

@ -142,8 +142,14 @@ ncclResult_t wrap_ibv_query_device(struct ibv_context *context, struct ibv_devic
IBV_INT_CHECK_RET_ERRNO(ibvSymbols, ibv_internal_query_device, ibv_internal_query_device(context, device_attr), 0, "ibv_query_device");
}
ncclResult_t wrap_ibv_query_port(struct ibv_context *context, uint8_t port_num, struct ibv_port_attr *port_attr) { /*returns 0 on success, or the value of errno on failure (which indicates the failure reason)*/
IBV_INT_CHECK_RET_ERRNO(ibvSymbols, ibv_internal_query_port, ibv_internal_query_port(context, port_num, port_attr), 0, "ibv_query_port");
ncclResult_t wrap_ibv_query_port(struct ibv_context *context, uint8_t port_num, struct ibv_port_attr *port_attr) {
// First try and query the extended port attributes (e.g. active_speed_ex)
if (ibv_query_port_ex(context, port_num, port_attr) != 0) {
// Fall back to the original attribute API call, but zero all members first
memset(port_attr, 0, sizeof(*port_attr));
IBV_INT_CHECK_RET_ERRNO(ibvSymbols, ibv_internal_query_port, ibv_internal_query_port(context, port_num, port_attr), 0, "ibv_query_port");
}
return ncclSuccess;
}
ncclResult_t wrap_ibv_query_gid(struct ibv_context *context, uint8_t port_num, int index, union ibv_gid *gid) {

View File

@ -52,6 +52,9 @@ ncclResult_t buildMlx5dvSymbols(struct ncclMlx5dvSymbols* mlx5dvSymbols) {
#define LOAD_SYM_VERSION(handle, symbol, funcptr, version) do { \
cast = (void**)&funcptr; \
*cast = dlvsym(handle, symbol, version); \
if (*cast == NULL) { \
INFO(NCCL_NET, "dlvsym failed on %s - %s version %s", symbol, dlerror(), version); \
} \
} while (0)
LOAD_SYM(mlx5dvhandle, "mlx5dv_is_supported", mlx5dvSymbols->mlx5dv_internal_is_supported);

View File

@ -441,7 +441,8 @@ static ncclResult_t socketTryAccept(struct ncclSocket* sock) {
if (sock->fd != -1) {
sock->state = ncclSocketStateAccepted;
} else if (errno == ENETDOWN || errno == EPROTO || errno == ENOPROTOOPT || errno == EHOSTDOWN ||
errno == ENONET || errno == EHOSTUNREACH || errno == EOPNOTSUPP || errno == ENETUNREACH) {
errno == ENONET || errno == EHOSTUNREACH || errno == EOPNOTSUPP || errno == ENETUNREACH ||
errno == EINTR) {
/* per accept's man page, for linux sockets, the following errors might be already pending errors
* and should be considered as EAGAIN. To avoid infinite loop in case of errors, we use the retry count*/
if (++sock->errorRetries == ncclParamRetryCnt()) {

View File

@ -21,7 +21,6 @@ struct ncclStrongStreamCapture {
cudaGraph_t graph;
unsigned long long graphId;
cudaStream_t captureStream;
cudaGraphNode_t lastRecord;
void* acquiredBy;
};
@ -216,7 +215,6 @@ ncclResult_t ncclStrongStreamAcquire(
CUDACHECKGOTO(cudaStreamCreateWithFlags(&cap->captureStream, cudaStreamNonBlocking), ret, do_unlock);
}
cap->graphId = graph.graphId;
cap->lastRecord = nullptr;
cap->acquiredBy = localThreadId();
// Push to capturing list.
cap->next = ss->captureHead;
@ -296,16 +294,6 @@ ncclResult_t ncclStrongStreamRelease(
cudaGraphNode_t recordNode;
CUDACHECK(cudaGraphAddEventRecordNode(&recordNode, graph.graph, nullptr, 0, ss->serialEvent));
// Make this record order after previous record on this stream.
if (cap->lastRecord != nullptr) {
#if CUDART_VERSION >= 13000
CUDACHECK(cudaGraphAddDependencies_v2(graph.graph, &cap->lastRecord, &recordNode, nullptr, 1));
#else
CUDACHECK(cudaGraphAddDependencies(graph.graph, &cap->lastRecord, &recordNode, 1));
#endif
}
cap->lastRecord = recordNode;
// Get current nodes from work stream so we can add them as dependencies.
cudaStreamCaptureStatus status;
cudaGraphNode_t const* nodes;
@ -338,6 +326,22 @@ ncclResult_t ncclStrongStreamRelease(
}
}
// Make every future operation captured on cap->captureStream depend on 'recordNode'.
#if CUDART_VERSION >= 13000
CUDACHECK(cudaStreamUpdateCaptureDependencies_v2(
cap->captureStream,
&recordNode, /* dependencies */
/*edges =*/ nullptr, /* no edge annotations */
1, /* count */
cudaStreamSetCaptureDependencies));
#else
CUDACHECK(cudaStreamUpdateCaptureDependencies(
cap->captureStream,
&recordNode,
1,
cudaStreamSetCaptureDependencies));
#endif
if (cap->acquiredBy != localThreadId() && ncclParamLaunchRaceFatal()) {
WARN("%s", launchRaceFatalMsg);
return ncclInvalidUsage;

View File

@ -16,12 +16,12 @@
#include <cuda_fp8.h>
#endif
#define NCCL_MAJOR ${nccl:Major}
#define NCCL_MINOR ${nccl:Minor}
#define NCCL_PATCH ${nccl:Patch}
#define NCCL_SUFFIX "${nccl:Suffix}"
#define NCCL_MAJOR ${nccl_Major}
#define NCCL_MINOR ${nccl_Minor}
#define NCCL_PATCH ${nccl_Patch}
#define NCCL_SUFFIX "${nccl_Suffix}"
#define NCCL_VERSION_CODE ${nccl:Version}
#define NCCL_VERSION_CODE ${nccl_Version}
#define NCCL_VERSION(X,Y,Z) (((X) <= 2 && (Y) <= 8) ? (X) * 1000 + (Y) * 100 + (Z) : (X) * 10000 + (Y) * 100 + (Z))
#ifdef __cplusplus

View File

@ -67,7 +67,7 @@ static pthread_once_t initPluginLibsOnceControl = PTHREAD_ONCE_INIT;
static ncclResult_t ncclNetPluginUnload(netPluginLib_t* pluginLib) {
if ((pluginLib->dlHandle) && ((pluginLib->ncclNetPluginRefCount) == 0)) {
INFO(NCCL_INIT|NCCL_NET, "Unloading plugin %s", pluginLib->name);
NCCLCHECK(ncclClosePluginLib(pluginLib->dlHandle));
NCCLCHECK(ncclClosePluginLib(pluginLib->dlHandle, ncclPluginTypeNet));
memset(pluginLib, 0, sizeof(netPluginLib_t));
}
return ncclSuccess;
@ -105,8 +105,9 @@ exit:
return ncclSuccess;
fail:
if (pluginLib->dlHandle) {
NCCLCHECK(ncclClosePluginLib(pluginLib->dlHandle));
NCCLCHECK(ncclClosePluginLib(pluginLib->dlHandle, ncclPluginTypeNet));
}
pluginLib->dlHandle = nullptr;
pluginLib->ncclNetPluginState = ncclNetPluginStateLoadFailed;
pluginLib->ncclCollNetPluginState = ncclNetPluginStateLoadFailed;
goto exit;

View File

@ -10,16 +10,12 @@
#include <dlfcn.h>
#include "debug.h"
#include "plugin.h"
#define MAX_STR_LEN 255
enum ncclPluginType {
ncclPluginTypeNet,
ncclPluginTypeTuner,
ncclPluginTypeProfiler,
};
#define NUM_LIBS 3
static char* libNames[NUM_LIBS];
static void *libHandles[NUM_LIBS];
static const char *pluginNames[NUM_LIBS] = { "NET", "TUNER", "PROFILER" };
static const char *pluginPrefix[NUM_LIBS] = { "libnccl-net", "libnccl-tuner", "libnccl-profiler" };
@ -61,24 +57,26 @@ static void* openPluginLib(enum ncclPluginType type, const char* libName) {
char eNoEntNameList[PATH_MAX] = { 0 };
if (libName && strlen(libName)) {
// match names that start with 'lib' and end with '.so'
if (strlen(libName) >= strlen("libX.so") && strncmp(libName, "lib", strlen("lib")) == 0 && strncmp(libName + strlen(libName) - strlen(".so"), ".so", strlen(".so")) == 0) {
snprintf(libName_, MAX_STR_LEN, "%s", libName);
libHandles[type] = tryOpenLib(libName_, &openErr, openErrStr);
if (libHandles[type]) {
INFO(subsys[type], "%s/Plugin: Plugin name set by env to %s", pluginNames[type], libName_);
return libHandles[type];
}
if (openErr == ENOENT) {
appendNameToList(eNoEntNameList, &len, libName_);
} else {
INFO(subsys[type], "%s/Plugin: %s", pluginNames[type], openErrStr);
}
snprintf(libName_, MAX_STR_LEN, "%s", libName);
libHandles[type] = tryOpenLib(libName_, &openErr, openErrStr);
if (libHandles[type]) {
INFO(subsys[type], "%s/Plugin: Plugin name set by env to %s", pluginNames[type], libName_);
libNames[type] = strdup(libName_);
return libHandles[type];
}
if (openErr == ENOENT) {
appendNameToList(eNoEntNameList, &len, libName_);
} else {
INFO(subsys[type], "%s/Plugin: %s", pluginNames[type], openErrStr);
}
// libName can't be a relative or absolute path (start with '.' or contain any '/'). It can't be a library name either (start with 'lib' or end with '.so')
if (strchr(libName, '/') == nullptr && (strncmp(libName, "lib", strlen("lib")) || strlen(libName) < strlen(".so") || strncmp(libName + strlen(libName) - strlen(".so"), ".so", strlen(".so")))) {
snprintf(libName_, MAX_STR_LEN, "%s-%s.so", pluginPrefix[type], libName);
libHandles[type] = tryOpenLib(libName_, &openErr, openErrStr);
if (libHandles[type]) {
INFO(subsys[type], "%s/Plugin: Plugin name set by env to %s", pluginNames[type], libName_);
libNames[type] = strdup(libName_);
return libHandles[type];
}
if (openErr == ENOENT) {
@ -91,6 +89,7 @@ static void* openPluginLib(enum ncclPluginType type, const char* libName) {
snprintf(libName_, MAX_STR_LEN, "%s.so", pluginPrefix[type]);
libHandles[type] = tryOpenLib(libName_, &openErr, openErrStr);
if (libHandles[type]) {
libNames[type] = strdup(libName_);
return libHandles[type];
}
if (openErr == ENOENT) {
@ -120,22 +119,21 @@ void* ncclOpenProfilerPluginLib(const char* name) {
return openPluginLib(ncclPluginTypeProfiler, name);
}
void* ncclGetNetPluginLib(void) {
return libHandles[ncclPluginTypeNet];
void* ncclGetNetPluginLib(enum ncclPluginType type) {
if (libNames[ncclPluginTypeNet]) {
// increment the reference counter of the net library
libNames[type] = strdup(libNames[ncclPluginTypeNet]);
libHandles[type] = dlopen(libNames[ncclPluginTypeNet], RTLD_NOW | RTLD_LOCAL);
}
return libHandles[type];
}
ncclResult_t ncclClosePluginLib(void* handle) {
bool found = false;
for (int l=0; l<NUM_LIBS; l++) {
if (libHandles[l] == handle) {
libHandles[l] = nullptr;
if (!found) {
if (handle) {
dlclose(handle);
}
found = true;
}
}
ncclResult_t ncclClosePluginLib(void* handle, enum ncclPluginType type) {
if (handle && libHandles[type] == handle) {
dlclose(handle);
libHandles[type] = nullptr;
free(libNames[type]);
libNames[type] = nullptr;
}
return ncclSuccess;
}

View File

@ -77,7 +77,8 @@ exit:
pthread_mutex_unlock(&profilerLock);
return ncclSuccess;
fail:
if (profilerPluginLib) NCCLCHECK(ncclClosePluginLib(profilerPluginLib));
if (profilerPluginLib) NCCLCHECK(ncclClosePluginLib(profilerPluginLib, ncclPluginTypeProfiler));
profilerPluginLib = nullptr;
profilerPluginStatus = profilerPluginLoadFailed;
goto exit;
}
@ -86,7 +87,7 @@ static ncclResult_t ncclProfilerPluginUnload(void) {
pthread_mutex_lock(&profilerLock);
if (0 == (--profilerPluginRefCount)) {
INFO(NCCL_ENV, "PROFILER/Plugin: Closing profiler plugin %s", ncclProfiler->name);
NCCLCHECK(ncclClosePluginLib(profilerPluginLib));
NCCLCHECK(ncclClosePluginLib(profilerPluginLib, ncclPluginTypeProfiler));
profilerPluginLib = nullptr;
ncclProfiler = nullptr;
profilerPluginStatus = profilerPluginLoadReady;

View File

@ -52,7 +52,7 @@ ncclResult_t ncclTunerPluginLoad(struct ncclComm* comm) {
tunerPluginLib = ncclOpenTunerPluginLib(ncclGetEnv("NCCL_TUNER_PLUGIN"));
if (nullptr == tunerPluginLib) {
tunerPluginLib = ncclGetNetPluginLib();
tunerPluginLib = ncclGetNetPluginLib(ncclPluginTypeTuner);
if (nullptr == tunerPluginLib) {
goto fail;
}
@ -78,6 +78,7 @@ exit:
pthread_mutex_unlock(&tunerPluginLock);
return ncclSuccess;
fail:
if (tunerPluginLib) NCCLCHECK(ncclClosePluginLib(tunerPluginLib, ncclPluginTypeTuner));
tunerPluginLib = nullptr;
status = tunerPluginLoadFailed;
goto exit;
@ -87,7 +88,7 @@ ncclResult_t ncclTunerPluginUnload(struct ncclComm* comm) {
pthread_mutex_lock(&tunerPluginLock);
if (comm->tunerPluginLoaded && 0 == (--tunerPluginRefCount)) {
INFO(NCCL_TUNING, "TUNER/Plugin: Closing tuner: '%s'", tunerSymbol->name);
NCCLCHECK(ncclClosePluginLib(tunerPluginLib));
NCCLCHECK(ncclClosePluginLib(tunerPluginLib, ncclPluginTypeTuner));
tunerPluginLib = nullptr;
tunerSymbol = nullptr;
comm->tuner = nullptr;

View File

@ -494,7 +494,9 @@ static int ibvSpeeds[] = {
14000, /* FDR */
25000, /* EDR */
50000, /* HDR */
100000 /* NDR */ };
100000, /* NDR */
200000 /* XDR */
};
static int firstBitSet(int val, int max) {
int i = 0;
@ -650,12 +652,15 @@ ncclResult_t ncclIbInit(ncclDebugLogger_t logFunction, ncclProfilerCallback_t pr
enum ncclIbProvider ibProvider = IB_PROVIDER_NONE;
char dataDirectDevicePath[PATH_MAX];
int dataDirectSupported = 0;
int skipNetDevForDataDirect = 0;
if (wrap_mlx5dv_is_supported(devices[d])) {
ibProvider = IB_PROVIDER_MLX5;
snprintf(dataDirectDevicePath, PATH_MAX, "/sys");
if((ncclMlx5dvDmaBufCapable(context)) && (wrap_mlx5dv_get_data_direct_sysfs_path(context, dataDirectDevicePath + 4, PATH_MAX - 4) == ncclSuccess)) {
INFO(NCCL_NET, "Data Direct DMA Interface is detected for device:%s", devices[d]->name);
if(ncclParamIbDataDirect()) dataDirectSupported = 1;
INFO(NCCL_INIT|NCCL_NET, "NET/IB: Data Direct DMA Interface is detected for device:%s", devices[d]->name);
// Now check whether Data Direct has been disabled by the user
if(ncclParamIbDataDirect() == 1) { dataDirectSupported = 1; skipNetDevForDataDirect = 1; }
if(ncclParamIbDataDirect() == 2) { dataDirectSupported = 1; skipNetDevForDataDirect = 0; }
}
}
int nPorts = 0;
@ -667,7 +672,8 @@ ncclResult_t ncclIbInit(ncclDebugLogger_t logFunction, ncclProfilerCallback_t pr
continue;
}
for (int port_num = 1; port_num <= devAttr.phys_port_cnt; port_num++) {
for (int dataDirect = 0; dataDirect < 1 + dataDirectSupported; ++dataDirect) {
// dataDirect = 0 exposes the devices normally, dataDirect = 1 exposes the devices through direct NIC
for (int dataDirect = skipNetDevForDataDirect; dataDirect < 1 + dataDirectSupported; ++dataDirect) {
struct ibv_port_attr portAttr;
if (ncclSuccess != wrap_ibv_query_port(context, port_num, &portAttr)) {
WARN("NET/IB : Unable to query port_num %d", port_num);
@ -688,15 +694,18 @@ ncclResult_t ncclIbInit(ncclDebugLogger_t logFunction, ncclProfilerCallback_t pr
ncclIbDevs[ncclNIbDevs].portAttr = portAttr;
ncclIbDevs[ncclNIbDevs].portNum = port_num;
ncclIbDevs[ncclNIbDevs].link = portAttr.link_layer;
ncclIbDevs[ncclNIbDevs].speed = ncclIbSpeed(portAttr.active_speed) * ncclIbWidth(portAttr.active_width);
if (portAttr.active_speed_ex)
// A non-zero active_speed_ex indicates XDR rate (0x100) or higher
ncclIbDevs[ncclNIbDevs].speed = ncclIbSpeed(portAttr.active_speed_ex) * ncclIbWidth(portAttr.active_width);
else
ncclIbDevs[ncclNIbDevs].speed = ncclIbSpeed(portAttr.active_speed) * ncclIbWidth(portAttr.active_width);
ncclIbDevs[ncclNIbDevs].context = context;
ncclIbDevs[ncclNIbDevs].pdRefs = 0;
ncclIbDevs[ncclNIbDevs].pd = NULL;
if (!dataDirect) {
strncpy(ncclIbDevs[ncclNIbDevs].devName, devices[d]->name, MAXNAMESIZE);
NCCLCHECKGOTO(ncclIbGetPciPath(ncclIbDevs[ncclNIbDevs].devName, &ncclIbDevs[ncclNIbDevs].pciPath, &ncclIbDevs[ncclNIbDevs].realPort), ret, fail);
}
else {
} else {
snprintf(ncclIbDevs[ncclNIbDevs].devName, MAXNAMESIZE, "%s_dma", devices[d]->name);
NCCLCHECK(ncclCalloc(&ncclIbDevs[ncclNIbDevs].pciPath, PATH_MAX));
strncpy(ncclIbDevs[ncclNIbDevs].pciPath, dataDirectDevicePath, PATH_MAX);