If an error code can not be recognized by cuGetErrorString, errStr remains null and causes crashing at DP() printing.
Protect this case.
Reviewed By: jhuber6, tianshilei1992
Differential Revision: https://reviews.llvm.org/D87980
Summary:
This patch starts adding support for adding information dumps to libomptarget
and rtl plugins. The information printing is controlled by the
LIBOMPTARGET_INFO environment variable introduced in D86483. The goal of this
patch is to provide the user with additional information about the device
during kernel execution and providing the user with information dumps in the
case of failure. This patch added the ability to dump the pointer mapping table
as well as printing the number of blocks and threads in the cuda RTL.
Reviewers: jdoerfort gkistanova ye-luo
Subscribers: guansong openmp-commits sstefan1 yaxunl ye-luo
Tags: #OpenMP
Differential Revision: https://reviews.llvm.org/D87165
Summary:
This patch consolidates the error handling and messaging routines to a single
file omptargetmessage. The goal is to simplify the error handling interface
prior to adding more error handling support
Reviewers: jdoerfert grokos ABataev AndreyChurbanov ronlieb JonChesterfield ye-luo tianshilei1992
Subscribers: danielkiss guansong jvesely kerbowa nhaehnle openmp-commits sstefan1 yaxunl
Instead of calling `cuFuncGetAttribute` with
`CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK` for every kernel invocation,
we can do it for the first one and cache the result as part of the
`KernelInfo` struct. The only functional change is that we now expect
`cuFuncGetAttribute` to succeed and otherwise propagate the error.
Ignoring any error seems like a slippery slope...
Reviewed By: JonChesterfield
Differential Revision: https://reviews.llvm.org/D86038
The standard way of printing `int64_t` data is via the PRId64 macro, `ld`
is for `long int` and int64_t is not guaranteed to be typedef'ed as `long int`
on all platforms. E.g. on Windows we get mismatch warnings.
Differential Revision: https://reviews.llvm.org/D85353
Summary:
Retaining per device primary context is preferred to creating a context owned by the plugin.
From CUDA documentation
1. Note that the use of multiple CUcontext s per device within a single process will substantially degrade performance and is strongly discouraged. Instead, it is highly recommended that the implicit one-to-one device-to-context mapping for the process provided by the CUDA Runtime API be used." from https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__DRIVER.html
2. Right under cuCtxCreate. In most cases it is recommended to use cuDevicePrimaryCtxRetain. https://docs.nvidia.com/cuda/cuda-driver-api/group__CUDA__CTX.html#group__CUDA__CTX_1g65dc0012348bc84810e2103a40d8e2cf
3. The primary context is unique per device and shared with the CUDA runtime API. These functions allow integration with other libraries using CUDA. https://docs.nvidia.com/cuda/cuda-driver-api/group__CUDA__PRIMARY__CTX.html#group__CUDA__PRIMARY__CTX
Two issues are addressed by this patch:
1. Not using the primary context caused interoperability issue with libraries like cublas, cusolver. CUBLAS_STATUS_EXECUTION_FAILED and cudaErrorInvalidResourceHandle
2. On OLCF summit, "Error returned from cuCtxCreate" and "CUDA error is: invalid device ordinal"
Regarding the flags of the primary context. If it is inactive, we set CU_CTX_SCHED_BLOCKING_SYNC. If it is already active, we respect the current flags.
Reviewers: grokos, ABataev, jdoerfert, protze.joachim, AndreyChurbanov, Hahnfeld
Reviewed By: jdoerfert
Subscribers: openmp-commits, yaxunl, guansong, sstefan1, tianshilei1992
Tags: #openmp
Differential Revision: https://reviews.llvm.org/D82718
Summary: Warnings are printed by clang when building LIBOMPTARGET_ENABLE_DEBUG=ON due incorrect format string.
Reviewers: tianshilei1992, jdoerfert
Reviewed By: tianshilei1992
Subscribers: yaxunl, guansong, sstefan1, openmp-commits
Tags: #openmp
Differential Revision: https://reviews.llvm.org/D82789
Summary:
In current implementation, D2D memcpy is first to copy data back to host and then
copy from host to device. This is very efficient if the device supports D2D
memcpy, like CUDA.
In this patch, D2D memcpy will first try to use native supported driver API. If
it fails, fall back to original way. It is worth noting that D2D memcpy in this
scenerio contains two ideas:
- Same devices: this is the D2D memcpy in the CUDA context.
- Different devices: this is the PeerToPeer memcpy in the CUDA context.
My implementation merges this two parts. It chooses the best API according to
the source device and destination device.
Reviewers: jdoerfert, AndreyChurbanov, grokos
Reviewed By: jdoerfert
Subscribers: yaxunl, guansong, sstefan1, openmp-commits
Tags: #openmp
Differential Revision: https://reviews.llvm.org/D80649
Summary: There is a typo in DeviceRTLTy::getNumOfDevices that the type of its return value is bool. It will lead to a problem of wrong device number returned from omp_get_num_devices.
Reviewers: jdoerfert
Reviewed By: jdoerfert
Subscribers: yaxunl, guansong, openmp-commits
Tags: #openmp
Differential Revision: https://reviews.llvm.org/D79255
Summary: Current implementation mixed everything up so that there is almost no encapsulation. In this patch, all CUDA related operations are put into a new class DeviceRTLTy and only necessary functions are exposed. In addition, all C++ code now conforms with LLVM code standard, keeping those API functions following C style.
Reviewers: jdoerfert
Reviewed By: jdoerfert
Subscribers: jfb, yaxunl, guansong, openmp-commits
Tags: #openmp
Differential Revision: https://reviews.llvm.org/D77951
...onization
Summary: In previous patch, in order to optimize performance, we only synchronize once
for each target region. The syncrhonization is via stream synchronization.
However, in the extreme situation, the performce might be bad. Consider the
following case: There is a task that requires transferring huge amount of data
(call many times of data transferring function). It is scheduled to the first
stream. And then we have 255 very light tasks scheduled to the remaining 255
streams (by default we have 256 streams). They can be finished before we do
synchronization at the end of the first task. Next, we get another very huge
task. It will be scheduled again to the first stream. Now the first task
finishes its kernel launch and call stream synchronization. Right now, the
stream already contains two kernels, and the synchronization will wait until the
two kernels finish instead of just the first one for the first task.
In this patch, we introduce stream pool. After each synchronization, the stream
will be returned back to the pool to make sure that for each synchronization,
only expected operations are waited.
Reviewers: jdoerfert
Reviewed By: jdoerfert
Subscribers: gregrodgers, yaxunl, lildmh, guansong, openmp-commits
Tags: #openmp
Differential Revision: https://reviews.llvm.org/D77412
Summary: According to comments on bi-weekly meeting, this patch put back old APIs and added new `_async` series
Reviewers: jdoerfert
Reviewed By: jdoerfert
Subscribers: yaxunl, guansong, openmp-commits
Tags: #openmp
Differential Revision: https://reviews.llvm.org/D77822
Summary:
This patch introduces two things for offloading:
1. Asynchronous data transferring: those functions are suffix with `_async`. They have one more argument compared with their synchronous counterparts: `__tgt_async_info*`, which is a new struct that only has one field, `void *Identifier`. This struct is for information exchange between different asynchronous operations. It can be used for stream selection, like in this case, or operation synchronization, which is also used. We may expect more usages in the future.
2. Optimization of stream selection for data mapping. Previous implementation was using asynchronous device memory transfer but synchronizing after each memory transfer. Actually, if we say kernel A needs four memory copy to device and two memory copy back to host, then we can schedule these seven operations (four H2D, two D2H, and one kernel launch) into a same stream and just need synchronization after memory copy from device to host. In this way, we can save a huge overhead compared with synchronization after each operation.
Reviewers: jdoerfert, ye-luo
Reviewed By: jdoerfert
Subscribers: yaxunl, lildmh, guansong, openmp-commits
Tags: #openmp
Differential Revision: https://reviews.llvm.org/D77005
Ensures that CUDA fail reasons (such as "No CUDA-capable device detected")
are printed together with libomptarget's debug message
(e.g. "Error when setting CUDA context"). Previously, the former was
printed only in CMAKE_BUILD_TYPE=Debug builds while the latter was
enabled by LIBOMPTARGET_ENABLE_DEBUG.
With this change, also only call cuGetErrorString when the error will be
printed.
Suggested-by: Ye Luo <xw111luoye@gmail.com>
Differential Revision: https://reviews.llvm.org/D65687
llvm-svn: 367910
Summary:
This patch adds support for handling variables under the:
```
#pragma omp declare target to()
```
clause when the
```
#pragma omp requires unified_shared_memory
```
is used.
The address of the host variable is copied into the device pointer just like for the declare target link case.
Reviewers: ABataev, caomhin, grokos, AlexEichenberger
Reviewed By: grokos
Subscribers: jcownie, guansong, jdoerfert, openmp-commits
Tags: #openmp
Differential Revision: https://reviews.llvm.org/D63106
llvm-svn: 363825
Summary: This patch enables the usage of a host variable on the device for declare target link variables when unified memory is available.
Reviewers: ABataev, caomhin, grokos
Reviewed By: grokos
Subscribers: Hahnfeld, guansong, jdoerfert, openmp-commits
Tags: #openmp
Differential Revision: https://reviews.llvm.org/D60884
llvm-svn: 362505
to reflect the new license. These used slightly different spellings that
defeated my regular expressions.
We understand that people may be surprised that we're moving the header
entirely to discuss the new license. We checked this carefully with the
Foundation's lawyer and we believe this is the correct approach.
Essentially, all code in the project is now made available by the LLVM
project under our new license, so you will see that the license headers
include that license only. Some of our contributors have contributed
code under our old license, and accordingly, we have retained a copy of
our old license notice in the top-level files in each project and
repository.
llvm-svn: 351648
cuDeviceGetProperties has apparently been deprecated since CUDA 5.0.
Nvidia started using annotations only in CUDA 9.2, so nobody noticed
nor cared before.
The new function returns the same values, tested with a P100.
Differential Revision: https://reviews.llvm.org/D51624
llvm-svn: 341372
Summary:
Currently Cuda plugin supports loading of the single image, though we
may have the executable with the several images, if it has target
regions inside of the dynamically loaded library. Patch allows to load
multiple images.
Reviewers: grokos
Subscribers: guansong, openmp-commits, kkwli0
Differential Revision: https://reviews.llvm.org/D49036
llvm-svn: 336569
Introduce OPENMP_INSTALL_LIBDIR and use in all install() commands.
This also fixes installation of libomptarget-nvptx that previously
didn't honor {OPENMP,LLVM}_LIBDIR_SUFFIX.
Differential Revision: https://reviews.llvm.org/D47130
llvm-svn: 333284
Summary:
Enable the device side debug messages at compile time, use env var to control at runtime.
To achieve this, an environment data block is passed to the device lib when it is loaded.
By default, the message is off, to enable it, a user need to set LIBOMPDEVICE_DEBUG=1.
Reviewers: grokos
Reviewed By: grokos
Subscribers: openmp-commits
Tags: #openmp
Differential Revision: https://reviews.llvm.org/D46210
llvm-svn: 331550
That's what we really need to link the CUDA plugin against,
not the CUDA runtime API in CUDA_LIBRARIES! While the latter
comes with the CUDA SDK, the Driver API is installed with
the kernel driver and there is at most one per system. As
fallback we can use the stubs library distributed with the
CUDA SDK for linking.
Differential Revision: https://reviews.llvm.org/D42643
llvm-svn: 323787
Use equivalents for the last calls to the Runtime API. Remove
stray assert in case of an error found during review, we should
only return OFFLOAD_FAIL.
Differential Revision: https://reviews.llvm.org/D42686
llvm-svn: 323786
These are needed by both libraries, so we can do that in a
common namespace and unify configuration parameters.
Also make sure that the user isn't requesting libomptarget
if the library cannot be built on the system. Issue an error
in that case.
Differential Revision: https://reviews.llvm.org/D40081
llvm-svn: 319342
Disable default debugging dumps for libomptarget and plugins and move dumps
under control of environment variable LIBOMPTARGET_DEBUG=<integer>. Dumps
are enabled when LIBOMPTARGET_DEBUG is set to a positive integer value.
Debugging dumps are available only in debug build; release build does not
support it.
Differential Revision: https://reviews.llvm.org/D33227
llvm-svn: 310841
This patch chagnes the plugin interface so that:
1) future plugins can take advantage of systems with shared CPU/device storage
2) instead of using base addresses, target regions are launched by providing target addresseds and base offsets explicitly.
Differential revision: https://reviews.llvm.org/D33028
llvm-svn: 302663
This is the patch upstreaming the plugins part of libomptarget (CUDA, generic-elf-64).
Differential Revision: https://reviews.llvm.org/D14253
llvm-svn: 293724
Ye Luo