Adding the compiler support of MD5 CS profile based on pervious context split work D107299. A MD5 CS profile is about 40% smaller than the string-based extbinary profile. As a result, the compilation is 15% faster.
There are a few conversion from real names to md5 names that have been made on the sample loader and context tracker side to get it work.
Reviewed By: wenlei, wmi
Differential Revision: https://reviews.llvm.org/D108342
This change aims at supporting LBR only sample perf script which is used for regular(Non-CS) profile generation. A LBR perf script includes a batch of LBR sample which starts with a frame pointer and a group of 32 LBR entries is followed. The FROM/TO LBR pair and the range between two consecutive entries (the former entry's TO and the latter entry's FROM) will be used to infer function profile info.
An example of LBR perf script(created by `perf script -F ip,brstack -i perf.data`)
```
40062f 0x40062f/0x4005b0/P/-/-/9 0x400645/0x4005ff/P/-/-/1 0x400637/0x400645/P/-/-/1 ...
4005d7 0x4005d7/0x4005e5/P/-/-/8 0x40062f/0x4005b0/P/-/-/6 0x400645/0x4005ff/P/-/-/1 ...
...
```
For implementation:
- Extended a new child class `LBRPerfReader` for the sample parsing, reused all the functionalities in `extractLBRStack` except for an extension to parsing leading instruction pointer.
- `HybridSample` is reused(just leave the call stack empty) and the parsed samples is still aggregated in `AggregatedSamples`. After that, range samples, branch sample, address samples are computed and recorded.
- Reused `ContextSampleCounterMap` to store the raw profile, since it's no need to aggregation by context, here it just registered one sample counter with a fake context key.
- Unified to use `show-raw-profile` instead of `show-unwinder-output` to dump the intermediate raw profile, see the comments of the format of the raw profile. For CS profile, it remains to output the unwinder output.
Profile generation part will come soon.
Differential Revision: https://reviews.llvm.org/D108153
Currently context strings contain a lot of duplicated function names and that significantly increase the profile size. This change split the context into a series of {name, offset, discriminator} tuples so function names used in the context can be replaced by the index into the name table and that significantly reduce the size consumed by context.
A follow-up improvement made in the compiler and profiling tools is to avoid reconstructing full context strings which is time- and memory- consuming. Instead a context vector of `StringRef` is adopted to represent the full context in all scenarios. As a result, the previous prevalent profile map which was implemented as a `StringRef` is now engineered as an unordered map keyed by `SampleContext`. `SampleContext` is reshaped to using an `ArrayRef` to represent a full context for CS profile. For non-CS profile, it falls back to use `StringRef` to represent a contextless function name. Both the `ArrayRef` and `StringRef` objects are underpinned by real array and string objects that are stored in producer buffers. For compiler, they are maintained by the sample reader. For llvm-profgen, they are maintained in `ProfiledBinary` and `ProfileGenerator`. Full context strings can be generated only in those cases of debugging and printing.
When it comes to profile format, nothing has changed to the text format, though internally CS context is implemented as a vector. Extbinary format is only changed for CS profile, with an additional `SecCSNameTable` section which stores all full contexts logically in the form of `vector<int>`, which each element as an offset points to `SecNameTable`. All occurrences of contexts elsewhere are redirected to using the offset of `SecCSNameTable`.
Testing
This is no-diff change in terms of code quality and profile content (for text profile).
For our internal large service (aka ads), the profile generation is cut to half, with a 20x smaller string-based extbinary format generated.
The compile time of ads is dropped by 25%.
Differential Revision: https://reviews.llvm.org/D107299
This change tried to integrate a new count based aggregated type of perf script. The only difference of the format is that an aggregated count is added at the head of the original sample which means the same samples are repeated to the given count times. This is used to reduce the perf script size.
e.g.
```
2
4005dc
400634
400684
7f68c5788793
0x4005c8/0x4005dc/P/-/-/0 ....
```
Implemented by a dedicated PerfReader `AggregatedHybridPerfReader`.
Differential Revision: https://reviews.llvm.org/D107192
Make extended binary the default output format for CSSPGO. This avoids having to pass flag every time when generating profile. It also matches llvm-profdata where binary profile is the default (should we switch to extbinary as default for llvm-profdata?).
We plan to compress name table for context profile, which depends on the built-in compression of extbinary.
Differential Revision: https://reviews.llvm.org/D103650
llvm-profgen uses profile summary based cold threshold to merge and trim cold context profile. This is to strike a good balance between profile size and performance.
We've been using 99.9% as the cutoff to save profile size without affecting performance. This change switch to use 99.9% instead of 99.9999% as default cold threshold cutoff for llvm-profgen.
Redundant switch csprof-cold-thres is also removed and tests cleaned up.
Differential Revision: https://reviews.llvm.org/D103071
It appears some instructions doesn't have the debug location info and the symbolizer will return an empty call stack for them which will cause some crash later in profile unwinding. Actually we do not record the sample info for them, so this change just filter out those instruction.
As those instruction would appears at the begin and end of the instruction list, without them we need to add the boundary check for IP `advance` and `backward`.
Also for pseudo probe based profile, we actually don't need the symbolized location info, so here just change to use an empty stack for it. This could save half of the binary loading time.
Differential Revision: https://reviews.llvm.org/D96434
To align with https://reviews.llvm.org/D95547, we need to add brackets for context id before initializing the `SampleContext`.
Also added test cases for extended binary format from llvm-profgen side.
Differential Revision: https://reviews.llvm.org/D95929
This change allows merging and trimming cold context profile in llvm-profgen to solve profile size bloat problem. Currently when the profile's total sample is below threshold(supported by a switch), it will be considered cold and merged into a base context-less profile, which will at least keep the profile quality as good as the baseline(non-cs).
For example, two input profiles:
[main @ foo @ bar]:60
[main @ bar]:50
Under threshold = 100, the two profiles will be merge into one with the base context, get result:
[bar]:110
Added two switches:
`--csprof-cold-thres=<value>`: Specified the total samples threshold for a context profile to be considered cold, with 100 being the default. Any cold context profiles will be merged into context-less base profile by default.
`--csprof-keep-cold`: Force profile generation to keep cold context profiles instead of dropping them. By default, any cold context will not be written to output profile.
Results:
Though not yet evaluating it with the latest CSSPGO, our internal branch shows neutral on performance but significantly reduce the profile size. Detailed evaluation on llvm-profgen with CSSPGO will come later.
Differential Revision: https://reviews.llvm.org/D94111
This stack of changes introduces `llvm-profgen` utility which generates a profile data file from given perf script data files for sample-based PGO. It’s part of(not only) the CSSPGO work. Specifically to support context-sensitive with/without pseudo probe profile, it implements a series of functionalities including perf trace parsing, instruction symbolization, LBR stack/call frame stack unwinding, pseudo probe decoding, etc. Also high throughput is achieved by multiple levels of sample aggregation and compatible format with one stop is generated at the end. Please refer to: https://groups.google.com/g/llvm-dev/c/1p1rdYbL93s for the CSSPGO RFC.
This change supports context-sensitive profile data generation into llvm-profgen. With simultaneous sampling for LBR and call stack, we can identify leaf of LBR sample with calling context from stack sample . During the process of deriving fall through path from LBR entries, we unwind LBR by replaying all the calls and returns (including implicit calls/returns due to inlining) backwards on top of the sampled call stack. Then the state of call stack as we unwind through LBR always represents the calling context of current fall through path.
we have two types of virtual unwinding 1) LBR unwinding and 2) linear range unwinding.
Specifically, for each LBR entry which can be classified into call, return, regular branch, LBR unwinding will replay the operation by pushing, popping or switching leaf frame towards the call stack and since the initial call stack is most recently sampled, the replay should be in anti-execution order, i.e. for the regular case, pop the call stack when LBR is call, push frame on call stack when LBR is return. After each LBR processed, it also needs to align with the next LBR by going through instructions from previous LBR's target to current LBR's source, which we named linear unwinding. As instruction from linear range can come from different function by inlining, linear unwinding will do the range splitting and record counters through the range with same inline context.
With each fall through path from LBR unwinding, we aggregate each sample into counters by the calling context and eventually generate full context sensitive profile (without relying on inlining) to driver compiler's PGO/FDO.
A breakdown of noteworthy changes:
- Added `HybridSample` class as the abstraction perf sample including LBR stack and call stack
* Extended `PerfReader` to implement auto-detect whether input perf script output contains CS profile, then do the parsing. Multiple `HybridSample` are extracted
* Speed up by aggregating `HybridSample` into `AggregatedSamples`
* Added VirtualUnwinder that consumes aggregated `HybridSample` and implements unwinding of calls, returns, and linear path that contains implicit call/return from inlining. Ranges and branches counters are aggregated by the calling context. Here calling context is string type, each context is a pair of function name and callsite location info, the whole context is like `main:1 @ foo:2 @ bar`.
* Added PorfileGenerater that accumulates counters by ranges unfolding or branch target mapping, then generates context-sensitive function profile including function body, inferring callee's head sample, callsite target samples, eventually records into ProfileMap.
* Leveraged LLVM build-in(`SampleProfWriter`) writer to support different serialization format with no stop
- `getCanonicalFnName` for callee name and name from ELF section
- Added regression test for both unwinding and profile generation
Test Plan:
ninja & ninja check-llvm
Reviewed By: hoy, wenlei, wmi
Differential Revision: https://reviews.llvm.org/D89723
wlei