[llvm-dev] AMDGPU and support for the new pass manager

Arthur Eubanks via llvm-dev
2021-01-07T20:28:00Z

We're sorting out the custom inliner in https://reviews.llvm.org/D94153.

As for LegacyDivergenceAnalysis and
Transforms/LoopUnswitch/AMDGPU/divergent-unswitch.ll, if there's no
response, I'll just pin the test to the legacy PM, since it's testing an
AMDGPU-specific optimization setting (disabling loop unswitching on
divergent loop conditions). If there are noticeable performance regressions
related to this due to the NPM switch, the AMDGPU community can temporarily
use the legacy PM and then port the relevant analysis passes and fix up
loop unswitching for AMDGPU.

Then we should be good to go for turning on the new PM for opt when it's
specified on the CMake command line.

On Mon, Jan 4, 2021 at 2:16 PM Arthur Eubanks <aeubanks at google.com>
wrote:

> I've ported most of the IR passes and added them to AMDGPU's opt
pipeline.
> There are 2 issues remaining:
> 1) LegacyDivergenceAnalysis is used in LoopUnswitch to avoid unswitching
> loops with divergent condition Values. I'm not sure what the state of
the
> LegacyDivergenceAnalysis vs DivergenceAnalysis is. (Also the new PM only
> has SimpleLoopUnswitch instead of LoopUnswitch).
> Transforms/LoopUnswitch/AMDGPU/divergent-unswitch.ll.
> 2) The AMDGPU backend has its own inliner
>
<https://github.com/llvm/llvm-project/blob/main/llvm/lib/Target/AMDGPU/AMDGPUInline.cpp>
(set
> here
>
<https://github.com/llvm/llvm-project/blob/92be640bd7d4fbc8e032a0aa81381a0246efa0be/llvm/lib/Target/AMDGPU/AMDGPUTargetMachine.cpp#L438>).
> Any ideas for how to do custom inliner cost modeling in the new PM
> pipelines? Allow targets to override an analysis pass that the inliner uses
> to get an InlineAdvisor?
> CodeGen/AMDGPU/amdgpu-inline.ll
>
> On Fri, Dec 4, 2020 at 4:44 PM Arthur Eubanks <aeubanks at
google.com> wrote:
>
>> Some indicative failing tests are under the llvm/test/CodeGen/AMDGPU
>> directory when opt's -enable-new-pm flag is set to true by default.
They
>> should also be repro'able by adding a corresponding NPM RUN line,
e.g. "opt
>> -S -O1 -mtriple=amdgcn-- ..." -> "opt -S
-passes='default<O1>'
>> -mtriple=amdgcn-- ...".
>>
>> I see the following AMDGPU-specific failures:
>>   LLVM :: CodeGen/AMDGPU/amdgpu-inline.ll
>>   LLVM :: CodeGen/AMDGPU/infer-addrpace-pipeline.ll
>>   LLVM :: CodeGen/AMDGPU/internalize.ll
>>   LLVM :: CodeGen/AMDGPU/llvm.amdgcn.wavefrontsize.ll
>>   LLVM :: CodeGen/AMDGPU/opt-pipeline.ll
>>   LLVM :: CodeGen/AMDGPU/propagate-attributes-clone.ll
>>   LLVM :: CodeGen/AMDGPU/propagate-attributes-single-set.ll
>>   LLVM :: CodeGen/AMDGPU/simplify-libcalls.ll
>>   LLVM :: CodeGen/AMDGPU/sroa-before-unroll.ll
>>   LLVM :: Transforms/LoopUnswitch/AMDGPU/divergent-unswitch.ll
>>
>> (Also I took a closer look, actually it looks like NVPTX also needs
>> updating, but NVPTXTargetMachine only adds two passes)
>>
>> On Fri, Dec 4, 2020 at 3:48 PM Arthur Eubanks <aeubanks at
google.com>
>> wrote:
>>
>>> Currently AMDGPU is the last target which injects passes into the
>>> pipeline but hasn't been updated to work with the new pass
manager.
>>>
>>> Recently there was added support for the NPM's equivalent of
>>> TargetMachine::adjustPassManager(). (Bug
>>> <https://bugs.llvm.org/show_bug.cgi?id=47244>, Phab
>>> <https://reviews.llvm.org/D88138>). BPF
>>>
<https://github.com/llvm/llvm-project/blob/99f79cbf31cc6ccdfa1aed253a64c5e8012f4ef7/llvm/lib/Target/BPF/BPFTargetMachine.cpp#L126>
>>> and Hexagon have their NPM equivalents implemented already, but
AMDGPU
>>> has a lot of custom passes added by adjustPassManager
>>>
<https://github.com/llvm/llvm-project/blob/99f79cbf31cc6ccdfa1aed253a64c5e8012f4ef7/llvm/lib/Target/AMDGPU/AMDGPUTargetMachine.cpp#L420>
and
>>> hasn't been updated to work with the NPM.
>>>
>>> Could the maintainers of AMDGPU port the necessary passes to the
new
>>> pass manager add them to
>>> AMDGPUTargetMachine::registerPassBuilderCallbacks()? I'm happy
to provide
>>> any guidance if necessary. Here's
<https://reviews.llvm.org/D91990> an
>>> example of porting a pass and adding it to the pipeline.
>>>
>>
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