> Hi @jianyuh I am getting following error when I try to run my benchmark. It
> gives following error,
>
> ```
> LLVM ERROR: Cannot select: 0x23809ef0: v16i32 = X86ISD::VPDPBUSD 0x210a09a8,
> 0x210a02c0, 0x19eb81b0
> 0x210a09a8: v16i32 = BUILD_VECTOR Constant:i32<0>, Constant:i32<0>,
> Consta
> @jianyuh please act on the review comments @were please
> https://docs.tvm.ai/contribute/code_review.html#approve-and-request-changes-explicitly
> @jianyuh please act on the review comments @were please
> https://docs.tvm.ai/contribute/code_review.html#approve-and-request-changes-explicitly
I
> If we have time, we could investigate why we couldn't achieve 252GFlops even
> more. Only 73% hardware efficiency means we have much work could dive.
252 Gops/s is a reasonable number as this is ~90% hardware efficiency.
Currently FBGEMM and MKL-DNN can reach this number. For the current PR, t
@FrozenGene @tqchen @anijain2305 @llyfacebook @were Ping for review.
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Similar to @anijain2305 's PR (https://github.com/dmlc/tvm/pull/3516),
currently we disable the AVX512 VNNI test in this PR.
Posted the question on tensorize failure in
https://discuss.tvm.ai/t/workaround-for-tensorize-failure/3577.
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> I am not sure if tensorize is a good way to suport VNNI:
>
> 1. VNNI is not true tensorization, though reduction dimension is introduced.
> It still operates on 1-D inputs. Due to the design of `tensorization`
> interface, you need to provide the declared intrin the shape of tensors
> offload
I can run the correct result locally. Also updated the summary part for this PR
to report the performance results.
However, I had the same issue as https://github.com/dmlc/tvm/issues/3598 for
the OSS compilation error
(http://ci.tvm.ai:8080/blue/organizations/jenkins/tvm/detail/PR-3388/11/pipel
@tqchen : Will take a look soon. Let me know if this PR becomes the blockers
for other things.
The current failure is shown as the following:
> http://ci.tvm.ai:8080/blue/organizations/jenkins/tvm/detail/PR-3388/7/pipeline
When I use tensorize routine and pass in “dot_16x1x16_int8_int8_int32” fun
My PR was based on the previous version of TVM. Not sure what are the recent
changes for TVM.
>> http://ci.tvm.ai:8080/blue/organizations/jenkins/tvm/detail/PR-3388/6/pipeline/
Not sure why “llvm.x86.avx512.pmaddubs.w.512“ (AVX512 instruction, not VNNI
instruction) is not recognized as an LLVM i
@tqchen Will update this soon (sorry for being busy with some other things
recently).
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