pytorch

f7a8bf28 - Use libkineto in profiler (#46470)

Use libkineto in profiler (#46470) Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/46470 Adding ability to use Kineto (CUPTI) to profile CUDA kernels Test Plan: USE_KINETO=1 USE_CUDA=1 USE_MKLDNN=1 BLAS=MKL BUILD_BINARY=1 python setup.py develop install python test/test_profiler.py python test/test_autograd.py -k test_profile python test/test_autograd.py -k test_record ``` ------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ Name Self CPU % Self CPU CPU total % CPU total CPU time avg Self CUDA Self CUDA % CUDA total CUDA time avg # of Calls ------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ Memcpy HtoD (Pageable -> Device) 0.00% 0.000us 0.00% 0.000us 0.000us 2.000us 33.33% 2.000us 1.000us 2 sgemm_32x32x32_NN 0.00% 0.000us 0.00% 0.000us 0.000us 2.000us 33.33% 2.000us 2.000us 1 void at::native::vectorized_elementwise_kernel<4, at... 0.00% 0.000us 0.00% 0.000us 0.000us 1.000us 16.67% 1.000us 1.000us 1 Memcpy DtoH (Device -> Pageable) 0.00% 0.000us 0.00% 0.000us 0.000us 1.000us 16.67% 1.000us 1.000us 1 aten::randn 5.17% 74.000us 6.71% 96.000us 48.000us 0.000us 0.00% 0.000us 0.000us 2 aten::empty 1.33% 19.000us 1.33% 19.000us 4.750us 0.000us 0.00% 0.000us 0.000us 4 aten::normal_ 1.05% 15.000us 1.05% 15.000us 7.500us 0.000us 0.00% 0.000us 0.000us 2 aten::to 77.90% 1.114ms 91.61% 1.310ms 436.667us 0.000us 0.00% 3.000us 1.000us 3 aten::empty_strided 2.52% 36.000us 2.52% 36.000us 12.000us 0.000us 0.00% 0.000us 0.000us 3 aten::copy_ 2.73% 39.000us 11.19% 160.000us 53.333us 0.000us 0.00% 3.000us 1.000us 3 cudaMemcpyAsync 4.34% 62.000us 4.34% 62.000us 20.667us 0.000us 0.00% 0.000us 0.000us 3 cudaStreamSynchronize 1.61% 23.000us 1.61% 23.000us 7.667us 0.000us 0.00% 0.000us 0.000us 3 aten::mm 0.21% 3.000us 7.20% 103.000us 103.000us 0.000us 0.00% 2.000us 2.000us 1 aten::stride 0.21% 3.000us 0.21% 3.000us 1.000us 0.000us 0.00% 0.000us 0.000us 3 cudaLaunchKernel 2.45% 35.000us 2.45% 35.000us 17.500us 0.000us 0.00% 0.000us 0.000us 2 aten::add 0.49% 7.000us 4.27% 61.000us 61.000us 0.000us 0.00% 1.000us 1.000us 1 ------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ``` benchmark: https://gist.github.com/ilia-cher/a5a9eb6b68504542a3cad5150fc39b1a Reviewed By: Chillee Differential Revision: D25142223 Pulled By: ilia-cher fbshipit-source-id: b0dff46c28da5fb0a8e01cf548aa4f2b723fde80