3 Commits

Author	SHA1	Message	Date
Mikhail Zolotukhin	dd96c26066	[TensorExpr] More NFC changes like Expr* -> ExprPtr. (#63778) ... Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63778 This is a preparation for a switch from raw pointers to shared pointers as a memory model for TE expressions and statements. Test Plan: Imported from OSS Reviewed By: navahgar Differential Revision: D30487425 Pulled By: ZolotukhinM fbshipit-source-id: 9cbe817b7d4e5fc2f150b29bb9b3bf578868f20c	2021-08-24 00:30:49 -07:00
Mikhail Zolotukhin	1263448cb2	[TensorExpr] Remove mask field from Load and Store classes. (#55825) ... Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/55825 The mask has never been used (in vectorization we generate an explicit `IfThenElse` construct when we need to mask out some elements). The PR removes it and cleans up all its traces from tests. Differential Revision: D27717776 Test Plan: Imported from OSS Reviewed By: navahgar Pulled By: ZolotukhinM fbshipit-source-id: 41d1feeea4322da75b3999d661801c2a7f82b9db	2021-04-13 12:08:51 -07:00
Raghavan Raman	8af648354f	[nnc] Benchmarks for concat (#52592) ... Summary: This PR adds a c++ benchmark for "concat" with 3 different versions - 1) aten::cat, 2) NNC implementation with if-then-else, 3) NNC implementation using multiple loops. It also adds a python benchmark for "concat" which can now be invoked with and without CPU fusion. Here are the results of these benchmarks on a `Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz` machine with `OMP_NUM_THREADS=1` ``` -------------------------------------------------------------------------------------------------------------------------- Benchmark Time CPU Iterations UserCounters... -------------------------------------------------------------------------------------------------------------------------- Concat2D2 (678fe9f077)Input/ATen/1/160/1/14/1 1211 ns 1211 ns 567896 GB/s=1.14953G/s Concat2D2 (678fe9f077)Input/ATen/1/580/1/174/1 1296 ns 1296 ns 537060 GB/s=4.65362G/s Concat2D2 (678fe9f077)Input/ATen/20/160/20/14/1 1823 ns 1823 ns 382052 GB/s=15.2677G/s Concat2D2 (678fe9f077)Input/ATen/20/580/20/174/1 3347 ns 3347 ns 210036 GB/s=36.0432G/s Concat2D2 (678fe9f077)Input/ATen/8/512/8/512/1 2093 ns 2093 ns 324760 GB/s=31.3061G/s Concat2D2 (678fe9f077)Input/NNC/1/160/1/14/1 694 ns 694 ns 1002902 GB/s=2.00692G/s Concat2D2 (678fe9f077)Input/NNC/1/580/1/174/1 852 ns 852 ns 803002 GB/s=7.08127G/s Concat2D2 (678fe9f077)Input/NNC/20/160/20/14/1 1639 ns 1639 ns 419683 GB/s=16.9828G/s Concat2D2 (678fe9f077)Input/NNC/20/580/20/174/1 5956 ns 5956 ns 117833 GB/s=20.2548G/s Concat2D2 (678fe9f077)Input/NNC/8/512/8/512/1 3136 ns 3136 ns 224122 GB/s=20.8958G/s Concat2D2 (678fe9f077)Input/NNCLoop/1/160/1/14/1 581 ns 581 ns 1209873 GB/s=2.39737G/s Concat2D2 (678fe9f077)Input/NNCLoop/1/580/1/174/1 614 ns 614 ns 1132332 GB/s=9.82955G/s Concat2D2 (678fe9f077)Input/NNCLoop/20/160/20/14/1 1091 ns 1091 ns 622952 GB/s=25.5247G/s Concat2D2 (678fe9f077)Input/NNCLoop/20/580/20/174/1 2399 ns 2399 ns 288376 GB/s=50.289G/s Concat2D2 (678fe9f077)Input/NNCLoop/8/512/8/512/1 1500 ns 1500 ns 478360 GB/s=43.6968G/s Concat2D3 (e23ddf06e9)Input/ATen/8/512/8/512/8/512/1 2584 ns 2584 ns 266394 GB/s=38.0397G/s Concat2D3 (e23ddf06e9)Input/NNC/8/512/8/512/8/512/1 5056 ns 5056 ns 139768 GB/s=19.4416G/s Concat2D3 (e23ddf06e9)Input/NNCLoop/8/512/8/512/8/512/1 1917 ns 1917 ns 369626 GB/s=51.2758G/s Concat2D7 (b5edf329f8)Input/ATen/8/128/8/256/8/384/8/512/8/512/8/512/8/512/1 3888 ns 3888 ns 178124 GB/s=46.3571G/s Concat2D7 (b5edf329f8)Input/NNC/8/128/8/256/8/384/8/512/8/512/8/512/8/512/1 24639 ns 24638 ns 28336 GB/s=7.31481G/s Concat2D7 (b5edf329f8)Input/NNCLoop/8/128/8/256/8/384/8/512/8/512/8/512/8/512/1 3093 ns 3093 ns 226326 GB/s=58.265G/s ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/52592 Reviewed By: bertmaher Differential Revision: D26596701 Pulled By: navahgar fbshipit-source-id: 650fa88febf4423ea49f5a1d3d734edc2294d257	2021-02-24 06:09:32 -08:00