Commit Graph

3 Commits

Author SHA1 Message Date
Jane Xu
533cb9530e Introducing TORCH_CUDA_CPP_API and TORCH_CUDA_CU_API to the code (#50627)
Summary:
Sub-step of my attempt to split up the torch_cuda library, as it is huge. Please look at https://github.com/pytorch/pytorch/issues/49050 for details on the split and which files are in which target.

This PR introduces two new macros for Windows DLL purposes, TORCH_CUDA_CPP_API and TORCH_CUDA_CU_API. Both are defined as TORCH_CUDA_API for the time being.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/50627

Reviewed By: mruberry

Differential Revision: D25955441

Pulled By: janeyx99

fbshipit-source-id: ff226026833b8fb2fb7c77df6f2d6c824f006869
2021-01-21 19:09:11 -08:00
jiej
ac146c4820 [nvFuser] Switching to CudaFusionGuard from BailOut for nvfuser - update 2 (#46452)
Summary:
1. Added CudaFusionGuard as the custom TypeCheck for nvfuser; enabled dynamic shape support with profiling executor;
2. dropped support for legacy fuser;
3. re-enabled nvfuser tests;
4. added registration for profiling record to allow profiling on user specified nodes.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/46452

Reviewed By: zou3519, anjali411

Differential Revision: D24364642

Pulled By: ngimel

fbshipit-source-id: daf53a9a6b6636e1ede420a3a6d0397d4a8b450b
2020-10-19 15:44:31 -07:00
jjsjann123
99e0a87bbb [nvFuser] Latency improvements for pointwise + reduction fusion (#45218)
Summary:
A lot of changes are in this update, some highlights:

- Added Doxygen config file
- Split the fusion IR (higher level TE like IR) from kernel IR (lower level CUDA like IR)
- Improved latency with dynamic shape handling for the fusion logic
- Prevent recompilation for pointwise + reduction fusions when not needed
- Improvements to inner dimension reduction performance
- Added input -> kernel + kernel launch parameters cache, added eviction policy
- Added reduction fusions with multiple outputs (still single reduction stage)
- Fixed code generation bugs for symbolic tiled GEMM example
- Added thread predicates to prevent shared memory form being loaded multiple times
- Improved sync threads placements with shared memory and removed read before write race
- Fixes to FP16 reduction fusions where output would come back as FP32

Pull Request resolved: https://github.com/pytorch/pytorch/pull/45218

Reviewed By: ezyang

Differential Revision: D23905183

Pulled By: soumith

fbshipit-source-id: 12f5ad4cbe03e9a25043bccb89e372f8579e2a79
2020-09-24 23:17:20 -07:00