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CUTLASS 3.2.1 (#1113)

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* Updates for 3.2.1 release.

* Minor fix in gemm op profiler for raster order.

* Add scheduler mapping for raster order in the kernels.
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ANIKET SHIVAM
2023-09-26 17:24:26 -04:00
committed by GitHub
parent e0aaa3c3b3
commit 90d3b0fb18
428 changed files with 22252 additions and 21761 deletions
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README.md
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@@ -43,7 +43,7 @@ In addition to GEMMs, CUTLASS implements high-performance convolution via the im
# What's New in CUTLASS 3.2
CUTLASS 3.2 is an update to CUTLASS adding:
CUTLASS 3.2.0 is an update to CUTLASS adding:
- New warp-specialized persistent FP8 GEMM kernel [kernel schedules](/include/cutlass/gemm/kernel/sm90_gemm_tma_warpspecialized_cooperative.hpp) and [mainloops](/include/cutlass/gemm/collective/sm90_mma_tma_gmma_ss_warpspecialized_fp8.hpp) targeting Hopper architecture that achieve great performance with TMA, WGMMA, and threadblock clusters. An example showcasing [Hopper warp-specialized FP8 GEMMs](/examples/54_hopper_fp8_warp_specialized_gemm).
- New [Epilogue Visitor Tree (EVT)](/examples/49_hopper_gemm_with_collective_builder/49_collective_builder.cu) support for Hopper TMA epilogues. EVTs allows for user-defined customized epilogue fusion patterns without having to write a new epilogue.
- [Stream-K](/include/cutlass/gemm/kernel/sm90_tile_scheduler_stream_k.hpp) feature for Hopper. Note that this is only a functional implementation of stream-K, and should not be used for performance comparison. Optimizations are expected in a future release.
@@ -53,6 +53,14 @@ CUTLASS 3.2 is an update to CUTLASS adding:
- New CUTLASS 2D Convolution Python interface. New [example](/examples/python/03_basic_conv2d.ipynb) here.
- Support for Windows (MSVC) builds.
CUTLASS 3.2.1 is an update to CUTLASS adding:
- Python support SM90 Epilogue Visitor Tree (EVT) on top of the C++ support released in 3.2.0.
- SM80 EVT support in C++ and Python.
- Splitting CUTLASS library into smaller units based on operation, arch and datatypes. See [1105](https://github.com/NVIDIA/cutlass/discussions/1105) for details.
- Making `tools/library/scripts` packageable - `tools/library/scripts` is now moving to `python/cutlass_library`. See the Python [README](/python/README.md) for details.
- SM90 TF32 kernel improvements for all layouts.
- SM90 rasterization direction support in the CUTLASS profiler.
- Improvement for CUTLASS profiler build times.
Minimum requirements:
@@ -176,7 +184,8 @@ CUTLASS is a header-only template library and does not need to be built to be us
projects. Client applications should target CUTLASS's `include/` directory in their include
paths.
CUTLASS unit tests, examples, and utilities can be build with CMake starting version 3.12.
CUTLASS unit tests, examples, and utilities can be build with CMake.
The minimum version of CMake is given in the [Quickstart guide](media/docs/quickstart.md).
Make sure the `CUDACXX` environment variable points to NVCC in the CUDA Toolkit installed
on your system.
@@ -512,7 +521,7 @@ reference_device: Passed
## More Details on Compiling CUTLASS Kernels and CUTLASS Profiler
- Please follow the links for more CMake examples on selectively compiling CUTLASS kernels:
- [GEMM CMake Examples](media/docs/quickstart.md#gemm-cmake-examples)
- [Implicit GEMM conovlution CMake Examples](media/docs/quickstart.md#convolution-cmake-examples)
- [Implicit GEMM convolution CMake Examples](media/docs/quickstart.md#convolution-cmake-examples)
- [Further details about the CUTLASS Profiler are described here.](media/docs/profiler.md)