Merge pull request #2669 from NVIDIA/421_update

4.2.1 update
This commit is contained in:
ANIKET SHIVAM
2025-09-23 14:02:29 -07:00
committed by GitHub
6 changed files with 24 additions and 6 deletions
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# CUTLASS 4.x # CUTLASS 4.x
# CUTLASS 4.2.1
## [4.2.1](https://github.com/NVIDIA/cutlass/releases/tag/v4.2.1) (2025-09-22)
### CuTe DSL
* Bug fixings and improvements
- Fixed an issue when running DSL codes with cuda-python 13.0
- Fixed an issue when running inductor with DSL codes
- Fixed an issue with unexpected logging when running DSL codes in FlashInfer
- Fixed the issue reported in https://github.com/NVIDIA/cutlass/issues/2647
- Fixed an issue when conditional define of variables outside of dynamic control flow
### CUTLASS C++
* Bypass EVT for nosmem blockwise kernels on Blackwell.
* Rename cutlass/python/cutlass directory to cutlass/python/cutlass_cppgen.
## [4.2.0](https://github.com/NVIDIA/cutlass/releases/tag/v4.2.0) (2025-09-15) ## [4.2.0](https://github.com/NVIDIA/cutlass/releases/tag/v4.2.0) (2025-09-15)
### CuTe DSL ### CuTe DSL
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![ALT](./media/images/gemm-hierarchy-with-epilogue-no-labels.png "Complete CUDA GEMM decomposition") ![ALT](./media/images/gemm-hierarchy-with-epilogue-no-labels.png "Complete CUDA GEMM decomposition")
# Overview # Overview
# CUTLASS 4.2.0 # CUTLASS 4.2.1
_CUTLASS 4.2.0 - Sept 2025_ _CUTLASS 4.2.1 - Sept 2025_
CUTLASS is a collection of abstractions for implementing high-performance matrix-matrix multiplication (GEMM) CUTLASS is a collection of abstractions for implementing high-performance matrix-matrix multiplication (GEMM)
and related computations at all levels and scales within CUDA. It incorporates strategies for and related computations at all levels and scales within CUDA. It incorporates strategies for
@@ -224,7 +224,10 @@ CUTLASS runs successfully on the following NVIDIA GPUs, and it is expected to be
|NVIDIA H100 Tensor Core GPU |9.0|11.8| |NVIDIA H100 Tensor Core GPU |9.0|11.8|
|NVIDIA H200 Tensor Core GPU |9.0|11.8| |NVIDIA H200 Tensor Core GPU |9.0|11.8|
|NVIDIA B200 Tensor Core GPU |10.0|12.8| |NVIDIA B200 Tensor Core GPU |10.0|12.8|
|NVIDIA B300 Tensor Core GPU |10.3|13.0|
|NVIDIA DRIVE Thor |11.0|13.0|
|NVIDIA GeForce RTX 50x0 series |12.0|12.8| |NVIDIA GeForce RTX 50x0 series |12.0|12.8|
|NVIDIA DGX Spark |12.1|13.0|
## Target Architecture ## Target Architecture
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#define CUTLASS_MAJOR 4 #define CUTLASS_MAJOR 4
#define CUTLASS_MINOR 2 #define CUTLASS_MINOR 2
#define CUTLASS_PATCH 0 #define CUTLASS_PATCH 1
#ifdef CUTLASS_VERSIONS_GENERATED #ifdef CUTLASS_VERSIONS_GENERATED
#include "cutlass/version_extended.h" #include "cutlass/version_extended.h"
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this._option_registry = OptionRegistry(device_cc()) this._option_registry = OptionRegistry(device_cc())
return this._option_registry return this._option_registry
this.__version__ = '4.2.0' this.__version__ = '4.2.1'
from cutlass_cppgen.backend import create_memory_pool from cutlass_cppgen.backend import create_memory_pool
from cutlass_cppgen.emit.pytorch import pytorch from cutlass_cppgen.emit.pytorch import pytorch
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@@ -36,7 +36,7 @@ from setuptools import setup
def perform_setup(): def perform_setup():
setup( setup(
name='cutlass_library', name='cutlass_library',
version='4.2.0', version='4.2.1',
description='CUTLASS library generation scripts', description='CUTLASS library generation scripts',
packages=['cutlass_library'] packages=['cutlass_library']
) )
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@@ -36,7 +36,7 @@ from setuptools import setup
def perform_setup(): def perform_setup():
setup( setup(
name='pycute', name='pycute',
version='4.2.0', version='4.2.1',
description='Python implementation of CuTe', description='Python implementation of CuTe',
packages=['pycute'], packages=['pycute'],
) )