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| README | https://github.com/lfopensource/cutlass |
| License | https://github.com/lfopensource/cutlass |
| https://github.com/lfopensource/cutlass/blob/main/media/images/gemm-hierarchy-with-epilogue-no-labels.png |
| https://github.com/lfopensource/cutlass#overview |
| https://github.com/lfopensource/cutlass#cutlass-435 |
| FP32 emulation via tensor core instruction | https://github.com/NVIDIA/cutlass/tree/main/examples/27_ampere_3xtf32_fast_accurate_tensorop_gemm |
| CUTLASS C++ Quick Start Guide | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/quickstart.html |
| CuTe DSL Quick Start Guide | https://docs.nvidia.com/cutlass/latest/media/docs/pythonDSL/quick_start.html |
| https://github.com/lfopensource/cutlass#whats-new-in-cutlass-43 |
| https://github.com/lfopensource/cutlass#cute-dsl |
| TVM-FFI | https://tvm.apache.org/ffi/index.html |
| Kernel launch with Programmatic Dependent Launch | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/blackwell/programmatic_dependent_launch.py |
| Hello World Example | https://github.com/NVIDIA/cutlass/blob/main/examples/python/CuTeDSL/notebooks/hello_world.ipynb |
| elementwise example | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/ampere/elementwise_apply.py |
| Blackwell SM100 persistent dense GEMM with static scheduling | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/blackwell/dense_gemm_persistent.py |
| Tutorial for Blackwell GEMM: Basic Blackwell SM100 GEMM | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/blackwell/tutorial_gemm |
| Baseline Blackwell GEMM | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/blackwell/tutorial_gemm/fp16_gemm_0.py |
| Tutorial for Async Pipeline API | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/notebooks/async_pipeline.ipynb |
| elementwise add notebook | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/notebooks/elementwise_add.ipynb |
| Benchmark and autotune demonstration | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/notebooks/benchmark_autotune.ipynb |
| Blackwell SM100 mixed-input GEMM | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/blackwell/mixed_input_gemm.py |
| Blackwell SM100 persistent blockwise dense GEMM | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/blackwell/blockwise_gemm/blockwise_gemm.py |
| Blackwell SM100 persistent blockwise contiguous grouped dense GEMM | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/blackwell/blockwise_gemm/contiguous_grouped_gemm.py |
| Blackwell SM100 persistent blockwise masked grouped dense GEMM | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/blackwell/blockwise_gemm/masked_grouped_gemm.py |
| Blackwell SM100 fmha bwd | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/blackwell/fmha_bwd.py |
| Blackwell SM100 mla | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/blackwell/mla.py |
| Hopper SM90 persistent dense GEMM with static scheduling | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/hopper/dense_gemm_persistent.py |
| Blackwell GeForce batched dense GEMM | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/blackwell_geforce/dense_gemm.py |
| Ampere HSTU Attention | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/ampere/hstu_attention.py |
| DSL API changelog | https://docs.nvidia.com/cutlass/latest/media/docs/pythonDSL/cute_dsl_api/changelog.html |
| Blackwell SM100 persistent dense blockscaled GEMM with static scheduling | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/blackwell/dense_blockscaled_gemm_persistent.py |
| Blackwell SM100 persistent dense blockscaled GEMM with static scheduling | https://github.com/NVIDIA/cutlass/tree/main/examples/python/CuTeDSL/blackwell/dense_blockscaled_gemm_persistent.py |
| https://github.com/lfopensource/cutlass#cutlass-c |
| example 77 | https://github.com/NVIDIA/cutlass/tree/main/examples/77_blackwell_fmha/ |
| example 89 | https://github.com/NVIDIA/cutlass/tree/main/examples/89_sm103_fp4_ultra_gemm/ |
| example 92 | https://github.com/NVIDIA/cutlass/tree/main/examples/92_blackwell_moe_gemm/ |
| example 67 | https://github.com/NVIDIA/cutlass/tree/main/examples/67_hopper_fp8_warp_specialized_gemm_with_blockwise_scaling/ |
| fprop_streamK | https://github.com/NVIDIA/cutlass/tree/main/test/unit/conv/device_3x/fprop/sm100_conv3d_fprop_implicit_gemm_f16_f16_f16_tensorop_f16_streamk.cu |
| dgrad_streamK | https://github.com/NVIDIA/cutlass/tree/main/test/unit/conv/device_3x/dgrad/sm100_conv3d_dgrad_implicit_gemm_f16_f16_f16_tensorop_f16_streamk.cu |
| wgrad_streamK | https://github.com/NVIDIA/cutlass/tree/main/test/unit/conv/device_3x/wgrad/sm100_conv2d_wgrad_implicit_gemm_f16_f16_f16_tensorop_f16_streamk.cu |
| compressor_fp16 | https://github.com/NVIDIA/cutlass/tree/main/test/unit/transform/device/sm100_sparse_gemm_compressor_f16.cu |
| CHANGELOG | https://docs.nvidia.com/cutlass/latest/CHANGELOG.html |
| https://github.com/lfopensource/cutlass#performance |
| https://github.com/lfopensource/cutlass/blob/main/media/images/cutlass-3.8-blackwell-gemm-peak-performance.svg |
| NVIDIA H100 | https://www.nvidia.com/en-us/data-center/h100/ |
| CUDA 12.5u1 Toolkit | https://developer.nvidia.com/cuda-downloads |
| mma | https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#warp-level-matrix-instructions-mma |
| wgmma | https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#asynchronous-warpgroup-level-matrix-instructions |
| https://github.com/lfopensource/cutlass/blob/main/media/images/cutlass-3.5.1-gemm-peak-performance.png |
| https://github.com/lfopensource/cutlass/blob/main/media/images/cutlass-3.5.1-gemm-peak-performance-fp8.png |
| https://github.com/lfopensource/cutlass#cute |
| dedicated documentation directory | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/cute/00_quickstart.html |
| https://github.com/lfopensource/cutlass#compatibility |
| CUDA 12.8 Toolkit | https://developer.nvidia.com/cuda-downloads |
| https://github.com/lfopensource/cutlass#operating-systems |
| https://github.com/lfopensource/cutlass#hardware |
| https://github.com/lfopensource/cutlass#target-architecture |
| CUDA Documentation | https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#feature-availability |
| functionality documentation | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/functionality.html |
| https://github.com/lfopensource/cutlass#documentation |
| Doxygen documentation | https://nvidia.github.io/cutlass |
| Quick Start Guide | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/quickstart.html |
| Functionality | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/functionality.html |
| Efficient GEMM in CUDA | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/efficient_gemm.html |
| CUTLASS 3.x Design | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/cutlass_3x_design.html |
| GEMM API 3.x | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/gemm_api_3x.html |
| GEMM API 2.x | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/gemm_api.html |
| Implicit GEMM Convolution | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/implicit_gemm_convolution.html |
| Code Organization | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/code_organization.html |
| Terminology | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/terminology.html |
| Programming Guidelines | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/programming_guidelines.html |
| Fundamental types | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/fundamental_types.html |
| Layouts | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/layout.html |
| Tile Iterators | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/tile_iterator_concept.html |
| CUTLASS Profiler | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/profiler.html |
| CUTLASS Utilities | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/utilities.html |
| Dependent kernel launch | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/dependent_kernel_launch.html |
| https://github.com/lfopensource/cutlass#resources |
| GPU Technology Conference 2018 | http://on-demand.gputechconf.com/gtc/2018/presentation/s8854-cutlass-software-primitives-for-dense-linear-algebra-at-all-levels-and-scales-within-cuda.pdf |
| CUTLASS: Software Primitives for Dense Linear Algebra at All Levels and Scales within CUDA | https://www.nvidia.com/en-us/on-demand/session/gtcsiliconvalley2018-s8854/ |
| Developing CUDA Kernels to Push Tensor Cores to the Absolute Limit on NVIDIA A100 | https://www.nvidia.com/en-us/on-demand/session/gtcsj20-s21745/ |
| Accelerating Convolution with Tensor Cores in CUTLASS | https://www.nvidia.com/en-us/on-demand/session/gtcspring21-s31883/ |
| Accelerating Backward Data Gradient by Increasing Tensor Core Utilization in CUTLASS | https://www.nvidia.com/en-us/on-demand/session/gtcspring22-s41996/ |
| CUTLASS: Python API, Enhancements, and NVIDIA Hopper | https://www.nvidia.com/en-us/on-demand/session/gtcfall22-a41131/ |
| https://github.com/lfopensource/cutlass#building-cutlass |
| Quickstart guide | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/quickstart.html |
| https://github.com/lfopensource/cutlass#project-structure |
| Doxygen documentation | https://nvidia.github.io/cutlass |
| CUTLASS documentation | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/code_organization.html |
| https://github.com/lfopensource/cutlass#cutlass-template-library |
| https://github.com/lfopensource/cutlass#cutlass-sdk-examples |
| CUTLASS SDK examples | https://github.com/NVIDIA/cutlass/tree/main/examples |
| https://github.com/lfopensource/cutlass#tools |
| https://github.com/lfopensource/cutlass#test |
| Quickstart guide | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/quickstart.html |
| https://github.com/lfopensource/cutlass#performance-profiling |
| https://github.com/lfopensource/cutlass#building-all-gemm-and-convolution-kernels-long-build-times |
| https://github.com/lfopensource/cutlass#building-a-subset-of-gemm-and-convolution-kernels-reduced-build-times |
| https://github.com/lfopensource/cutlass#building-a-subset-tensor-core-gemm-kernels |
| https://github.com/lfopensource/cutlass#building-one-cuda-core-gemm-kernel |
| https://github.com/lfopensource/cutlass#building-a-subset-of-tensor-core-convolution-kernels |
| https://github.com/lfopensource/cutlass#building-one-convolution-cuda-kernel |
| https://github.com/lfopensource/cutlass#more-details-on-compiling-cutlass-kernels-and-cutlass-profiler |
| GEMM CMake Examples | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/quickstart.html#gemm-cmake-examples |
| Implicit GEMM convolution CMake Examples | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/quickstart.html#convolution-cmake-examples |
| Further details about the CUTLASS Profiler are described here. | https://docs.nvidia.com/cutlass/latest/media/docs/cpp/profiler.html |
| https://github.com/lfopensource/cutlass#about |
| 3-clause "New" BSD license | https://github.com/lfopensource/cutlass/blob/main/LICENSE.txt |
| https://github.com/lfopensource/cutlass#contributors |
| CONTRIBUTORS | https://github.com/lfopensource/cutlass/blob/main/CONTRIBUTORS.md |
| https://github.com/lfopensource/cutlass#copyright |
| Readme | https://github.com/lfopensource/cutlass#readme-ov-file |
| License | https://github.com/lfopensource/cutlass#License-1-ov-file |
| Activity | https://github.com/lfopensource/cutlass/activity |
| 0 forks | https://github.com/lfopensource/cutlass/forks |
| Report repository | https://github.com/contact/report-content?content_url=https%3A%2F%2Fgithub.com%2Flfopensource%2Fcutlass&report=lfopensource+%28user%29 |
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| Status | https://www.githubstatus.com/ |
| Community | https://github.community/ |
| Docs | https://docs.github.com/ |
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