cff-version: 1.2.0 title: CUTLASS message: >- If you use this software, please cite using the following metadata. type: software authors: - given-names: Vijay family-names: Thakkar email: vithakkar@nvidia.com affiliation: NVIDIA - given-names: Pradeep family-names: Ramani email: prramani@nvidia.com affiliation: NVIDIA - given-names: Cris family-names: Cecka email: ccecka@nvidia.com affiliation: NVIDIA - given-names: Aniket family-names: Shivam email: ashivam@nvidia.com affiliation: NVIDIA - given-names: Honghao family-names: Lu email: honghaol@nvidia.com affiliation: NVIDIA - given-names: Ethan family-names: Yan email: etyan@nvidia.com affiliation: NVIDIA - given-names: Jack family-names: Kosaian email: jkosaian@nvidia.com affiliation: NVIDIA - given-names: Mark family-names: Hoemmen email: mhoemmen@nvidia.com affiliation: NVIDIA - given-names: Haicheng family-names: Wu email: haichengw@nvidia.com affiliation: NVIDIA - given-names: Andrew family-names: Kerr email: akerr@nvidia.com affiliation: NVIDIA - given-names: Matt family-names: Nicely email: mnicely@nvidia.com affiliation: NVIDIA - given-names: Duane family-names: Merrill email: dumerrill@nvidia.com affiliation: NVIDIA - given-names: Dustyn family-names: Blasig email: dblasig@nvidia.com affiliation: NVIDIA - given-names: Fengqi family-names: Qiao email: fqiao@nvidia.com affiliation: NVIDIA - given-names: Piotr family-names: Majcher email: pmajcher@nvidia.com affiliation: NVIDIA - given-names: Paul family-names: Springer email: pspringer@nvidia.com affiliation: NVIDIA - given-names: Markus family-names: Hohnerbach affiliation: NVIDIA email: mhohnerbach@nvidia.com - given-names: Jin family-names: Wang email: jinw@nvidia.com affiliation: NVIDIA - given-names: Manish family-names: Gupta affiliation: Google email: manigupta@google.com repository-code: 'https://github.com/NVIDIA/cutlass' abstract: >- CUTLASS is a collection of CUDA C++ template abstractions for implementing high-performance matrix-multiplication (GEMM) and related computations at all levels and scales within CUDA. It incorporates strategies for hierarchical decomposition and data movement similar to those used to implement cuBLAS and cuDNN. CUTLASS decomposes these "moving parts" into reusable, modular software components abstracted by C++ template classes. These thread-wide, warp-wide, block-wide, and device-wide primitives can be specialized and tuned via custom tiling sizes, data types, and other algorithmic policy. The resulting flexibility simplifies their use as building blocks within custom kernels and applications. keywords: - 'cutlass, tensor cores, cuda, cute, nvidia, gpu, linear algebra, matrix computations' license: BSD-3-Clause license-url: https://github.com/NVIDIA/cutlass/blob/v3.0.0/LICENSE.txt version: '3.0.0' date-released: '2023-01-23' identifiers: - type: url value: "https://github.com/NVIDIA/cutlass/tree/v3.0.0" description: The GitHub release URL of tag 3.0.0