From f248e9bdb4a6e59bd665241f11cc76754b3c9429 Mon Sep 17 00:00:00 2001 From: Haicheng Wu <57973641+hwu36@users.noreply.github.com> Date: Tue, 7 Jun 2022 21:25:16 -0400 Subject: [PATCH] Create CITATION.cff Add initial CITATION.cff --- CITATION.cff | 82 ++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 82 insertions(+) create mode 100644 CITATION.cff diff --git a/CITATION.cff b/CITATION.cff new file mode 100644 index 00000000..ea053e66 --- /dev/null +++ b/CITATION.cff @@ -0,0 +1,82 @@ +cff-version: 1.2.0 +title: CUTLASS +message: >- + If you use this software, please cite using the + following metadata. +type: software +authors: + - given-names: Andrew + email: akerr@nvidia.com + family-names: Kerr + affiliation: NVIDIA + - given-names: Haicheng + family-names: Wu + affiliation: NVIDIA + email: haichengw@nvidia.com + - given-names: Manish + family-names: Gupta + affiliation: Google + email: manigupta@google.com + - given-names: Dustyn + family-names: Blasig + email: dblasig@nvidia.com + affiliation: NVIDIA + - given-names: Pradeep + family-names: Ramini + email: prramani@nvidia.com + affiliation: NVIDIA + - given-names: Duane + family-names: Merrill + email: dumerrill@nvidia.com + affiliation: NVIDIA + - given-names: Aniket + family-names: Shivam + email: ashivam@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: Matt + family-names: Nicely + email: mnicely@nvidia.com + affiliation: NVIDIA +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' +license: BSD-3-Clause +license-url: https://github.com/NVIDIA/cutlass/blob/v2.9.0/LICENSE.txt +version: '2.9' +date-released: '2022-04-27' +identifiers: + - type: url + value: "https://github.com/NVIDIA/cutlass/tree/v2.9.0" + description: The GitHub release URL of tag 2.9.0