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Introduction

CUTLASS is a collection of CUDA C++ template abstractions for implementing high-performance matrix-multiplication (GEMM) at all levels and scales within CUDA. It incorporates strategies for hierarchical decomposition and data movement similar to those used to implement cuBLAS. 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.

To support a wide variety of applications, CUTLASS provides extensive support for mixed-precision computations, providing specialized data-movement and multiply-accumulate abstractions for 8-bit integer, half-precision floating point (FP16), single-precision floating point (FP32), and double-precision floating point (FP64) types. Furthermore, CUTLASS demonstrates CUDA's WMMA API for targeting the programmable, high-throughput Tensor Cores provided by NVIDIA's Volta architecture and beyond.

For more exposition, see our Parallel Forall blog post CUTLASS: Fast Linear Algebra in CUDA C++.

Performance

CUTLASS primitives are very efficient. When used to construct device-wide GEMM kernels, they exhibit performance comparable to cuBLAS for scalar GEMM computations. The above figure shows CUTLASS performance relative to cuBLAS for large matrix dimensions (M=10240, N=K=4096) running on an NVIDIA Tesla V100 GPU when compiled with CUDA 9.0.

Project Structure

CUTLASS is arranged as a header-only library with several example test programs that demonstrate instantiating a GEMM task within a CUDA kernel. Comments inline with the source explain the individual components.

The repository is organized in the following arrangement.

cutlass/                Root of header-only source library for matrix multiply
  gemm/                 Implementation of GEMM __device__ code and supporting components
  util/                 Utility components for CUDA device-side CUDA development

A test program is provided to illustrate the use of CUTLASS. This is implemented in the following directory.

cutlass_test            Root of test programs depicting CUTLASS kernels
  util/                 Utilities
  gemm.cu               Simple example calling CUTLASS and CUBLAS GEMM kernels
  Makefile              Build script for test programs

Makefile usage

There are different sample targets for different GEMM data types and transposititions. Be sure to specify your target architecture.

make <sgemm|dgemm|hgemm|igemm|wgemm> sm=<60|61|70> \
  [transpose=<nn|nt|tn|tt>] [verbose=<0|1>] [keep=<0|1>]

Program usage

Program usage:

 <s|d|h|i|w>gemm_<nn|nt|tn|tt>
       [--help]
       [--schmoo=<#schmoo-samples> || --m=<height> --n=<width> --k=<depth>]
       [--i=<timing iterations>]
       [--device=<device-id>]
       [--alpha=<alpha> --beta=<beta>]

Open Source License

CUTLASS is released by NVIDIA Corporation under the "New BSD" open-source license:

Copyright (c) 2017, NVIDIA CORPORATION.  All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
   *  Redistributions of source code must retain the above copyright
      notice, this list of conditions and the following disclaimer.
   *  Redistributions in binary form must reproduce the above copyright
      notice, this list of conditions and the following disclaimer in the
      documentation and/or other materials provided with the distribution.
   *  Neither the name of the NVIDIA CORPORATION nor the
      names of its contributors may be used to endorse or promote products
      derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Latest Releases
v0.1.0
 Dec. 5 2017