deb_control_files:
- control
- md5sums
deb_fields:
Architecture: all
Description: |-
CUDA Templates for Linear Algebra Subroutines
CUTLASS is a collection of CUDA C++ template abstractions for implementing
high-performance matrix-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. Primitives for
different levels of a conceptual parallelization hierarchy 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 half-precision floating point (FP16),
BFloat16 (BF16), Tensor Float 32 (TF32), single-precision floating point
(FP32), FP32 emulation via tensor core instruction, double-precision
floating point (FP64) types, integer data types (4b and 8b), and binary
data types (1b). CUTLASS demonstrates warp-synchronous matrix multiply
operations targeting the programmable, high-throughput Tensor Cores
implemented by NVIDIA's Volta, Turing, Ampere, and Hopper architectures.
.
This is a header-only library.
Homepage: https://github.com/NVIDIA/cutlass
Installed-Size: '11102'
Maintainer: Debian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
Package: libcutlass-dev
Priority: optional
Section: contrib/libdevel
Source: nvidia-cutlass
Version: 3.4.1+ds-1
srcpkg_name: nvidia-cutlass
srcpkg_version: 3.4.1+ds-1