cuSPARSELt v0.1.0 Now Available: Arm and Windows Support

NVIDIA announced the availability of cuSPARSELt version 0.1.0. This software can be downloaded now free for members of the NVIDIA Developer Program.

Today, NVIDIA is announcing the availability of cuSPARSELt version 0.1.0. This software can be downloaded now free for members of the NVIDIA Developer Program.

Download Now

What’s New

Support for Window 10 (x86_64)
Support for Linux ARM
Introduced SM 8.6 Compatibility
Support for TF32 compute type
Better performance for SM 8.0 kernels (up to 90% SOL)
Position independent sparseA / sparseB
New APIs for compression and pruning
- Decoupled from cusparseLtMatmulPlan_t

See the cuSPARSELt Release Notes for more information

About cuSPARSELt

NVIDIA cuSPARSELt is a high-performance CUDA library dedicated to general matrix-matrix operations in which at least one operand is a sparse matrix:

$D=alpha op(A) cdot op(B) + beta op(C)$

In this formula, $op(A)$ and $op(B)$ refer to in-place operations such as transpose/non-transpose.

The cuSPARSELt APIs allow flexibility in the algorithm/operation selection, epilogue, and matrix characteristics, including memory layout, alignment, and data types.

Key features:

NVIDIA Sparse MMA tensor core support
Mixed-precision computation support:
- FP16 input/output, FP32 Tensor Core accumulate
- BFLOAT16 input/output, FP32 Tensor Core accumulate
- INT8 input/output, INT32 Tensor Core compute
- FP32 input/output, TF32 Tensor Core compute
- TF32 input/output, TF32 Tensor Core compute
Matrix pruning and compression functionalities
Auto-tuning functionality (see cusparseLtMatmulSearch())

Learn more:

GTC 2021: S31754 Recent Developments in NVIDIA Math Libraries
GTC 2021: S31286 A Deep Dive into the Latest HPC Software
GTC 2021: CWES1098 Tensor Core-Accelerated Math Libraries for Dense and Sparse Linear Algebra in AI and HPC
cuSPARSELt Product Documentation

Recent Developer Blog posts:

Leave a Reply Cancel reply