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What is cuSPARSE

Chapter 5
Developing Linear Algebra Codes on Modern Processors: Emerging Research and Opportunities
A library that contains a set of basic linear algebra subroutines used for handling sparse matrices on GPUs. It is developed in NVIDIA CUDA and it is designed to be called from C and C++ routines.
Published in Chapter:
Batched Computing
Copyright: © 2023 |Pages: 23
DOI: 10.4018/978-1-7998-7082-1.ch005
Abstract
This chapter presents the concept of batched computing, which consists of the division of a large problem into smaller portions and can be applied to both dense and sparse linear algebra. Two examples, general matrix-matrix multiplication (GEMM) and general triangular solver (GTSV), are used to present different approaches depending on the problem to solve. The GEMM example focuses on multi-core platforms, and it is also used to introduce the concept of auto-tunning. In the case of GTSV, the targeted device is a GPU. Moreover, given that this is a sparse operation, an analysis of the data layout is presented to see the impact of this aspect.
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