VCSR: An Efficient GPU Memory-Aware Sparse Format-Reference-Cited by-同舟云学术

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VCSR: An Efficient GPU Memory-Aware Sparse Format

Published:2022-12-01 Issue:12 Volume:33 Page:3977-3989
ISSN:1045-9219
Container-title:IEEE Transactions on Parallel and Distributed Systems
language:
Short-container-title:IEEE Trans. Parallel Distrib. Syst.

Author:

Karimi Elmira¹^ORCID,Agostini Nicolas Bohm¹,Dong Shi¹^ORCID,Kaeli David¹^ORCID

Affiliation:

1. ECE Department, Northeastern University, Boston, MA, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/71/9790018/09787804.pdf?arnumber=9787804

Reference40 articles.

2. A complete key recovery timing attack on a GPU

3. Sparse matrix vector processing formats;stathis,2004

4. A sparse matrix library in C$++$++ for high performance architectures;dongarraxz;Proc 2nd Object Oriented Numerics Conf,1994

5. SPARSKIT: A basic toolkit for sparse matrix computations;saad;NASA Tech Rep Server,1990

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3. Sparse Stream Semantic Registers: A Lightweight ISA Extension Accelerating General Sparse Linear Algebra;IEEE Transactions on Parallel and Distributed Systems;2023-12

4. HASpMV: Heterogeneity-Aware Sparse Matrix-Vector Multiplication on Modern Asymmetric Multicore Processors;2023 IEEE International Conference on Cluster Computing (CLUSTER);2023-10-31

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