FSpGEMM: A Framework for Accelerating Sparse General Matrix-Matrix Multiplication Using Gustavson's Algorithm on FPGAs

General sparse matrix-matrix multiplication (SpGEMM) is integral to many high-performance computing (HPC) and machine learning applications. However, prior field-programmable gate array (FPGA)-based SpGEMM accelerators either use the inner product algorithm with wasted and costly operations or Gusta...

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Vydáno v:	IEEE transactions on very large scale integration (VLSI) systems Ročník 32; číslo 4; s. 1 - 0
Hlavní autoři:	Tavakoli, Erfan Bank, Riera, Michael, Quraishi, Masudul Hassan, Ren, Fengbo
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.04.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Benchmarks Computer architecture Computer memory Embedded systems Field programmable gate arrays Field-programmable gate array (FPGA) Format general sparse matrix–matrix multiplication (SpGEMM) Graphics processing units Gustavson’s algorithm Hardware Indexes Machine learning Mathematical analysis Matrix algebra Matrix converters Memory management Multiplication Network latency OpenCL Performance enhancement Preprocessing reconfigurable computing Resource utilization Sparse matrices Sparsity
ISSN:	1063-8210, 1557-9999
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