Exploring Memory Access Patterns for Graph Processing Accelerators
Published in arXiv (Cornell University) • Oct 26, 2020
NobleIDNI6P71W14R18S02
Authors:,,
Jonas Dann
Daniel Ritter
Holger Fröning
Abstract
Recent trends in business and technology (e.g., machine learning, social network analysis) benefit from storing and processing growing amounts of graph-structured data in databases and data science platforms. FPGAs as accelerators for graph processing with a customizable memory hierarchy promise sol...
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