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CoSPARSE: A Software and Hardware Reconfigurable SpMV Framework for Graph Analytics
2021
2021 58th ACM/IEEE Design Automation Conference (DAC)
Sparse matrix-vector multiplication (SpMV) is a critical building block for iterative graph analytics algorithms. Typically, such algorithms have a varying active vertex set across iterations. This variablity has been used to improve performance by either dynamically switching algorithms between iterations (software) or designing custom accelerators (hardware) for graph analytics algorithms. In this work, we propose a novel framework, CoSPARSE, that employs hardware and software reconfiguration
doi:10.1109/dac18074.2021.9586114
fatcat:pukdkrjnyndtpcnwyusebclpjm