Presentation
Eliminate control divergence in SpMV via in-SRAM reduction
DescriptionSpMV is a critical kernels in multiple application domains. The performance of SpMV on SIMD devices suffers from control divergences greatly. This paper proposes an In-SRAM Computing based SpMV optimization framework. We divide the SpMV into two stages: a compute-intensive and a control-intensive stage. The first stage has been efficently accelerated on most current SIMD devices. To optimize the second stage, we convert the control divergences to the memory divergences, and utilize the feature of multi-bank SRAM to eliminate the memory divergences' overheads. Experimental results indicate that our solution achieves significant performance speedups over the highly optimized vector SpMV kernels.
Event Type
Work-in-Progress Poster
TimeWednesday, June 265:00pm - 6:00pm PDT
LocationLevel 2 Lobby
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