ReSMA: Accelerating Approximate String Matching Using ReRAM-based Content Addressable Memory
TimeThursday, July 14th11:15am - 11:37am PDT
Location3002, Level 3
Event Type
Research Manuscript
In-memory and Near-memory Computing
DescriptionIn this paper, we present a novel ASM processing-in-memory accelerator, namely
ReSMA, based on ReRAM-based content addressable memory
(ReCAM) arrays. We develop a novel ReCAM-friendly filter-andfiltering
algorithm to process the q-grams filtering in ReCAM
memory. We also design the new data mapping and a new
verification algorithm, which enables computing the edit distances
totally in ReRAM crossbars for energy saving. Experimental
results show that ReSMA outperforms the CPU, GPU, FPGA,
ASIC, and PIM based solutions by 268.7