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Spurred by widening gap between data processing speed and data communicationspeed in Von-Neumann computing architectures, some bioinformatic applicationshave harnessed the computational power of Processing-in-Memory (PIM) platforms.However, the performance of PIMs unavoidably diminishes when dealing with suchcomplex applications seeking bulk bit-wise comparison or addition operations.In this work, we present an efficient Processing-in-MRAM Accelerated De BruijnGraph based DNA Assembly platform named PANDA based on an optimized andhardware-friendly genome assembly algorithm. PANDA is able to assemblelarge-scale DNA sequence data-set from all-pair overlaps. We first design PANDAplatform that exploits MRAM as a computational memory and converts it to apotent processing unit for genome assembly. PANDA can execute not onlyefficient bulk bit-wise X(N)OR-based comparison/addition operations heavilyrequired for the genome assembly task but a full-set of 2-/3-input logicoperations inside MRAM chip. We then develop a highly parallel and step-by-stephardware-friendly DNA assembly algorithm for PANDA that only requires thedeveloped in-memory logic operations. The platform is then configured with anovel data partitioning and mapping technique that provides local storage andprocessing to fully utilize the algorithm-level's parallelism. The cross-layersimulation results demonstrate that PANDA reduces the run time and power,respectively, by a factor of 18 and 11 compared with CPU. Besides, speed-ups ofup-to 2-4x can be obtained over recent processing-in-MRAM platforms to performthe same task.

PANDA: Processing-in-MRAM Accelerated De Bruijn Graph based DNA Assembly