PANDA: Processing in Magnetic Random-Access Memory-Accelerated de Bruijn Graph-Based DNA Assembly

In this work, we present an efficient Processing in MRAM-Accelerated De Bruijn Graph-based DNA Assembly platform, named PANDA, based on an optimized and hardware-friendly genome assembly algorithm. PANDA is able to assemble large-scale DNA sequence datasets from all-pair overlaps. We first design a PANDA platform that exploits MRAM as computational memory and converts it to a potent processing unit for genome assembly. PANDA can not only execute efficient bulk bit-wise X(N)OR-based comparison/addition operations heavily required for the genome assembly task but also a full set of 2-/3-input logic operations inside the MRAM chip. We then develop a highly parallel and step-by-step hardware-friendly DNA assembly algorithm for PANDA that only requires the developed in-memory logic operations. The platform is then configured with a novel data partitioning and mapping technique that provides local storage and processing to utilize the algorithm level’s parallelism fully. The cross-layer simulation results demonstrate that PANDA reduces the run time and power by a factor of 18 and 11, respectively, compared with CPU. Moreover, speed-ups of up to 2.5 to 10× can be obtained over other recent processing in-memory platforms to perform the same task, like STT-MRAM, ReRAM, and DRAM.