DNA Mapping using Processor-in-Memory Architecture

Dominique Lavenier (1) , Jean-Francois Roy (2) , David Furodet (2)

1 GenScale - Scalable, Optimized and Parallel Algorithms for Genomics
2 UPMEM SAS [Grenoble]

This paper presents the implementation of a mapping algorithm on a new Processing-in-Memory (PIM) architecture developed by UPMEM Company. UPMEM's solution consists in adding processing units into the DRAM, to minimize data access time and maximize bandwidth, in order to drastically accelerate data-consuming algorithms. The technology developed by UPMEM makes it possible to combine 256 cores with 16 GBytes of DRAM, on a standard DIMM module. An experimentation of DNA Mapping on Human genome dataset shows that a speed-up of 25 can be obtained with UPMEM technology compared to fast mapping software such as BWA, Bowtie2 or NextGenMap running on 16 Intel threads. Experimentation also highlight that data transfer from storage device limits the performances of the implementation. The use of SSD drives can boost the speed-up to 80.

Mots clés: mapping; processing-in-memory; PIM; bioinformatics; genomic; I/O disk bandwidth; hardware accelerator

Domaines: Architectures Matérielles [cs.AR]; Bio-informatique [q-bio.QM]

Dominique Lavenier, Jean-Francois Roy, David Furodet. DNA Mapping using Processor-in-Memory Architecture. Workshop on Accelerator-Enabled Algorithms and Applications in Bioinformatics, Dec 2016, Shenzhen, China. ⟨hal-01399997⟩