Power-Efficient Accelerated Genomic Short Read Mapping on Heterogeneous Computing Platforms

Abstract (2016)
Author(s)

Ernst Joachim Houtgast (Bluebee, Delft, TU Delft - Computer Engineering)

V.M. Sima (TU Delft - Computer Engineering, Bluebee, Delft)

Giacomo Marchiori (Bluebee, Delft)

KLM Bertels (TU Delft - Quantum & Computer Engineering, TU Delft - FTQC/Bertels Lab)

Z. Al-Ars (TU Delft - Computer Engineering)

Research Group
Computer Engineering
DOI related publication
https://doi.org/10.1109/FCCM.2016.17
More Info
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Publication Year
2016
Language
English
Research Group
Computer Engineering
Pages (from-to)
1-1

Abstract

We propose a novel FPGA-accelerated BWA-MEM implementation, a popular tool for genomic data mapping. The performance and power-efficiency of the FPGA implementation on the single Xilinx Virtex-7 Alpha Data add-in card is compared
against a software-only baseline system. By offloading the Seed Extension phase onto the FPGA, a two-fold speedup in overall application-level performance is achieved and a 1.6x gain in power-efficiency. To facilitate platform and tool-agnostic comparisons, the base pairs per Joule unit is introduced as a measure of power-efficiency. The FPGA design is able to map up to 34 thousand base pairs per Joule.

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