Name
Title | ||
|---|---|---|
Power-Efficient Accelerated Genomic Short Read Mapping on Heterogeneous Computing Platforms |
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/FCCM.2016.17 | 2016 IEEE 24th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM) |
Keywords | Field | DocType |
FPGA,power-efficiency,read mapping | Electrical efficiency,Algorithm design,Data mapping,Computer science,Parallel computing,Symmetric multiprocessor system,Field-programmable gate array,Real-time computing,Reconfigurable computing,Joule,Speedup | Conference |
ISBN | Citations | PageRank |
978-1-5090-2357-8 | 1 | 0.37 |
References | Authors | |
3 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ernst Houtgast | 1 | 44 | 6.04 |
| Vlad Mihai Sima | 2 | 58 | 8.08 |
| Giacomo Marchiori | 3 | 2 | 0.77 |
| Koen Bertels | 4 | 1365 | 138.66 |
| Zaid Al-Ars | 5 | 560 | 78.62 |