Abstract
Due to its high-throughput and low cost, Next Generation Sequencing (NGS) technology is becoming increasingly popular in many genomics research labs. However, handling the massive raw data generated by the NGS platforms poses a significant computational challenge to genomics analysis tools. This paper presents a GPU acceleration of the GATK HaplotypeCaller (GATK HC), a widely used DNA variant caller in the clinic. Moreover, this paper proposes a load-balanced multi-process optimization of GATK HaplotypeCaller to address its implementation limitation which forces the sequential execution of the program and prevents effective utilization of hardware acceleration. In single-threaded mode, the GPU-based GATK HC is 1.71x and 1.21x faster than the baseline HC implementation and the vectorized GATK HC implementation, respectively. Moreover, the GPU-based implementation achieves up to 2.04x and 1.40x speedup in load-balanced multi-process mode over the baseline implementation and the vectorized GATK HC implementation in non-load-balanced multi-process mode, respectively.
| Original language | English |
|---|---|
| Title of host publication | 2017 IEEE 17th International Conference on BioInformatics and BioEngineering (BIBE) |
| Place of Publication | Piscataway |
| Publisher | IEEE |
| Pages | 497-502 |
| Number of pages | 6 |
| ISBN (Electronic) | 978-1-5386-1324-5 |
| ISBN (Print) | 978-1-5386-1325-2 |
| DOIs | |
| Publication status | Published - 2017 |
| Event | BIBE 2017: 17th IEEE International Conference on BioInformatics and BioEngineering - Washington DC, United States Duration: 23 Oct 2017 → 25 Oct 2017 http://bibe2017.com/index.html |
Conference
| Conference | BIBE 2017 |
|---|---|
| Abbreviated title | BIBE 2017 |
| Country/Territory | United States |
| City | Washington DC |
| Period | 23/10/17 → 25/10/17 |
| Internet address |
Keywords
- Bioinformatics
- Genomics
- Graphics processing units
- Acceleration
- DNA
- Optimization
- Sequential analysis