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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jing Zhang Heshan Lin Balaji, P. Wu-Chun Feng |
| Copyright Year | 2013 |
| Abstract | Computational biology sequence alignment tools using the Burrows-Wheeler Transform (BWT) are widely used in next-generation sequencing (NGS) analysis. However, despite extensive optimization efforts, the performance of these tools still cannot keep up with the explosive growth of sequencing data. Through an in-depth performance analysis of BWA, a popular BWT-based aligner on multicore architectures, we demonstrate that such tools are limited by memory bandwidth due to their irregular memory access patterns. We then propose a locality-aware implementation of BWA that aims at optimizing its performance by better exploiting the caching mechanisms of modern multicore processors. Experimental results show that our improved BWA implementation can reduce last-level cache (LLC) misses by 30% and translation look aside buffer (TLB) misses by 20%, resulting in up to 2.6-fold speedup over the original BWA implementation. |
| Starting Page | 377 |
| Ending Page | 384 |
| File Size | 326661 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781467364652 |
| e-ISBN | 9780769549965 |
| DOI | 10.1109/CCGrid.2013.67 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-05-13 |
| Publisher Place | Netherlands |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Bioinformatics Genomics Multicore processing Program processors Data structures Algorithm design and analysis Sequential analysis multicore short-read mapping Burrows-Wheeler transform FM-index bioinformatics data locality |
| Content Type | Text |
| Resource Type | Article |
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