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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Walters, J.P. Darole, R. Chaudhary, V. |
| Copyright Year | 2009 |
| Description | Author affiliation: Department of Computer Science and Engineering, University at Buffalo, The State University of New York, USA (Walters, J.P.; Darole, R.; Chaudhary, V.) |
| Abstract | We present PIO-HMMER, an enhanced version of MPI-HMMER. PIO-HMMER improves on MPI-HMMER's scalability through the use of parallel I/O and a parallel file system. In addition, we describe several enhancements, including a new load balancing scheme, enhanced post-processing, improved double-buffering support, and asynchronous I/O for returning scores to the master node. Our enhancements to the core HMMER search tools, hmmsearch and hmmpfam, allow for scalability up to 256 nodes where MPI-HMMER previously did not scale beyond 64 nodes. We show that our performance enhancements allow hmmsearch to achieve between 48× and 221× speedup using 256 nodes, depending on the size of the input HMM and the database. Further, we show that by integrating database caching with PIO-HMMER's hmmpfam tool we can achieve up to 328× performance using only 256 nodes. |
| Starting Page | 1 |
| Ending Page | 11 |
| File Size | 603248 |
| Page Count | 11 |
| File Format | |
| ISBN | 9781424437511 |
| ISSN | 15302075 |
| DOI | 10.1109/IPDPS.2009.5161074 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-05-23 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Scalability Hidden Markov models Databases File systems Message passing Computer science Load management Concurrent computing Acceleration Moore's Law |
| Content Type | Text |
| Resource Type | Article |
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