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Surviving the Life Sciences Data Deluge using Cray Supercomputers
| Content Provider | Semantic Scholar |
|---|---|
| Author | Rekepalli, Bhanu Giblock, Paul |
| Copyright Year | 2013 |
| Abstract | The growing deluge of data in the Life Science domains threatens to overwhelm computing architectures. This persistent trend necessitates the development of effective and user-friendly computational components for rapid data analysis and knowledge discovery. Bioinformatics, in particular, employs data-intensive applications driven by novel DNA sequencing technologies, as do the high-throughput approaches that complement proteomics, genomics, metabolomics, and metagenomics. We are developing massively parallel applications to analyze this rising flood of life sciences data for large scale knowledge discovery. We have chosen to work with the desktop or cluster based applications most widely used by the scientific community, such as NCBI BLAST, HMMER, and MUSCLE. Our endeavors encompasses extending highly scalable parallel applications that scale to tens of thousands of cores on Cray’s XT architecture to Cray’s next generation XE and XC architectures along with focusing on making them robust and optimized, which will be discussed in this paper. Keywords-Benchmarking; Bioinformatics; HPC; |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://cug.org/proceedings/cug2013_proceedings/includes/files/pap166.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
