Name
Abstract | ||
|---|---|---|
In the analysis of next-generation DNA sequencing data, Hidden Markov Models (HMMs) are used to perform variant calling between DNA sequences and a reference genome. The PairHMM model is solved by the Forward Algorithm, for which the performance and power efficiency can be increased tremendously using systolic arrays (SAs) in FPGAs. We model the performance characteristics of such SAs, and propose a novel architecture that allows the computational units to continuously perform useful work on the input data. The implementation achieves up to 90% of the theoretical throughput for a real dataset. The implementation of the proposed architecture achieves more than 2.5x throughput over the state-of-the-art on a similar contemporary platform. |
Year | Venue | Keywords |
|---|---|---|
2016 | 2016 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM) | High-Throughput Sequencing, GATK, Haplotype-Caller, PairHMM, Systolic Array, FPGA |
Field | DocType | ISSN |
Electrical efficiency,Algorithm design,Forward algorithm,Computer science,Field-programmable gate array,Systolic array,Throughput,Bioinformatics,Hidden Markov model,Reference genome | Conference | 2156-1125 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Johan Peltenburg | 1 | 2 | 3.15 |
| Shanshan Ren | 2 | 11 | 3.05 |
| Zaid Al-Ars | 3 | 560 | 78.62 |