Name
Abstract | ||
|---|---|---|
The ability to rapidly identify a given protein from small subsamples (i.e. peptides) is at the basis of fundamental applications in the medical field. At the basis of protein identification we have a string matching problem which is computational intensive if we consider that the complexity of the algorithm scales with the length of the string and the number of sweeps of the database that are needed. In this paper we present an improvement for the FPGA-based string matching solution available in the literature improving the amount of parallelism exploited by the solution achieving a 1.63× reduction of the energy needed for the task over the literature and a 5.75× reduction when compared with high-end workstation. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IPDPSW.2016.170 | 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) |
Keywords | Field | DocType |
parallel protein identification,FPGA-based solution,medical field,string matching,parallelism | String searching algorithm,Protein identification,Computer science,Parallel computing,Workstation,Field-programmable gate array,Software | Conference |
ISSN | ISBN | Citations |
2164-7062 | 978-1-5090-3683-7 | 0 |
PageRank | References | Authors |
0.34 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fabiola Casasopra | 1 | 1 | 0.73 |
| Gea Bianchi | 2 | 0 | 0.34 |
| Gianluca C. Durelli | 3 | 21 | 3.86 |
| Marco D. Santambrogio | 4 | 771 | 91.15 |