URI | http://purl.tuc.gr/dl/dias/D0548287-BD72-4A1B-A12F-40FE85519E32 | - |
Identifier | https://doi.org/10.1109/MM.2021.3075848 | - |
Identifier | https://ieeexplore.ieee.org/document/9416903 | - |
Language | en | - |
Extent | 7 pages | en |
Title | Accelerating phylogenetics using FPGAs in the cloud | en |
Creator | Alachiotis Nikolaos | en |
Creator | Brokalakis Andreas | en |
Creator | Μπροκαλακης Ανδρεας | el |
Creator | Amourgianos-Lorentzos Vasileios | en |
Creator | Αμουργιανος-Λορεντζος Βασιλειος | el |
Creator | Ioannidis Sotirios | en |
Creator | Ιωαννιδης Σωτηριος | el |
Creator | Malakonakis Pavlos | en |
Creator | Μαλακωνακης Παυλος | el |
Creator | Bokalidis Anastasios | en |
Creator | Μποκαλιδης Αναστασιος | el |
Publisher | Institute of Electrical and Electronics Engineers | en |
Content Summary | Phylogenetics study the evolutionary history of organisms using an iterative process of creating and evaluating phylogenetic trees. This process is very computationally intensive; constructing a large phylogenetic tree requires hundreds to thousands of CPU hours. In this article, we describe an FPGA-based system that can be deployed on AWS EC2 F1 cloud instances to accelerate phylogenetic analyses by boosting performance of the phylogenetic likelihood function, i.e., a widely employed tree-evaluation function that accounts for up to 95% of the overall analysis time. We exploit domain-specific knowledge to reduce the amount of transferred data that limits overall system performance. Our proof-of-concept implementation reveals that the effective accelerator throughput nearly quadruples with optimized data movement, reaching up to 75% of its theoretical peak and nearly 10× faster processing than a CPU using AVX2 extensions. | en |
Type of Item | Peer-Reviewed Journal Publication | en |
Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
License | http://creativecommons.org/licenses/by/4.0/ | en |
Date of Item | 2022-11-01 | - |
Date of Publication | 2021 | - |
Subject | Phylogeny | en |
Subject | Topology | en |
Subject | Central Processing Unit | en |
Subject | Mathematical model | en |
Subject | Probability | en |
Subject | Field programmable gate arrays | en |
Bibliographic Citation | N. Alachiotis, A. Brokalakis, V. Amourgianos, S. Ioannidis, P. Malakonakis and T. Bokalidis, "Accelerating phylogenetics using FPGAs in the cloud," IEEE Micro, vol. 41, no. 4, pp. 24-30, 1 July-Aug. 2021, doi: 10.1109/MM.2021.3075848. | en |