Accelerating Phylogenetics Using FPGAs in the Cloud

Nikolaos Alachiotis, Andreas Brokalakis, Vasilis Amourgianos, Sotiris Ioannidis, Pavlos Malakonakis, Tasos Bokalidis

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

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.
Original languageEnglish
Article number9416903
Pages (from-to)24-30
Number of pages7
JournalIEEE micro
Volume41
Issue number4
Early online date27 Apr 2021
DOIs
Publication statusPublished - 1 Jul 2021

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