Accelerating Phylogenetics Using FPGAs in the Cloud
Accelerating Phylogenetics Using FPGAs in the Cloud
复制标题
在云中使用 FPGA 加速系统发育
DOI：
10.1109/mm.2021.3075848
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发表时间：
2021
期刊：
影响因子：
3.6
通讯作者：
Tasos Bokalidis
中科院分区：
文献类型：
--
作者：
Nikolaos S. Alachiotis;A. Brokalakis;Vasilis Amourgianos;S. Ioannidis;P. Malakonakis;Tasos Bokalidis
系统发育学研究生物的进化历史，用于创建和评估系统发育的过程。可以通过提高系统发育可能性函数的性能，将其部署在AWS EC2 F1云实例上，以加速系统发育分析。也就是说，占整体分析时间的95％的广泛使用的树木评估功能。有效的加速器吞吐量几乎具有优化的数据移动，比使用AVX2扩展的CPU，其理论峰值的75％和几乎更快的处理。
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.