Na Bai, Shanjiang Tang*, Ce Yu*, Hao Fu , Chen Wang and Xi Chen
In recent years, the rapid growth of biological datasets in bioinformatics has made the computation of multiple sequence alignment (MSA) become extremely slow. Using the GPU to accelerate MSA has shown to be an effective approach. Moreover, there is a trend that many bioinformatic researchers or institutes setup a shared server for remote users to submit MSA jobs via provided web-pages or tools. Given the fact that different MSA jobs submitted by users often process similar datasets, there can be an opportunity for users to share their computation results between each other, which can avoid the redundant computation and thereby reduce the overall computing time. Furthermore, in the heterogeneous CPU/GPU platform, many existing applications assign their computation on GPU devices only, which leads to a waste of the CPU resources. Co-run computation can be made use of to increase the utilization of computing resources on both CPUs and GPUs by dispatching workloads onto them simultaneously. In this paper, we propose an efficient MSA system called GMSA for multi-users on shared heterogeneous CPU/GPU platforms. To accelerate the computation of jobs from multiple users, data sharing is considered in GMSA due to the fact that different MSA jobs often have a percentage of same data and tasks. Additionally, We also propose a scheduling strategy based on the similarity in datasets or tasks between MSA jobs. Furthermore, co-run computation model is adopted to fully utilize both CPUs and GPUs. Experiments results showed that GMSA can achieve a speedup of up to 32X.
Multiple Sequence Alignment (MSA), Multiple Users, Data Sharing, Heterogeneous CPU/GPU, Co-run, Pairwise AlignmentMultiple Sequence Alignment (MSA), Pairwise Alignments
College of Intelligence and Computing, Tianjin University, Tianjin, College of Intelligence and Computing, Tianjin University, Tianjin, College of Intelligence and Computing, Tianjin University, Tianjin, College of Intelligence and Computing, Tianjin University, Tianjin, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, College of Intelligence and Computing, Tianjin University, Tianjin