Abstract
Pairwise sequence alignment is an important application to identify regions of similarity that may indicate the relationship between two biological sequences. This is a computationally intensive task that usually requires parallel processing to provide realistic execution times. This work introduces a new framework for a deadline constrained application of sequence alignment, called MASA-CUDAlign, that exploits cloud computing with Spot GPU instances. Although much cheaper than On-Demand instances, Spot GPUs can be revoked at any time, so the framework is also able to restart MASA-CUDAlign from a checkpoint in a new instance when a revocation occurs. We evaluate the proposed framework considering five pairs of DNA sequences and different AWS instances. Our results show that the framework reduces financial costs when compared to On-Demand GPU instances while meeting the deadlines even in scenarios with several instances revocations.
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Acknowledgments
This research is supported by project CNPq/AWS 440014/2020-4, Brazil, by the Programa Institucional de Internacionalização (PrInt) from CAPES (process number 88887.310261/2018-00) and by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (process 145088/2019-7).
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Brum, R.C., Sousa, W.P., Melo, A.C.M.A., Bentes, C., de Castro, M.C.S., Drummond, L.M.d.A. (2021). A Fault Tolerant and Deadline Constrained Sequence Alignment Application on Cloud-Based Spot GPU Instances. In: Sousa, L., Roma, N., Tomás, P. (eds) Euro-Par 2021: Parallel Processing. Euro-Par 2021. Lecture Notes in Computer Science(), vol 12820. Springer, Cham. https://doi.org/10.1007/978-3-030-85665-6_20
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