Análise de viabilidade de ferramenta para correção híbrida de sequências genômicas em ambiente de memória compartilhada com FPGA
Abstract
Genome analysis comprises extensive researches, that focus on diseases and their treatments. Supporting such activities, researchers handle computational tools to assemble genomes. This work presents a feasibility analysis of a tool for hybrid correction of genomic sequences; a necessary step for genome assembly. An architecture for heterogeneous environments is proposed, and its implementation is made with a CPU and an FPGA board. The results obtained from the theoretical and practical data survey indicate that the implementation with the hardware accelerator has performance gains of up to 19 times over the sequential version, and may increase depending on the communication technology used.
References
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Del Angel, V. D., Hjerde, E., Sterck, L., Capella-Gutierrez, S., Notredame, C., Pettersson, O. V., Amselem, J., Bouri, L., Bocs, S., Klopp, C., et al. (2018). Ten steps to get started in genome assembly and annotation. F1000Research, 7.
Goodwin, S., McPherson, J. D., and McCombie, W. R. (2016). Coming of age: ten years of next-generation sequencing technologies. Nature Reviews Genetics, 17(6):333.
Hu, Y. and Georgiou, P. (2015). A real-time de novo dna sequencing assembly platform based on an fpga implementation. IEEE/ACM transactions on computational biology and bioinformatics, 13(2):291–300.
Koren, S., Walenz, B. P., Berlin, K., Miller, J. R., Bergman, N. H., and Phillippy, A. M. (2017). Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome research, 27(5):722–736.
Mahram, A. and Herbordt, M. C. (2012). Fmsa: Fpga-accelerated clustalw-based multiple sequence alignment through pipelined prefiltering. In 2012 IEEE 20th International Symposium on Field-Programmable Custom Computing Machines, pages 177–183.
Ramachandran, A., Heo, Y., Hwu, W., Ma, J., and Chen, D. (2015). Fpga accelerated dna error correction. In 2015 Design, Automation Test in Europe Conference Exhibition (DATE), pages 1371–1376.
Salmela, L. and Rivals, E. (2014). Lordec: accurate and efficient long read error correction. Bioinformatics, 30(24):3506–3514.
Varma, B. S. C., Paul, K., Balakrishnan, M., and Lavenier, D. (2013). Fassem: Fpga based acceleration of de novo genome assembly. In 2013 IEEE 21st Annual International Symposium on Field-Programmable Custom Computing Machines, pages 173–176.
Published
2019-11-08
How to Cite
ALMEIDA, Felipe; SATO, Liria; MIDORIKAWA, Edson.
Análise de viabilidade de ferramenta para correção híbrida de sequências genômicas em ambiente de memória compartilhada com FPGA. In: SYMPOSIUM ON HIGH PERFORMANCE COMPUTING SYSTEMS (SSCAD), 20. , 2019, Campo Grande.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 430-437.
DOI: https://doi.org/10.5753/wscad.2019.8688.
