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Considerations in using OpenCL on GPUs and FPGAs for throughput-oriented genomics workloads

Author
Cadenelli, N.; Jaksic, Z.; Polo, J.; Carrera, D.
Type of activity
Journal article
Journal
Future generation computer systems
Date of publication
2019-05
Volume
94
First page
148
Last page
159
DOI
https://doi.org/10.1016/j.future.2018.11.028 Open in new window
Project funding
Computación de Altas Prestaciones VII
HiEST: Holistic Integration of Emerging Supercomputing Technologies
Models de Programacio i Entorns d'eXecució PARal.lels
Repository
http://hdl.handle.net/2117/126685 Open in new window
URL
https://www.sciencedirect.com/science/article/pii/S0167739X18314183 Open in new window
Abstract
The recent upsurge in the available amount of health data and the advances in next-generation sequencing are setting the ground for the long-awaited precision medicine. To process this deluge of data, bioinformatics workloads are becoming more complex and more computationally demanding. For this reasons they have been extended to support different computing architectures, such as GPUs and FPGAs, to leverage the form of parallelism typical of each of such architectures. The paper describes how a ...
Citation
Cadenelli, N., Jaksic, Z., Polo, J., Carrera, D. Considerations in using OpenCL on GPUs and FPGAs for throughput-oriented genomics workloads. "Future generation computer systems", Maig 2019, vol. 94, p. 148-159.
Keywords
Energy-to-solution, FPGAs, GPUs, K-mer, OpenCL
Group of research
CAP - High Performace Computing Group

Participants

  • Cadenelli, Nicola  (author)
  • Jaksic, Zoran  (author)
  • Polo Bardés, Jorda  (author)
  • Carrera Perez, David  (author)

Attachments