Abstract
DNA methylation analysis has become an important topic in the study of human health. In previous work, we developed a suite of tools to perform this analysis. It includes HPG-Dhunter, a web-based tool for automatic detection of differentially methylated regions (DMRs) between different samples. The back-end of that tool receives an undefined number of simultaneous requests to detect DMRs on different datasets. Currently, simultaneous requests are queued and processed one at a time. This paper proposes a parallel architecture where multiple daemons serve requests simultaneously. Daemons can also share the same physical GPUs. A scheduler manages requests and forwards them to daemons. The number of daemons per GPU is configurable, thus adapting the architecture to the available hardware. Results show that the proposed parallel architecture hugely reduces the execution time. Furthermore, the speedup increases proportionally to the number of available GPUs (up to 7.47x in our experimental setup).
| Original language | English |
|---|---|
| Journal | Journal of Supercomputing |
| Early online date | 06 Mar 2024 |
| DOIs | |
| Publication status | Early online date - 06 Mar 2024 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© The Author(s) 2024.
Keywords
- DNA methylation analysis
- GPU computing
- Software as a service
ASJC Scopus subject areas
- Theoretical Computer Science
- Software
- Information Systems
- Hardware and Architecture
Access to Document
- Accelerating the detection of DNA differentially methylated regions using multiple GPUs
Copyright 2024 the authors. This is an open access article published under a Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.