PMG: Multi-core Metabolite Identification

Mohammad Mahdi Jaghoori (1, 2) , Sung-Shik T.Q. Jongmans (2) , Frank de Boer (2) , Julio Peironcely (3) , Jean-Loup Faulon (4, 5) , Theo Reijmers (3) , Thomas Hankemeier (3)

1 AMC - Academic Medical Center - Academisch Medisch Centrum [Amsterdam]
2 CWI - Centrum Wiskunde & Informatica
3 LACDR - Leiden Academic Centre for Drug Research
4 ISSB - Institut de biologie systémique et synthétique
5 CNRS - Centre National de la Recherche Scientifique

Distributed computing has been considered for decades as a promising way of speeding up software execution, resulting in a valuable collection of safe and efficient concurrent algorithms. With the pervasion of multi-core processors, parallelization has moved to the center of attention with new challenges, especially regarding scalability to tens or even hundreds of parallel cores. In this paper, we present a scalable multi-core tool for the metabolomics community. This tool addresses the problem of metabolite identification which is currently a bottleneck in metabolomics pipeline.

Mots clés: multi-core; Java concurrency; fork-join; scalability; metabolomics

Domaines: Sciences du Vivant [q-bio]

Mohammad Mahdi Jaghoori, Sung-Shik T.Q. Jongmans, Frank de Boer, Julio Peironcely, Jean-Loup Faulon, et al.. PMG: Multi-core Metabolite Identification. Electronic Notes in Theoretical Computer Science, 2013, 299, pp.53-60. ⟨10.1016/j.entcs.2013.11.005⟩. ⟨hal-01601690⟩