bowtie-bwa:ff:multicore:biomed:14 (Article)
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Author(s) | Claudia Misale, Giulio Ferrero, Massimo Torquati and Marco Aldinucci |
Title | « Sequence alignment tools: one parallel pattern to rule them all? » |
Journal | BioMed Research International |
Year | 2014 |
URL | http://downloads.hindawi.com/journals/bmri/2014/539410.pdf |
Abstract & Keywords |
In this paper we advocate high-level programming methodology for Next Generation Sequencers (NGS) alignment tools for both productivity and absolute performance. We analyse the problem of parallel alignment and review the parallelisation strategies of the most popular alignment tools, which can all be abstracted to a single parallel paradigm. We compare these tools against their porting onto the FastFlow pattern-based programming framework, which provides programmers with high-level parallel patterns. By using a high-level approach, programmers are liberated from all complex aspects of parallel programming, such as synchronisation protocols and task scheduling, gaining more possibility for seamless performance tuning. In this work we show some use case in which, by using a high-level approach for parallelising NGS tools, it is possible to obtain comparable or even better absolute performance for all used datasets.
Keywords: fastflow,bioinformatics
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@article{bowtie-bwa:ff:multicore:biomed:14,
keywords = {fastflow,bioinformatics},
url = {http://downloads.hindawi.com/journals/bmri/2014/539410.pdf},
title = {Sequence alignment tools: one parallel pattern to rule them all?},
author = {Claudia Misale and Giulio Ferrero and Massimo Torquati and Marco
Aldinucci},
abstract = {In this paper we advocate high-level programming methodology for
Next Generation Sequencers (NGS) alignment tools for both
productivity and absolute performance. We analyse the problem of
parallel alignment and review the parallelisation strategies of
the most popular alignment tools, which can all be abstracted to a
single parallel paradigm. We compare these tools against their
porting onto the FastFlow pattern-based programming framework,
which provides programmers with high-level parallel patterns. By
using a high-level approach, programmers are liberated from all
complex aspects of parallel programming, such as synchronisation
protocols and task scheduling, gaining more possibility for
seamless performance tuning. In this work we show some use case in
which, by using a high-level approach for parallelising NGS tools,
it is possible to obtain comparable or even better absolute
performance for all used datasets. },
year = {2014},
journal = {BioMed Research International},
}
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