Parallel stochastic systems biology in the cloud

被引:6
|
作者
Aldinucci, Marco [1 ,2 ,3 ]
Torquati, Massimo [4 ]
Spampinato, Concetto [5 ]
Drocco, Maurizio [6 ]
Misale, Claudia
Calcagno, Cristina
Coppo, Mario [1 ,7 ]
机构
[1] Univ Turin, Dept Comp Sci, I-10149 Turin, Italy
[2] Univ Pisa, I-56100 Pisa, Italy
[3] Italian Natl Res Agcy, Rome, Italy
[4] Univ Pisa, Dept Comp Sci, I-56100 Pisa, Italy
[5] Univ Catania, I-95124 Catania, Italy
[6] Univ Turin, I-10149 Turin, Italy
[7] Dept Comp Sci, Oxford, England
关键词
stochastic simulation; cloud; multi-core; distributed computing; parallel patterns; SIMULATION; ENVIRONMENT; MAPREDUCE; SOFTWARE; CALCULUS; MODELS;
D O I
10.1093/bib/bbt040
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The stochastic modelling of biological systems, coupled with Monte Carlo simulation of models, is an increasingly popular technique in bioinformatics. The simulation-analysis workflow may result computationally expensive reducing the interactivity required in the model tuning. In this work, we advocate the high-level software design as a vehicle for building efficient and portable parallel simulators for the cloud. In particular, the Calculus of Wrapped Components (CWC) simulator for systems biology, which is designed according to the FastFlow pattern-based approach, is presented and discussed. Thanks to the FastFlow framework, the CWC simulator is designed as a high-level workflow that can simulate CWC models, merge simulation results and statistically analyse them in a single parallel workflow in the cloud. To improve interactivity, successive phases are pipelined in such a way that the workflow begins to output a stream of analysis results immediately after simulation is started. Performance and effectiveness of the CWC simulator are validated on the Amazon Elastic Compute Cloud.
引用
收藏
页码:798 / 813
页数:16
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