NDLI: Many-core CPUs can deliver scalable performance to stochastic simulations of large-scale biochemical reaction networks

Content Provider	IEEE Xplore Digital Library
Author	Kouskoumvekakis, E. Soudris, D. Manolakos, E.S.
Copyright Year	2015
Description	Author affiliation: Dept. of Inf. & Telecommun., Univ. of Athens, Athens, Greece (Kouskoumvekakis, E.; Manolakos, E.S.) \|\| Sch. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Athens, Greece (Soudris, D.)
Abstract	Stochastic simulation of large-scale biochemical reaction networks is becoming essential for Systems Biology. It enables the in-silico investigation of complex biological system dynamics under different conditions and intervention strategies, while also taking into account the inherent “biological noise” especially present in the low species count regime. It is however a great computational challenge since in practice we need to execute many repetitions of a complex simulation model to assess the average and extreme cases behavior of the dynamical system it represents. The problem's work scales quickly, with the number of repetitions required and the number of reactions in the bio-model. The worst case scenario s when there is a need to run thousands of repetitions of a complex model with thousands of reactions. We have developed a stochastic simulation software framework for many- and multi-core CPUs. It is evaluated using Intel's experimental many-cores Single-chip Cloud Computer (SCC) CPU and the latest generation consumer grade Core i7 multi-core Intel CPU, when running Gillespie's First Reaction Method exact stochastic simulation algorithm. It is shown that emerging many-core NoC processors can provide scalable performance achieving linear speedup as simulation work scales in both dimensions.
Starting Page	517
Ending Page	524
File Size	999985
Page Count	8
File Format	PDF
ISBN	9781467378123
e-ISBN	9781467378130
DOI	10.1109/HPCSim.2015.7237084
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-20
Publisher Place	Netherlands
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Biochemical reaction networks Multicore processing Biological system modeling Computational modeling Stochastic processes Parallel algorithms Program processors Stochastic simulation algorithms First Reaction Method Many-core processors Hardware Intel SCC Networks on Chip
Content Type	Text
Resource Type	Article

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