Biochemical simuflation and analysis play a significant role in systems biology research. Numerous software tools have been developed to serve this area. Using these tools for completing tasks, for example, stochastic simulation, parameter fitting and optimization, usually requires sufficient computational power to make the duration of completion acceptable. COPASI is one of the most powerful tools for quantitative simulation and analysis targeted at biological systems. It supports systems biology markup language and covers multiple categories of tasks. This work develops an open source package ParaCopasi for parallel COPASI tasks and investigates its performance regarding accelerations. ParaCopasi can be installed on platforms equipped with multicore CPU to exploit the cores, scaling from desktop computers to large scale high-performance computing clusters. More cores bring more performance. The results show that the parallel efficiency has a positive correlation with the total workload. The parallel efficiency reaches a level of at least 95% for both homogeneous and heterogenous tasks when computational workload is adequate. An example is illustrated by applicating this package in parameter estimation to calibrate a biochemical kinetics model.
Keywords: COPASI; HPC; biochemical simulation; model validation; systems biology.
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