AESS: Accelerated Exact Stochastic Simulation

The Stochastic Simulation Algorithm (SSA) developed by Gillespie provides a powerful mechanism for exploring the behavior of chemical systems with small species populations or with important noise contributions. Gene circuit simulations for systems biology commonly employ the SSA method, as do ecological applications. This algorithm tends to be computationally expensive, so researchers seek an efficient implementation of SSA. In this program package, the Accelerated Exact Stochastic Simulation Algorithm (AESS) contains optimized implementations of Gillespieʼs SSA that improve the performance of individual simulation runs or ensembles of simulations used for sweeping parameters or to provide statistically significant results.Program summaryProgram title: AESSCatalogue identifier: AEJW_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJW_v1_0.htmlProgram obtainable from: CPC Program Library, Queenʼs University, Belfast, N. IrelandLicensing provisions: University of Tennessee copyright agreementNo. of lines in distributed program, including test data, etc.: 10 861No. of bytes in distributed program, including test data, etc.: 394 631Distribution format: tar.gzProgramming language: C for processors, CUDA for NVIDIA GPUsComputer: Developed and tested on various x86 computers and NVIDIA C1060 Tesla and GTX 480 Fermi GPUs. The system targets x86 workstations, optionally with multicore processors or NVIDIA GPUs as accelerators.Operating system: Tested under Ubuntu Linux OS and CentOS 5.5 Linux OSClassification: 3, 16.12Nature of problem: Simulation of chemical systems, particularly with low species populations, can be accurately performed using Gillespieʼs method of stochastic simulation. Numerous variations on the original stochastic simulation algorithm have been developed, including approaches that produce results with statistics that exactly match the chemical master equation (CME) as well as other approaches that approximate the CME.Solution method: The Accelerated Exact Stochastic Simulation (AESS) tool provides implementations of a wide variety of popular variations on the Gillespie method. Users can select the specific algorithm considered most appropriate. Comparisons between the methods and with other available implementations indicate that AESS provides the fastest known implementation of Gillespieʼs method for a variety of test models. Users may wish to execute ensembles of simulations to sweep parameters or to obtain better statistical results, so AESS supports acceleration of ensembles of simulation using parallel processing with MPI, SSE vector units on x86 processors, and/or using NVIDIA GPUs with CUDA.

► Stochastic simulation algorithm (Gillespieʼs method) implementation.
► Fastest known implementation of exact Gillespie method.
► Supports parallelism using MPI.
► GPGPU support with CUDA.
► Supports tau leaping.