Fat versus thin threading approach on GPUs: Application to stochastic simulation of chemical reactions

IEEE Transactions on Parallel and Distributed Systems

Volumn 23, Issue 2, 2012, Pages 280-287

  Klingbeil, Guido ^a   Erban, Radek ^a   Giles, Mike ^b   Maini, Philip K ^a  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

compute unified device architecture (CUDA); graphics processing unit (GPU); Parallel processing

Indexed keywords

ACCESS LATENCY; COMPUTE UNIFIED DEVICE ARCHITECTURES; DATA ACCESS TIME; GRAPHICS PROCESSING UNIT; PARALLEL PROCESSING; REACTION SYSTEM; SHARED MEMORIES; STOCHASTIC SIMULATION ALGORITHMS; STOCHASTIC SIMULATIONS; THIN-THREADS;

CHEMICAL REACTIONS; PROGRAM PROCESSORS; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

COMPUTER GRAPHICS EQUIPMENT;

EID: 84855375396     PISSN: 10459219     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPDS.2011.157     Document Type: Article

References (28)

1. Nvidia CUDA Programming Guide, Version 2.1, NVIDIA Corporation, 2701 San Tomas Expressway, vol. 12, 2008.
2. R. Erban, S. Chapman, I. Kevrekidis, and T. Vejchodsky, "Analysis of a Stochastic Chemical System Close to a Sniper Bifurcation of Its Mean-Field Model," SIAM J. Applied Math., vol. 70, no. 3, pp. 984-1016, 2009.
3. B. Alberts, A. Johnson, J. Lewis, M. Raff, K. Roberts, and P. Walter, Molecular Biology of the Cell. Garland Science, 2007.
4. F. Holstege, E. Jennings, J. Wyrick, T. Lee, C. Hengartner, M. Green, T. Golub, E. Lander, and R. Young, "Dissecting the Regulatory Circuitry of a Eukaryotic Genome," Cell, vol. 95, no. 5, pp. 717-728, Nov. 1998. (Pubitemid 28544132)
5. J. Hasty, D. McMillen, F. Isaacs, and J. Collins, "Computational Studies of Gene Regulatory Networks: In Numero Molecular Biology," Nature Rev. Genetics, vol. 2, no. 4, pp. 268-279, Apr. 2001. (Pubitemid 33674775)
6. T. Tian and K. Burrage, "Stochastic Models for Regulatory Networks of the Genetic Toggle Switch," Proc. Nat'l Academy of Sciences of USA, vol. 103, no. 22, pp. 8372-8377, 2006. (Pubitemid 43838462)
7. G. Ewing, D. McNickle, and K. Pawlikowski, "Multiple Replications in Parallel: Distributed Generation of Data for Speeding up Quantitative Stochastic Simulation," Proc. Int'l Assoc. for Mathematics and Computers in Simulation (IMACS '97), pp. 397-402, 1997.
8. L. Dematte and T. Mazza, "On Parallel Stochastic Simulation of Diffusive Systems," Proc. Sixth Int'l Conf. Computational Methods in Systems Biology (CMSB '08), pp. 191-210, 2008.
9. T. Tian and K. Burrage, "Parallel Implementation of Stochastic Simulation for Large-Scale Cellular Processes," Proc. Eighth Int'l Conf. High Performance Computing and Grid in Asia-Pacific Region, vol. 0, pp. 621-626, 2005. (Pubitemid 46276495)
10. A. Snavely, L. Carter, J. Boisseau, A. Majumdar, K.S. Gatlin, N. Mitchell, J. Feo, and B. Koblenz, "Multi-Processor Performance on the Tera MTA," Proc. IEEE/ACM Conf. Supercomputing (SC '98), pp. 4-4, 1998.
11. A. Agarwal, J. Kubiatowicz, D. Kranz, B. Lim, D. Yeung, G. D'souza, and M. Parkin, "Sparcle: An Evolutionary Processor Design for Large-Scale Multiprocessors," IEEE Micro, vol. 13, no. 3, pp. 48-61, June 1993.
12. F. Irigoin and R. Triolet, "Supernode Partitioning," POPL '88: Proc. 15th ACM SIGPLAN-SIGACT Symp. Principles of Programming Languages, pp. 319-329, 1988.
13. D. Gillespie, "A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions," J. Computational Physics, vol. 22, pp. 403-434, 1976.
14. D. Gillespie, "Exact Stochastic Simulation of Coupled Chemical Reactions," J. Physical Chemistry, vol. 81, no. 25, pp. 2340-2361, 1977.
15. M. Gibson and J. Bruck, "Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels," J. Physical Chemistry A, vol. 104, pp. 1876-1889, 2000.
16. H. Li and L. Petzold, "Logarithmic Direct Method for Discrete Stochastic Simulation of Chemically Reacting Systems," technical report, Dept. of Computer Science, Univ. of California, http://www.cs.ucsb.edu/cse/ publications.php, 2006.
17. Y. Cao, H. Li, and L. Petzold, "Efficient Formulation of the Stochastic Simulation Algorithm for Chemically Reacting Systems," J. Chemical Physics, vol. 121, no. 9, pp. 4059-4067, 2004.
18. E. Lindholm, J. Nickolls, S. Oberman, and J. Montrym, "Nvidia Tesla: A Unified Graphics and Computing Architecture," IEEE CS Hot Chips, no. 19, pp. 39-45, Mar./Apr. 2008.
19. J. Nickolls, I. Buck, M. Garland, and K. Skadron, "Scalable Parallel Programming with CUDA," ACM Queue, vol. 6, no. 2, pp. 40-53, Mar./Apr. 2008.
20. P. Maciol and K. Banas, "Testing Tesla Architecture for Scientific Computing: The Performance of Matrix-Vector Product," Proc. Int'l Multiconf. Computer Science and Information Technology, vol. 3, pp. 285-291, 2008.
21. Nvidia Compute PTX: Parallel Thread Execution, ISA Version 1.4, NVIDIA Corporation, 2701 San Tomas Expressway, vol. 3, 2009.
22. G.M. Amdahl, "Validity of the Single Processor Approach to Achieving Large Scale Computing Capabilities," AFIPS '67 : Proc. Apr. 18-20, 1967, Spring Joint Computer Conf., pp. 483-485, 1967.
23. D. Gillespie, "Approximate Accelerated Stochastic Simulation of Chemically Reacting Systems," J. Chemical Physics, vol. 115, no. 4, pp. 1716-1733, 2001. (Pubitemid 32715518)
24. J. Murray, Mathematical Biology 1: An Introduction, third ed. Springer Verlag, 2002.
25. J. Vilar, H. Kueh, N. Barkai, and S. Leibler, "Mechanisms of Noise-Resistance in Genetic Oscillators," Proc. Nat'l Academy of Sciences of USA, vol. 99, no. 9, pp. 5988-5992, 2002. (Pubitemid 34493252)
26. D. Wilkinson, Stochastic Modelling for Systems Biology. Chapman & Hall/CRC, 2006.
27. NVIDIA CUDA C Programming Best Practices Guide CUDA Toolkit 2.3, NVIDIA Corporation, 2701 San Tomas Expressway, July 2008.
28. NVIDIAs Next Generation CUDA Compute Architecture: Fermi, NVIDIA Corporation, 2701 San Tomas Expressway, v 1.1, 2009.