Accelerating molecular dynamics computing using iteration space slicing

• Autorzy: Palkowski M.
• Języki publikacji: EN

Abstrakty

EN

Molecular dynamics is an important computational tool to simulate and understand biochemical processes at the atomic level. Accurate modelling of processes such as simulation of the Newtonian equations of motion requires a large number of computation steps for systems with hundreds to millions of particles. In this paper, we present an approach to accelerate molecular dynamics simulations by means of automatic program loop parallelization. To parallelize code of applications, we have used the Iteration Space Slicing framework. The scope of the applicability of the approach is illustrated using the Gromacs package. Results of a performance analysis for parallelized loops executed on a multi-core computer are presented. The future work is discussed.

Słowa kluczowe

EN

molecular computing; multicore processing; computational biology; computational biochemistry; application acceleration; loop parallelization

PL

obliczenia molekularne; przetwarzanie wielordzeniowe; biologia obliczeniowa; biochemia obliczeniowa; akceleracja aplikacji; zrównoleglenie pętli

• Wydawca: Wydawnictwo Politechniki Łódzkiej
• Czasopismo: Journal of Applied Computer Science
• Rocznik: 2013
• Tom: Vol. 21, nr 2
• Strony: 85--96
• Opis fizyczny: Bibliogr. 20 poz.

Twórcy

autor

Palkowski M.

• West Pomeranian University of Technology, Faculty of Computer Science and Information Technology, ul. Zolnierska 49, 71-210 Szczecin, Poland

Bibliografia

• [1] Plimpton, S. : Fast Parallel Algorithms for Short-Range Molecular Dynamics, Journal of Computational Physics, 117, pp. 1-19, (1995).
• [2] Lim, A., Lam, M., Cheong, G. : An affine partitioning algorithm to maximize parallelism and minimize communication. In ICS’99, ACM Press, 228-237, (1999).
• [3] Feautrier, P. : Somefficient solutions to the affine scheduling problem, part I and II, one and multidimensional time, International Journal of Parallel Programming 21, 313-348 and 389-420, (1992).
• [4] OpenMP Specification 3.0, http://www.openmp.org, (2008).
• [5] Beletska, A., Bielecki, W., Cohen, A., Palkowski, M., Siedlecki, K. : Coarsegrained loop parallelization: Iteration space slicing vs affine transformations. Parallel Computing, 37, 479-497, (2011).
• [6] Wonnacott, D. : A Retrospective of the Omega Project, Haverford College Computer Science Tech Report (2010).
• [7] Pugh, W., Wonnacott, D. : An exact method for analysis of value-based array data dependences. In In Sixth Annual Workshop on Programming Languages and Compilers for Parallel Computing. Springer-Verlag, (1993).
• [8] Kelly, W., Maslov, V., Pugh, W., Rosser, E., Shpeisman, T., Wonnacott, D. : The omega library interface guide. Technical report, College Park, MD, USA, (1995).
• [9] Bastoul, C., : Code Generation in the Polyhedral Model Is Easier Than You Think, PACT’13 IEEE International Conference on Parallel Architecture and Compilation Techniques, pp. 7–16, (2004).
• [10] Kelly, W., Pugh, W., Maslov, V., Rosser, E., Shpeisman, T., Wonnacott, D. : New User Interface for Petit and Other Extensions. User Guide, (1996).
• [11] Gromacs Documentation http://www.gromacs.org/Documentation, (2012).
• [12] Lindahl, E. : Introduction to molecular dynamics with GROMACS, http://courses.theophys.kth.se/SI2710/gromacs\_molecular\_modeling\_tutorial.pdf, (2011).
• [13] SPEC CPU2006 Benchmark, http://www.spec.org/cpu2006/, (2006).
• [14] PLUTO - An automatic parallelizer and locality optimizer for multicores, http://pluto-compiler.sourceforge.net, (2011).
• [15] Bondhugula, U., Baskaran, M., et al. : Affine transformations for communication minimal parallelization and locality optimization of arbitrarily-nested loopsequences,LectureNotesinComputerScience,Volume4959/2008,132-146, (2008).
• [16] Bondhugula, U., Hartono, A., Ramanujan, J., Sadayappan, P. : A practical automatic polyhedral parallelizer and locality optimizer. In ACM SIGPLAN Programming Languages Design and Implementation (PLDI ’08), (2008).
• [17] Polylib - A library of polyhedral functions, http://www.irisa.fr/polylib/, (2012).
• [18] Liu, W., et al.: Accelerating molecular dynamics simulations using Graphics Processing Units with CUDA, Computer Physics Communications 179, pp. 634-641, (2008).
• [19] Amini, M., et al. : Par4All User Guide http://www.par4all.org, (2012).
• [20] Amini, M., et al., : PIPS Is not (just) Polyhedral Software. In First International Workshop on Polyhedral Compilation Techniques (IMPACT 2011). Chamonix, France, 4/2011, (2011).