Abstract
Performance modelling is an important tool utilised by the High Performance Computing industry to accurately predict the run-time of science applications on a variety of different architectures. Performance models aid in procurement decisions and help to highlight areas for possible code optimisations. This paper presents a performance model for a magnetohydrodynamics physics application, Lare. We demonstrate that this model is capable of accurately predicting the run-time of Lare across multiple platforms with an accuracy of 90% (for both strong and weak scaled problems). We then utilise this model to evaluate the performance of future optimisations. The model is generated using SST/macro, the machine level component of the Structural Simulation Toolkit (SST) from Sandia National Laboratories, and is validated on both a commodity cluster located at the University of Warwick and a large scale capability resource located at Lawrence Livermore National Laboratory.
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References
Pang, B., Li Pen, U., Perrone, M.: Magnetohydrodynamics on Heterogeneous architectures: a performance comparison. CoRR abs/1004.1680 (2010)
Ryoo, S., Rodrigues, C.I., Baghsorkhi, S.S., Stone, S.S., Kirk, D.B., Hwu, W.-M.W.: Optimization principles and application performance evaluation of a multithreaded GPU using CUDA. In: Proceedings of the 13th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2008, pp. 73–82. ACM, New York (2008)
Griebel, M., Zaspel, P.: A multi-GPU accelerated solver for the three-dimensional two-phase incompressible Navier-Stokes equations. Computer Science - Research and Development 25, 65–73 (2010), doi:10.1007/s00450-010-0111-7
Arber, T., Longbottom, A., Gerrard, C., Milne, A.: A Staggered Grid, Lagrangian-Eulerian Remap Code for 3-D MHD Simulations. Journal of Computational Physics 171 (2001)
Kerbyson, D., Hoisie, A., Wasserman, H.: Modelling the performance of large-scale systems.. IEE Proceedings – Software 150, 214 (2003)
Hammond, S.D., Mudalige, G.R., Smith, J.A., Davis, J.A., Jarvis, S.A., Holt, J., Miller, I., Herdman, J.A., Vadgama, A.: To upgrade or not to upgrade? Catamount vs. Cray Linux Environment. In: 2010 IEEE International Symposium on Parallel Distributed Processing, Workshops and Phd Forum (IPDPSW), pp. 1–8 (2010)
Herdman, J.A., Gaudin, W.P., Turland, D., Hammond, S.D.: Benchmarking and Modelling of POWER-7, Westmere, BG/P, and GPUs: An Industry Case Study. ACM SIGMETRICS Performance Evaluation Review 38 (2011)
Pennycook, S.J., Hammond, S.D., Mudalige, G.R., Wright, S.A., Jarvis, S.A.: On the Acceleration of Wavefront Applications using Distributed Many-Core Architectures. The Computer Journal 55, 138–153 (2011)
Mudalige, G.R., Giles, M.B., Bertolli, C., Kelly, P.H.: Predictive modeling and analysis of OP2 on distributed memory GPU clusters. In: Proceedings of the Second International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computing Systems, PMBS 2011, pp. 3–4. ACM, New York (2011)
Giles, M.B., Mudalige, G.R., Sharif, Z., Markall, G., Kelly, P.H.: Performance analysis of the OP2 framework on many-core architectures. SIGMETRICS Perform. Eval. Rev. 38, 9–15 (2011)
Alexandrov, A., Ionescu, M.F., Schauser, K.E., Scheiman, C.: LogGP: incorporating long messages into the LogP model - One step closer towards a realistic model for parallel computation. In: Proceedings of the Seventh Annual ACM Symposium on Parallel Algorithms and Architectures, SPAA 1995, pp. 95–105. ACM, New York (1995)
Culler, D., Karp, R., Patterson, D., Sahay, A., Schauser, K.E., Santos, E., Subramonian, R., von Eicken, T.: LogP: towards a realistic model of parallel computation. In: Proceedings of the Fourth ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP 1993, pp. 1–12. ACM, New York (1993)
Mudalige, G.R., Vernon, M.K., Jarvis, S.A.: A Plug-and-Play Model for Evaluating Wavefront Computations on Parallel Architectures. In: 22nd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2008 (2008)
Davis, J.A., Mudalige, G.R., Hammond, S.D., Herdman, J., Miller, I., Jarvis, S.A.: Predictive Analysis of a Hydrodynamics Application on Large-Scale CMP Clusters. In: International Supercomputing Conference (ISC 2011). Computer Science (R & D), vol. 26, pp. 175–185. Springer, Heidelberg (2011)
Sundaram-Stukel, D., Vernon, M.K.: Predictive analysis of a wavefront application using LogGP. SIGPLAN Not. 34, 141–150 (1999)
Hammond, S.D., Mudalige, G.R., Smith, J.A., Jarvis, S.A., Herdman, J.A., Vadgama, A.: WARPP: A Toolkit for Simulating High Performance Parallel Scientific Codes. In: 2nd International Conference on Simulation Tools and Techniques, SIMUTools 2009 (2009)
Janssen, C.L., Adalsteinsson, H., Kenny, J.P.: Using simulation to design extremescale applications and architectures: programming model exploration. SIGMETRICS Perform. Eval. Rev. 38, 4–8 (2011)
Rodrigues, A.F., Hemmert, K.S., Barrett, B.W., Kersey, C., Oldfield, R., Weston, M., Risen, R., Cook, J., Rosenfeld, P., CooperBalls, E., Jacob, B.: The structural simulation toolkit. SIGMETRICS Perform. Eval. Rev. 38, 37–42 (2011)
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Bird, R.F., Wright, S.A., Beckingsale, D.A., Jarvis, S.A. (2013). Performance Modelling of Magnetohydrodynamics Codes. In: Tribastone, M., Gilmore, S. (eds) Computer Performance Engineering. EPEW UKPEW 2012 2012. Lecture Notes in Computer Science, vol 7587. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36781-6_14
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DOI: https://doi.org/10.1007/978-3-642-36781-6_14
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