This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Simulating Whole Supercomputer Applications
May/June 2011 (vol. 31 no. 3)
pp. 32-45
Juan Gonzalez, Barcelona Supercomputing Center
Judit Gimenez, Barcelona Supercomputing Center
Marc Casas, Lawrence Livermore National Laboratory
Miquel Moreto, Polytechnic University of Catalonia
Alex Ramirez, Polytechnic University of Catalonia
Jesus Labarta, Polytechnic University of Catalonia
Mateo Valero, Polytechnic University of Catalonia

Detailed simulations of large scale message-passing interface parallel applications are extremely time consuming and resource intensive. A new methodology that combines signal processing and data mining techniques plus a multilevel simulation reduces the simulated data by various orders of magnitude. This reduction makes possible detailed software performance analysis and accurate performance predictions in a reasonable time.

1. E.A. Brewer et al., "PROTEUS: A High-Performance Parallel-Architecture Simulator," Proc. ACM SIGMETRICS Joint Int'l Conf. Measurement and Modeling of Computer Systems, ACM Press, 1992, pp. 247-248.
2. J.E. Miller et al., "Graphite: A Distributed Parallel Simulator for Multicores," Proc. 16th IEEE Int'l Symp. High Performance Computer Architecture, IEEE Press, 2010, doi:10.1109/HPCA.2010.5416635.
3. E. Argollo et al., "COTSon: Infrastructure for Full System Simulation," ACM SIGOPS Operating Systems Review, vol. 43, no. 1, 2009, pp. 52-61.
4. E.S. Chung et al., "A Complexity-Effective Architecture for Accelerating Full-System Multiprocessor Simulations Using FPGAs," Proc. 16th Int'l ACM/SIGDA Symp. Field Programmable Gate Arrays, ACM Press, 2008, pp. 77-86.
5. E. Perelman et al., "Using SimPoint for Accurate and Efficient Simulation," Proc. ACM SIGMETRICS Int'l Conf. Measurement and Modeling of Computer Systems, ACM Press, 2003, pp. 318-319.
6. R.E. Wunderlich et al., "SMARTS: Accelerating Microarchitecture Simulation via Rigorous Statistical Sampling," ACM SIGARCH Computer Architecture News, vol. 31, no. 2, 2003, pp. 84-97.
7. M. Casas, R.M. Badia, and J. Labarta, "Automatic Structure Extraction from MPI Applications Tracefiles," Proc. Int'l Euro-Par Conf. Parallel Computing, LNCS 4641, Springer, 2007, pp. 3-12.
8. M. Ester et al., "A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise," Proc. 2nd Int'l Conf. Knowledge Discovery and Data Mining, AAAI Press, 1996, pp. 226-231.
9. J. Gonzalez, J. Gimenez, and J. Labarta, "Automatic Detection of Parallel Applications Computation Phases," Proc. IEEE Int'l Symp. Parallel & Distributed Processing, IEEE CS Press, 2009, doi:10.1109/IPDPS.2009.5161027.
10. S. Girona, J. Labarta, and R.M. Badia, "Validation of Dimemas Communication Model for MPI Collective Operations," Proc. 7th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface, Springer, 2000, pp. 39-46.
11. G. Toht, "Versatile Advection Code," Proc. Int'l Conf. Exhibition on High-Performance Computing and Networking, Springer, 1997, pp. 253-262.
12. J. Michalakes et al., "The Weather Research and Forecast Model: Software Architecture and Performance," Proc. 11th ECMWF Workshop Use of High Performance Computing in Meteorology, World Scientific Books, 2004, pp. 156-168.
1. E. Perelman et al., "Using SimPoint for Accurate and Efficient Simulation," Proc. ACM SIGMETRICS Int'l Conf. Measurement and Modeling of Computer Systems, ACM Press, 2003, pp. 318-319.
2. R.E. Wunderlich et al., "SMARTS: Accelerating Microarchitecture Simulation via Rigorous Statistical Sampling," ACM SIGARCH Computer Architecture News, vol. 31, no. 2, 2003, pp. 84-97.
3. E.A. Brewer et al., "PROTEUS: A High-Performance Parallel-Architecture Simulator," Proc. ACM SIGMETRICS Joint Int'l Conf. Measurement and Modeling of Computer Systems, ACM Press, 1992, pp. 247-248.
4. J.E. Miller et al., "Graphite: A Distributed Parallel Simulator for Multicores," Proc. 16th IEEE Int'l Symp. High Performance Computer Architecture, IEEE Press, 2010, doi:10.1109/HPCA.2010.5416635.
5. E.S. Chung et al., "A Complexity-Effective Architecture for Accelerating Full-System Multiprocessor Simulations using FPGAs," Proc. 16th Int'l ACM/SIGDA Symp. Field Programmable Gate Arrays, ACM Press, 2008, pp. 77-86.
6. E. Argollo et al., "COTSon: Infrastructure for Full System Simulation," ACM SIGOPS Operating Systems Review, vol. 43, no. 1, 2009, pp. 52-61.
7. L. Carrington et al., "A Performance Prediction Framework for Scientific Applications," Proc. Int'l Conf. Computational Science, LNCS 2659, Springer, 2003, pp. 926-935.
8. E.A. León et al., "Instruction-Level Simulation of a Cluster at Scale," Proc. Conf. High Performance Computing Networking, Storage and Analysis, ACM Press, 2009, doi:10.1145/1654059.1654063.
9. G. Zheng et al., "Simulating Large Scale Parallel Applications Using Statistical Models for Sequential Execution Blocks," Proc. IEEE 16th Int'l Conf. Parallel and Distributed Systems, IEEE Press, 2010, pp. 221-228.

Index Terms:
parallel applications, performance analysis, performance prediction, spectral analysis, cluster analysis, microarchitecture simulation, network simulation, Barcelona Supercomputing Center, message-passing interface
Citation:
Juan Gonzalez, Judit Gimenez, Marc Casas, Miquel Moreto, Alex Ramirez, Jesus Labarta, Mateo Valero, "Simulating Whole Supercomputer Applications," IEEE Micro, vol. 31, no. 3, pp. 32-45, May-June 2011, doi:10.1109/MM.2011.58
Usage of this product signifies your acceptance of the Terms of Use.