In this paper we present an automatic system able to detect the internal structure of executions of high-performance computing applications. This automatic system is able to rule out non-significant regions of executions, to detect redundancies, and, finally, to select small but significant execution regions. This automatic detection process is based on spectral analysis (wavelet transform, Fourier transform, etc.) and works detecting the most important frequencies of the application’s execution. These main frequencies are strongly related to the internal loops of the application’s source code. The automatic detection of small but significant execution regions shown in the paper reduces the load of the performance analysis process remarkably.
Badia, R.M., et al. (2003). Programming Grid applications with GRID Superscalar. J. Grid Comput. 1(2): 151-170.
2.
Bailey, D., et al. (1994). The NAS Parallel Benchmarks. RNR Technical Report RNR-94-007.
3.
Baysal, E., Kosloff, D.D. and Sherwood, J.W.C. ( 1983). Reverse time migration. Geophysics48: 1514-1524.
4.
Brunst, H., Kranzlmuller, D. and Nagel, W.E. ( 2004). Tools for scalable parallel program analysis-Vampir VNG and DeWiz. Distributed and Parallel Systems, pp. 93-102.
5.
Casas, M., Badia, R.M. and Labarta, J. ( 2007). Automatic extraction of structure of MPI applications tracefiles. Proceedings of the International Euro-Par Conference on Parallel Computing (Euro-Par), pp. 3-12.
6.
Daubechies, I. ( 1992). Ten Lectures on Waveletes. Philadelphia , PA: Society for Industrial and Applied Mathematics .
7.
De Chevigne, A. and Kawahara, H. ( 2002). YIN, a fundamental frequency estimator for speech and music. J. Acoust. Soc. Am. 111: 1917-1930.
8.
Gamblin, T. et al. (2008). Scalable load-balance measurement for SPMD codes. Proceedings of the 2008 ACM/IEEE Conference on Supercomputing.
9.
Geimer, M. et al. (2008). The SCALASCA Performance Tool-set Architecture . Proceedings of the International Workshop on Scalable Tools for High-End Computing (STHEC), pp. 51-65.
10.
Gerndt, M. and Kereku, E. ( 2007). Automatic memory access analysis with Periscope. Proceedings of the International Conference on Computational Science (ICCS) (Lecture Notes in Computer Science, Vol. 4488). Berlin: Springer , pp. 847-854.
11.
Houzeaux, G., Eguzkitza, B. and Vázquez, M. ( 2007). A variational multiscale model for the advection-diffusion-reaction equation. Communications in Numerical Methods in Engineering .
12.
Hoyas, S. and Jimenez, J. (2006). Scaling of velocity fluctuations in turbulent channels up to Re=2003. Phys. Fluids18: 351-356.
13.
Huffmire, T. and Sherwood, T. ( 2006). Wavelet-based phase classification. Proceedings of Parallel Architectures and Compilation Techniques (PACT), pp. 95-104.
14.
Kaiser, G. ( 1994). A Friendly Guide to Wavelets. Basel : Birkhäuser.
15.
Knuepfer, A., Brunst, H. and Nagel, W.E. ( 2005). High performance event trace visualization. Proceedings of the 13th Euromicro Conference on Parallel, Distributed and Network-Based Processing, pp. 258-263.
16.
Komatitsch, D., Ritsema, J. and Tromp, J. ( 2002). The spectral-element method, Beowulf computing and global seismology. Science298: 1737-1742.
17.
Kranzlmuller, D., Scarpa, M. and Volkert, J. ( 2003). DeWiz-a modular tool architecture for parallel program analysis. Proceedings of the European Conference on Parallel Computing (Euro-Par), pp. 74-80.
18.
Labarta, J. et al. (1996). DiP: a parallel program development environment . Proceedings of the European Conference on Parallel Computing (Euro-Par), pp. 665-674.
19.
Mohr, B. and Traff, J.L. ( 2003). Initial design of a test suite for automatic performance analysis tools. Proceedings of the IEEE International Parallel & Distributed Processing Symposium (IPDPS), pp. 131-140.
20.
Mohr, B. and Wolf, F. ( 2003). KOJAK-a tool set for automatic performance analysis of parallel programs. Proceedings of the International Euro-Par Conference on Parallel Computing (Euro-Par), pp. 1301-1304.
21.
Nagel, W. et al. (1996). VAMPIR: visualization and analysis of MPI resources. Supercomputer63: 69-80.
22.
Press, W.H. et al. (1992). Numerical Recipes in FORTRAN: The Art of Scientific Computing, 2nd edn. Cambridge : Cambridge University Press, pp. 538-539.
23.
Roth, P.C. and Miller, B.P. ( 2006). On-line automated performance diagnosis on thousands of processes. Proceedings of 11th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), pp. 69-80.
24.
Saxena, V. et al. (2004). Vacuum-assisted closure: microdeformations of wounds and cell proliferation. Plastic and Reconstructive Surgery114: 1086-1096.
25.
Shen, X., Zhong, Y. and Ding, C. ( 2004). Locality phase prediction. Proceedings of the 11th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), pp. 165-176.
26.
Shende, S. and Malony, A.D. ( 2006). The TAU Parallel Performance System. Int. J. High Perform. Comput. Appl. 20(2): 287-311.
27.
Sherwood, T. et al. (2002). Automatically characterizing large scale program behavior. Proceedings of the 10th International Conference on Architectural Support for Programming Languages and Operating Systems, (ASPLOS), pp. 45-57.
28.
Springel, V., Yoshida, N. and White, S.D.M. ( 2001). Gadget: a code for collisionless and gasdynamical cosmological simulations. New Astron. 6(2): 79-117.
29.
Teysser, R. ( 2002). Cosmological hydrodynamics with adaptive mesh refinement-a new high resolution code called RAMSES. Astron. Astrophys385: 337-364.
30.
Vetter, J.S. and Worley, P.H. ( 2002). Asserting performance expectations. Proceedings of the ACM/IEEE International Conference on Supercomputing, pp. 1-13.
31.
Walnut, D.F. ( 2004). An Introduction to Wavelet Analysis. Boston, MA: Birkhäuser.
