Perfilamento e Análise de Escalabilidade de Código em um Sistema Distribuído com o PaScal Analyzer: Um Estudo de Caso
Resumo
Este trabalho apresenta uma extensão do PaScal Analyzer, ferramenta para análise de escalabilidade, originalmente focada em aplicações OpenMP, agora adaptada para ambientes distribuídos via instrumentação manual e coleta de dados desacoplada. Aplicado ao benchmark NAS, o método identificou gargalos regionais, indicando seu potencial para análise e otimização em sistemas distribuídos.Referências
Adhianto, L., Banerjee, S., Fagan, M., Krentel, M., Marin, G., Mellor-Crummey, J., and Tallent, N. R. (2010). Hpctoolkit: Tools for performance analysis of optimized parallel programs. Concurrency and Computation: Practice and Experience, 22(6):685–701.
Bailey, D. H., Barszcz, E., Barton, J. T., Browning, D. S., Carter, R. L., Dagum, L., Fatoohi, R., Fineberg, S., Frederickson, P. O., Lasinski, T. A., Schreiber, R. S., Simon, H. D., Venkatakrishnan, V., and Weeratunga, S. (1994). The nas parallel benchmarks. Technical Report RNR-94-007, NASA Ames Research Center, Moffett Field, CA, USA. NASA Technical Report.
Boehme, D., Aschwanden, P., Pearce, O., Weiss, K., and LeGendre, M. (2021). Ubiquitous performance analysis. In Chamberlain, B. L., Varbanescu, A.-L., Ltaief, H., and Luszczek, P., editors, High Performance Computing, pages 431–449, Cham. Springer International Publishing.
Boehme, D., Gamblin, T., Beckingsale, D., Bremer, P.-T., Gimenez, A., LeGendre, M., Pearce, O., and Schulz, M. (2016). Caliper: performance introspection for hpc software stacks. In SC’16: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pages 550–560. IEEE.
da Silva, V. R. G., da Silva, A. B. N., Valderrama, C., Manneback, P., and Xavier-de Souza, S. (2022). A minimally intrusive approach for automatic assessment of parallel performance scalability of shared-memory hpc applications. Electronics, 11(5).
Eberius, D. (2020). Providing Insight into the Performance of Distributed Applications Through Low-Level Metrics. PhD thesis, University of Tennessee.
Fan, K., Kesavan, S., Petruzza, S., and Kumar, S. (2024). Tinyprof: Towards continuous performance introspection through scalable parallel i/o. In Proceedings of the International Supercomputing Conference (ISC), pages 1–12. IEEE.
Knüpfer, A., Rössel, C., Mey, D. a., Biersdorff, S., Diethelm, K., Eschweiler, D., Geimer, M., Gerndt, M., Lorenz, D., Malony, A., et al. (2012). Score-p: A joint performance measurement run-time infrastructure for periscope, scalasca, tau, and vampir. In Tools for High Performance Computing 2011: Proceedings of the 5th International Workshop on Parallel Tools for High Performance Computing, September 2011, ZIH, Dresden, pages 79–91. Springer.
Madsen, J. R., Awan, M. G., Brunie, H., Deslippe, J., Gayatri, R., Oliker, L., Wang, Y., Yang, C., and Williams, S. (2020). Timemory: modular performance analysis for hpc. In High Performance Computing: 35th International Conference, ISC High Performance 2020, Frankfurt/Main, Germany, June 22–25, 2020, Proceedings 35, pages 434–452. Springer.
Schulz, M., Galarowicz, J., Maghrak, D., Hachfeld, W., Montoya, D., and Cranford, S. (2008). Open— speedshop: An open source infrastructure for parallel performance analysis. Scientific Programming, 16.
Shende, S. S. and Malony, A. D. (2006). The tau parallel performance system. The International Journal of High Performance Computing Applications, 20(2):287–311.
Bailey, D. H., Barszcz, E., Barton, J. T., Browning, D. S., Carter, R. L., Dagum, L., Fatoohi, R., Fineberg, S., Frederickson, P. O., Lasinski, T. A., Schreiber, R. S., Simon, H. D., Venkatakrishnan, V., and Weeratunga, S. (1994). The nas parallel benchmarks. Technical Report RNR-94-007, NASA Ames Research Center, Moffett Field, CA, USA. NASA Technical Report.
Boehme, D., Aschwanden, P., Pearce, O., Weiss, K., and LeGendre, M. (2021). Ubiquitous performance analysis. In Chamberlain, B. L., Varbanescu, A.-L., Ltaief, H., and Luszczek, P., editors, High Performance Computing, pages 431–449, Cham. Springer International Publishing.
Boehme, D., Gamblin, T., Beckingsale, D., Bremer, P.-T., Gimenez, A., LeGendre, M., Pearce, O., and Schulz, M. (2016). Caliper: performance introspection for hpc software stacks. In SC’16: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pages 550–560. IEEE.
da Silva, V. R. G., da Silva, A. B. N., Valderrama, C., Manneback, P., and Xavier-de Souza, S. (2022). A minimally intrusive approach for automatic assessment of parallel performance scalability of shared-memory hpc applications. Electronics, 11(5).
Eberius, D. (2020). Providing Insight into the Performance of Distributed Applications Through Low-Level Metrics. PhD thesis, University of Tennessee.
Fan, K., Kesavan, S., Petruzza, S., and Kumar, S. (2024). Tinyprof: Towards continuous performance introspection through scalable parallel i/o. In Proceedings of the International Supercomputing Conference (ISC), pages 1–12. IEEE.
Knüpfer, A., Rössel, C., Mey, D. a., Biersdorff, S., Diethelm, K., Eschweiler, D., Geimer, M., Gerndt, M., Lorenz, D., Malony, A., et al. (2012). Score-p: A joint performance measurement run-time infrastructure for periscope, scalasca, tau, and vampir. In Tools for High Performance Computing 2011: Proceedings of the 5th International Workshop on Parallel Tools for High Performance Computing, September 2011, ZIH, Dresden, pages 79–91. Springer.
Madsen, J. R., Awan, M. G., Brunie, H., Deslippe, J., Gayatri, R., Oliker, L., Wang, Y., Yang, C., and Williams, S. (2020). Timemory: modular performance analysis for hpc. In High Performance Computing: 35th International Conference, ISC High Performance 2020, Frankfurt/Main, Germany, June 22–25, 2020, Proceedings 35, pages 434–452. Springer.
Schulz, M., Galarowicz, J., Maghrak, D., Hachfeld, W., Montoya, D., and Cranford, S. (2008). Open— speedshop: An open source infrastructure for parallel performance analysis. Scientific Programming, 16.
Shende, S. S. and Malony, A. D. (2006). The tau parallel performance system. The International Journal of High Performance Computing Applications, 20(2):287–311.
Publicado
02/07/2025
Como Citar
SANTOS-DA-SILVA, Felipe H.; GOMES, Júlio F. Peixoto; FERNANDES, João B.; XAVIER-DE-SOUZA, Samuel; ASSIS, Ítalo A. S..
Perfilamento e Análise de Escalabilidade de Código em um Sistema Distribuído com o PaScal Analyzer: Um Estudo de Caso. In: ESCOLA REGIONAL DE ALTO DESEMPENHO DA REGIÃO NORDESTE (ERAD-NE), 6. , 2025, Natal/RN.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 17-20.
DOI: https://doi.org/10.5753/erad-ne.2025.11760.
