Avaliação do Escalonamento de Processos Através de Monitoração
Resumo
Este artigo descreve o PSMS (Process Scheduling Monitoring System), uma ferramenta para monitorar o escalonamento de processos em sistemas distribuídos. Com a informação retornada pelo PSMS, o software de escalonamento pode descobrir se os objetivos definidos para o escalonamento de processos estão sendo alcançados, e pode opcionalmente modificar ou adaptar o algoritmo de escalonamento, permitindo melhor desempenho.O PSMS trabalha com métricas e regras de decisão aplicadas a essas métricas. Este artigo apresenta a estrutura geral do PSMS e um estudo de caso de sua utilização, envolvendo métricas relacionadas à utilização da CPU e uma regra de decisão baseada no coeficiente de variação.Referências
Baumgartner, K.M., e Wah, B. W. (1991) “Computer Scheduling Algorithms: Past, Present and Future”, Information Sciences, Elsevier Science Pub. Co., v.57, pp. 319-345.
Beguelin, A., Geist, A., Dongarra, J., Jiang, W., Manchek, R., e Sunderam, V. (1994) “PVM: Parallel Virtual Machine. A User’s Guide and Tutorial for Networked Parallel Computing”, The MIT Press.
Berman, F., Wolski, R., Casanova, H., Cirne, W., Dail, H., Faerman, M., Figueira, S., Hayes, J., Obertelli, G., Schopf, J., Shao, G., Smallen, S., Spring, S., Su, A., e Zagorodnov, D. (2003) “Adaptive Computing on the Grid Using AppLeS”, IEEE Transactions on Parallel and Distributed Systems (TPDS), 14(4), pp. 369--382.
Feilteson, D.G., e Rudolph, L. (1995) “Parallel Job Scheduling: Issues and Approaches”, IPPS'95 Workshop on Job Scheduling Strategies for Parallel Processing, Lecture Notes in Computer Science v.949, Abril.
Feiltelson, D.G., e Rudolph, L. (1996) “Toward Convergence in Job Schedulers for Parallel Supercomputers”, IPPS' 96 Workshop on Job Scheduling Strategies for Parallel Processing, Lecture Notes in Computer Science v.1162, April.
Feiltelson, D.G., e Rudolph, L. (1998) “Metrics and Benchmarking for Parallel Job Scheduling”, Lecture Notes in Computer Science, n. 1459, p. 1-24.
Ferrari, D., e Zhou, S. (1987) “An Empirical Investigation of Load Indices for Load Balancing Applications”, Proceedings of Performance'87, the 12th Int'l Symposium on Computer Performance Modeling, Measurement, and Evaluation, pp. 515-528.
Gardner, M.K., Feng, W., Broxton, M., Engelhart, A., e Hurwitz, G. (2003) “MAGNeT: A Tool for Debugging, Analyzing and Adapting Computing Systems”, Proc. Of the 3rd IEEE/ACM International Symposium on Cluster Computing and the Grid.
Krallmann, J.; Schwigelshohn, U. (1999) On the design and evaluation of job scheduling algorithms. in. Feitelson D.; Rudolph, L. eds. Job Scheduling Strategies for Parallel Processing, Springer-Verlag, pp. 17-42.
Miller, B.P., Callaghan, M.D., Cargille, J.M., Hollingsworh, J.K., Irwin, R.B, Karavanic, K.L., Kunchithapadam, K., e Newhall, T. (1995) “The Paradyn Parallel Performance Measurements tools”, IEEE Computer, November.
Platform Computing Corporation. (2000) “LSF Administrator's Guide”.
Ribler, R.L., Simitci, H., e Reed, D.A. (2001) “The Autopilot Performance-Directed Adaptive Control System”, Future Generation Computer Systems, Special Issue (Performance Data Mining), 18(1), September.
Shirazi, B., e Hurson, A.R. (1992) “Special Issue on Scheduling and Load Balancing: Guest Editor's Introduction”, Journal of Parallel and Distributed Computing, v.16, Issue 4.
Smith, W. (2001) “A framework for control and observation in distributed environments”, Technical Report NAS-01-006, NASA.
Souza, P.S.L., Santana, M.J., e Santana, R.H.C. (1999) “A New Scheduling Environment for Near-Optimal Performance”, International Conference on Parallel and Distributed Processing Techniques and Applications - PDPTA'99.
Sun Microsystems, Inc. (2003) “Sun Grid Engine 5.3 Administration and User's Guide”.
Wolski, R., Spring, N., e Hayes J. (1999) “The Network Weather Service: A Distributed Resource Performance Forecasting Service for Metacomputing”, Journal of Future Generation Computing Systems, Volume 15, Numbers 5-6, October.
Wong, F.C., Martin, R.P, Arpaci-Dusseau, R.H., e Culler, D.E. (1999) “Architectural requirements and scalability of the NAS parallel benchmarks”, Proceedings of the 1999 ACM/IEEE conference on Supercomputing.
Beguelin, A., Geist, A., Dongarra, J., Jiang, W., Manchek, R., e Sunderam, V. (1994) “PVM: Parallel Virtual Machine. A User’s Guide and Tutorial for Networked Parallel Computing”, The MIT Press.
Berman, F., Wolski, R., Casanova, H., Cirne, W., Dail, H., Faerman, M., Figueira, S., Hayes, J., Obertelli, G., Schopf, J., Shao, G., Smallen, S., Spring, S., Su, A., e Zagorodnov, D. (2003) “Adaptive Computing on the Grid Using AppLeS”, IEEE Transactions on Parallel and Distributed Systems (TPDS), 14(4), pp. 369--382.
Feilteson, D.G., e Rudolph, L. (1995) “Parallel Job Scheduling: Issues and Approaches”, IPPS'95 Workshop on Job Scheduling Strategies for Parallel Processing, Lecture Notes in Computer Science v.949, Abril.
Feiltelson, D.G., e Rudolph, L. (1996) “Toward Convergence in Job Schedulers for Parallel Supercomputers”, IPPS' 96 Workshop on Job Scheduling Strategies for Parallel Processing, Lecture Notes in Computer Science v.1162, April.
Feiltelson, D.G., e Rudolph, L. (1998) “Metrics and Benchmarking for Parallel Job Scheduling”, Lecture Notes in Computer Science, n. 1459, p. 1-24.
Ferrari, D., e Zhou, S. (1987) “An Empirical Investigation of Load Indices for Load Balancing Applications”, Proceedings of Performance'87, the 12th Int'l Symposium on Computer Performance Modeling, Measurement, and Evaluation, pp. 515-528.
Gardner, M.K., Feng, W., Broxton, M., Engelhart, A., e Hurwitz, G. (2003) “MAGNeT: A Tool for Debugging, Analyzing and Adapting Computing Systems”, Proc. Of the 3rd IEEE/ACM International Symposium on Cluster Computing and the Grid.
Krallmann, J.; Schwigelshohn, U. (1999) On the design and evaluation of job scheduling algorithms. in. Feitelson D.; Rudolph, L. eds. Job Scheduling Strategies for Parallel Processing, Springer-Verlag, pp. 17-42.
Miller, B.P., Callaghan, M.D., Cargille, J.M., Hollingsworh, J.K., Irwin, R.B, Karavanic, K.L., Kunchithapadam, K., e Newhall, T. (1995) “The Paradyn Parallel Performance Measurements tools”, IEEE Computer, November.
Platform Computing Corporation. (2000) “LSF Administrator's Guide”.
Ribler, R.L., Simitci, H., e Reed, D.A. (2001) “The Autopilot Performance-Directed Adaptive Control System”, Future Generation Computer Systems, Special Issue (Performance Data Mining), 18(1), September.
Shirazi, B., e Hurson, A.R. (1992) “Special Issue on Scheduling and Load Balancing: Guest Editor's Introduction”, Journal of Parallel and Distributed Computing, v.16, Issue 4.
Smith, W. (2001) “A framework for control and observation in distributed environments”, Technical Report NAS-01-006, NASA.
Souza, P.S.L., Santana, M.J., e Santana, R.H.C. (1999) “A New Scheduling Environment for Near-Optimal Performance”, International Conference on Parallel and Distributed Processing Techniques and Applications - PDPTA'99.
Sun Microsystems, Inc. (2003) “Sun Grid Engine 5.3 Administration and User's Guide”.
Wolski, R., Spring, N., e Hayes J. (1999) “The Network Weather Service: A Distributed Resource Performance Forecasting Service for Metacomputing”, Journal of Future Generation Computing Systems, Volume 15, Numbers 5-6, October.
Wong, F.C., Martin, R.P, Arpaci-Dusseau, R.H., e Culler, D.E. (1999) “Architectural requirements and scalability of the NAS parallel benchmarks”, Proceedings of the 1999 ACM/IEEE conference on Supercomputing.
Publicado
31/07/2004
Como Citar
SOUZA, Márcio Augusto de; SANTANA, Regina Helena C.; SANTANA, Marcos José.
Avaliação do Escalonamento de Processos Através de Monitoração. In: WORKSHOP EM DESEMPENHO DE SISTEMAS COMPUTACIONAIS E DE COMUNICAÇÃO (WPERFORMANCE), 3. , 2004, Salvador/BA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2004
.
p. 35-49.
ISSN 2595-6167.
