The Forgotten Factor: Facts on Performance Evaluation and Its Dependence on Workloads

The performance of a computer system depends not only on its design and implementation, but also on the workloads it has to handle. Indeed, in some cases the workload can sway performance evaluation results. It is therefore crucially important that representative workloads be used for performance evaluation. This can be done by analyzing and modeling existing workloads. However, as more sophisticated workload models become necessary, there is an increasing need for the collection of more detailed data about workloads. This has to be done with an eye for those features that are really important.

[1]  Dror G. Feitelson,et al.  Utilization, Predictability, Workloads, and User Runtime Estimates in Scheduling the IBM SP2 with Backfilling , 2001, IEEE Trans. Parallel Distributed Syst..

[2]  Larry Rudolph,et al.  Metrics and Benchmarking for Parallel Job Scheduling , 1998, JSSPP.

[3]  Mark Crovella,et al.  Performance Evaluation with Heavy Tailed Distributions , 2000, Computer Performance Evaluation / TOOLS.

[4]  Dan C. Marinescu,et al.  Correlation of the paging activity of individual node programs in the SPMD execution mode , 1995, Proceedings of the Twenty-Eighth Annual Hawaii International Conference on System Sciences.

[5]  Mary K. Vernon,et al.  Characteristics of a Large Shared Memory Production Workload , 2001, JSSPP.

[6]  W. Cirne,et al.  A comprehensive model of the supercomputer workload , 2001, Proceedings of the Fourth Annual IEEE International Workshop on Workload Characterization. WWC-4 (Cat. No.01EX538).

[7]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[8]  Larry Rudolph,et al.  Evaluation of Design Choices for Gang Scheduling Using Distributed Hierarchical Control , 1996, J. Parallel Distributed Comput..

[9]  Paul Messina,et al.  A quantitative study of parallel scientific applications with explicit communication , 2004, The Journal of Supercomputing.

[10]  Francine Berman,et al.  A model for moldable supercomputer jobs , 2001, Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001.

[11]  Dror G. Feitelson,et al.  Job Characteristics of a Production Parallel Scientivic Workload on the NASA Ames iPSC/860 , 1995, JSSPP.

[12]  Anoop Gupta,et al.  The SPLASH-2 programs: characterization and methodological considerations , 1995, ISCA.

[13]  Allen B. Downey,et al.  The elusive goal of workload characterization , 1999, PERV.

[14]  Fang Wang,et al.  Modeling of Workload in MPPs , 1997, JSSPP.

[15]  Dror G. Feitelson Analyzing the Root Causes of Performance Evaluation Results , 2002 .

[16]  Francine Berman,et al.  A comprehensive model of the supercomputer workload , 2001 .

[17]  Jeffrey S. Vetter,et al.  Communication characteristics of large-scale scientific applications for contemporary cluster architectures , 2002, Proceedings 16th International Parallel and Distributed Processing Symposium.

[18]  Steven Hotovy,et al.  Workload Evolution on the Cornell Theory Center IBM SP2 , 1996, JSSPP.

[19]  Bill Nitzberg,et al.  A comparison of workload traces from two production parallel machines , 1996, Proceedings of 6th Symposium on the Frontiers of Massively Parallel Computation (Frontiers '96).

[20]  Evgenia Smirni,et al.  Workload Characterization of Input/Output Intensive Parallel Applications , 1997, Computer Performance Evaluation.

[21]  Anoop Gupta,et al.  Scaling parallel programs for multiprocessors: methodology and examples , 1993, Computer.

[22]  Phillip Krueger,et al.  ob Scheduling is More Important than Processor Allocation for Hypercube Computers , 1994, IEEE Trans. Parallel Distributed Syst..

[23]  Thu D. Nguyen,et al.  Parallel Application Characteristics for Multiprocessor Scheduling Policy Design , 1996, JSSPP.

[24]  Allen B. Downey,et al.  A parallel workload model and its implications for processor allocation , 1996, Proceedings. The Sixth IEEE International Symposium on High Performance Distributed Computing (Cat. No.97TB100183).

[25]  Carla Schlatter Ellis,et al.  File-Access Characteristics of Parallel Scientific Workloads , 1996, IEEE Trans. Parallel Distributed Syst..

[26]  Dror G. Feitelson,et al.  Memory Usage in the LANL CM-5 Workload , 1997, JSSPP.

[27]  Jens Mache,et al.  A Comparative Study of Real Workload Traces and Synthetic Workload Models for Parallel Job Scheduling , 1998, JSSPP.

[28]  Dror G. Feitelson,et al.  The workload on parallel supercomputers: modeling the characteristics of rigid jobs , 2003, J. Parallel Distributed Comput..

[29]  Patrick H. Worley,et al.  The Effect of Time Constraints on Scaled Speedup , 1990, SIAM J. Sci. Comput..

[30]  Leonid Oliker,et al.  System Utilization Benchmark on the Cray T3E and IBM SP , 2000, JSSPP.