Representing Task and Machine Heterogeneities for Heterogeneous Computing Systems

ABSTRACT A distributed heterogeneous computing (HC) system consists of diversely capable machines harnessed together to execute a set of tasks that vary in their computational requirements. Heuristics are needed to map (match and schedule) tasks onto machines in an HC system so as to optimize some figure of merit. An HC system model is needed to simulate different HC environments to allow the study of the relative performance of different mapping heuristics under different circumstances. This paper characterizes a simulated HC environment by using the expected execution times of the tasks that arrive in the system on the different machines present in the system. This information is arranged in an “expected time to compute” (ETC) matrix as a model of the given HC system, where the entry (i, j) is the expected execution time of task i on machine j. The ETC model is used to express the heterogeneity among the runtimes of the tasks to be executed, and among the machines in the HC system. An existing range-based technique to express heterogeneity in ETC matrices is described. A coefficient-of-variation based technique to express heterogeneity in ETC matrices is proposed, and compared with the range-based technique. The coefficient-of-variation-based ETC generation method provides a greater control over the spread of values (i.e., heterogeneity) in any given row or column of the ETC matrix than the range-based method.

[1]  R. F. Freund,et al.  Dynamic Mapping of a Class of Independent Tasks onto Heterogeneous Computing Systems , 1999, J. Parallel Distributed Comput..

[2]  Enrico Gobbetti,et al.  Encyclopedia of Electrical and Electronics Engineering , 1999 .

[3]  R. F. Freund,et al.  Scheduling resources in multi-user, heterogeneous, computing environments with SmartNet , 1998, Proceedings Seventh Heterogeneous Computing Workshop (HCW'98).

[4]  Howard Jay Siegel,et al.  The PASM project: a study of reconfigurable parallel computing , 1996, Proceedings Second International Symposium on Parallel Architectures, Algorithms, and Networks (I-SPAN'96).

[5]  Lawrence L. Lapin Probability and Statistics for Modern Engineering , 1983 .

[6]  Ray Jain,et al.  The art of computer systems performance analysis - techniques for experimental design, measurement, simulation, and modeling , 1991, Wiley professional computing.

[7]  Howard Jay Siegel,et al.  Heterogeneous Distributed Computing , 1999 .

[8]  Howard Jay Siegel,et al.  Techniques for mapping tasks to machines in heterogeneous computing systems , 2000, J. Syst. Archit..

[9]  John G. Proakis,et al.  Probability, random variables and stochastic processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[10]  Arif Ghafoor,et al.  Estimation of Execution times on Heterogeneous Supercomputer Architectures , 1993, 1993 International Conference on Parallel Processing - ICPP'93.

[11]  Arif Ghafoor,et al.  A distributed heterogeneous supercomputing management system , 1993, Computer.

[12]  A. A. Maciejewski,et al.  Heterogeneous Computing , 2002 .

[13]  Noé Lopez-Benitez,et al.  Simulation of task graph systems in heterogeneous computing environments , 1999, Proceedings. Eighth Heterogeneous Computing Workshop (HCW'99).

[14]  Ishfaq Ahmad,et al.  Optimal task assignment in heterogeneous distributed computing systems , 1998, IEEE Concurr..

[15]  Michael W. Godfrey,et al.  An overview of MSHN: the Management System for Heterogeneous Networks , 1999, Proceedings. Eighth Heterogeneous Computing Workshop (HCW'99).

[16]  Lee C. Potter,et al.  Statistical prediction of task execution times through analytic benchmarking for scheduling in a heterogeneous environment , 1999, Proceedings. Eighth Heterogeneous Computing Workshop (HCW'99).

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

[18]  Bruno O. Shubert,et al.  Random variables and stochastic processes , 1979 .

[19]  Ladislau Bölöni,et al.  A comparison study of static mapping heuristics for a class of meta-tasks on heterogeneous computing systems , 1999, Proceedings. Eighth Heterogeneous Computing Workshop (HCW'99).

[20]  Ami Marowka,et al.  The GRID: Blueprint for a New Computing Infrastructure , 2000, Parallel Distributed Comput. Pract..

[21]  Salim Hariri,et al.  Task scheduling algorithms for heterogeneous processors , 1999, Proceedings. Eighth Heterogeneous Computing Workshop (HCW'99).

[22]  Henry G. Dietz,et al.  Would You Run it Here or There? AHS: Automatic Heterogeneous Supercomputing , 1993, 1993 International Conference on Parallel Processing - ICPP'93.