Hybrid resource management algorithms for multicomputer systems

Addresses the issue of resource management in parallel systems. Two new hybrid algorithms for general resource management in distributed memory computers are presented. T-hybrid is a decoupled algorithm that combines a static template allocation scheme with a low-cost local demand-driven dynamic algorithm while C-hybrid is a coupled algorithm that combines a simple static allocation scheme with the same dynamic algorithm as T-hybrid. A set of test programs is scheduled using these hybrid algorithms and compared with scheduling using pure static and dynamic schemes when executed on an Ncube2 system under the Chare Kernel. The results show that the two new hybrid strategies provide faster execution times than all the pure dynamic and static algorithms investigated, and that the simpler C-hybrid algorithm resulted in an execution time about 6% faster than T-hybrid and 22% faster than the fastest non-hybrid scheme.<<ETX>>

[1]  Laxmikant V. Kalé,et al.  Comparing the Performance of Two Dynamic Load Distribution Methods , 1988, ICPP.

[2]  Charles L. Seitz,et al.  Multicomputers: message-passing concurrent computers , 1988, Computer.

[3]  Utpal Banerjee,et al.  Dependence analysis for supercomputing , 1988, The Kluwer international series in engineering and computer science.

[4]  Daniel A. Reed,et al.  Circuit-switched multicomputers and heuristic load placement , 1989 .

[5]  Srinivas Patil,et al.  Parallel algorithms for test generation and fault simulation , 1991 .

[6]  Robert M. Keller,et al.  The Gradient Model Load Balancing Method , 1987, IEEE Transactions on Software Engineering.

[7]  Prithviraj Banerjee,et al.  Performance measurement and trace driven simulation of parallel CAD and numeric applications on a hypercube multicomputer , 1990, ISCA '90.

[8]  Yung-Terng Wang,et al.  Load Sharing in Distributed Systems , 1985, IEEE Transactions on Computers.

[9]  Daniel A. Reed The Performance of Multimicrocomputer Networks Supporting Dynamic Workloads , 1984, IEEE Transactions on Computers.

[10]  Laxmikant V. Kalé,et al.  Supporting Machine Independent Programming on Diverse Parallel Architectures , 1991, ICPP.

[11]  Masahiro Tsuchiya,et al.  A Task Allocation Model for Distributed Computing Systems , 1982, IEEE Transactions on Computers.

[12]  Jerry C. Yan,et al.  The Post-Game Analysis Framework - Developing Resource Management Strategies for Concurrent Systems , 1989, IEEE Trans. Knowl. Data Eng..

[13]  Shahid H. Bokhari,et al.  Control of Distributed Processes , 1978, Computer.

[14]  Menkae Jeng,et al.  Dynamic Task Allocation on Shared Memory Multiprocessor Systems , 1990, ICPP.

[15]  Larry D. Wittie,et al.  Wave Scheduling - Decentralized Scheduling of Task Forces in Multicomputers , 1984, IEEE Trans. Computers.

[16]  Harold S. Stone,et al.  Multiprocessor Scheduling with the Aid of Network Flow Algorithms , 1977, IEEE Transactions on Software Engineering.

[17]  Janak H. Patel,et al.  The LAST Algorithm: A Heuristic-Based Static Task Allocation Algorithm , 1989, International Conference on Parallel Processing.

[18]  Gordon Bell,et al.  Ultracomputers: a teraflop before its time , 1992, CACM.

[19]  Donald F. Towsley,et al.  Adaptive Load Sharing in Heterogeneous Distributed Systems , 1990, J. Parallel Distributed Comput..

[20]  Kemal Efe,et al.  Heuristic Models of Task Assignment Scheduling in Distributed Systems , 1982, Computer.

[21]  Anna Hác,et al.  Dynamic Load Balancing in a Distributed System Using a Decentralized Algorithm , 1987, ICDCS.