2000 Fiscal Year Final Research Report Summary
Efficient Processor Allocation Policies for Massively Parallel Systems
| Project/Area Number |
10680336
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
計算機科学
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| Research Institution | THE UNIVERSITY OF TOKYO |
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Principal Investigator |
SHIMIZU Kentaro GRADUATE SCHOOL OF AGRICULTURAL AND LIFE SCIENCES, THE UNIVERSITY OF TOKYO PROFESSOR, 大学院・農学生命科学研究科, 教授 (80178970)
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| Co-Investigator(Kenkyū-buntansha) |
NAKAMURA Shugo GRADUATE SCHOOL OF AGRICULTURAL AND LIFE SCIENCES, THE UNIVERSITY OF TOKYO RESEARCH ASSOCIATE, 大学院・農学生命科学研究科, 助手 (90272442)
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| Project Period (FY) |
1998 – 2000
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| Keywords | parallel computing / parallel programming environment / MPI (Message Passing Interface) / processor allocation / scheduling / molecular dynamics / computational chemistry |
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| Research Abstract |
We designed and implemented a new parallel programming environment called Parsley, which provides fine-grained scheduling services based on the structures of application programs. In Parsley, application programs are divided into subtasks that can run serially or in parallel. It provides a programming interface that allows a user to define subtasks and to easily specify precedence constraints among them. Parsley uses these constraints to schedule subtasks at run time. In this research project, we developed the scheduling policy and mechanism for Parsley and applied them to parallel molecular dynamics simulation program on distributed memory multiprocessor systems. The scheduling policy is automatically improved to reflect the hardware environment and resource usage. The basic policy is an incremental scheduling algorithm based on the critical path method. In this algorithm, subtask priorities are dynamically determined by using the execution time of each subtask, as monitored by the resource management facilities of Parsley. This policy improves processor utilization by 35 to 55 % compared with the FIFO scheduling policy. In addition, Parsley is useful in the heterogeneous environment (e.g. a network of different workstations and clusters) as well as the homogeneous environment. Users need not be aware of the individual performance of the computers and networks, because of the dynamic processor allocation facilities of Parsley. We have developed several resource management policies for Parsley on heterogeneous environment and evaluated the performance for molecular dynamics simulation.
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