Performance-driven processor allocation

• Published in: IEEE transactions on parallel and distributed systems Vol. 16; no. 7; pp. 599 - 611
• Main Authors: Corbalan, J., Martorell, X., Labarta, J.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2005; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithm design and analysis; Coordinate measuring machines; Delay; Humans; Multiprocessing systems; multiprocessor scheduling; OpenMP; Operating system algorithms; Performance analysis; Processor scheduling; Proposals; runtime analysis; Runtime library; Scheduling algorithm; Studies
• ISSN: 1045-9219; 1558-2183
• DOI: 10.1109/TPDS.2005.85

In current multiprogrammed multiprocessor systems, to take into account the performance of parallel applications is critical to decide an efficient processor allocation. In this paper, we present the performance-driven processor allocation policy (PDPA). PDPA is a new scheduling policy that implements a processor allocation policy and a multiprogramming-level policy, in a coordinated way, based on the measured application performance. With regard to the processor allocation, PDPA is a dynamic policy that allocates to applications the maximum number of processors to reach a given target efficiency. With regard to the multiprogramming level, PDPA allows the execution of a new application when free processors are available and the allocation of all the running applications is stable, or if some applications show bad performance. Results demonstrate that PDPA automatically adjusts the processor allocation of parallel applications to reach the specified target efficiency, and that it adjusts the multiprogramming level to the workload characteristics. PDPA is able to adjust the processor allocation and the multiprogramming level without human intervention, which is a desirable property for self-configurable systems, resulting in a better individual application response time.