Implementing a dynamic processor allocation policy for multiprogrammed parallel applications in the Solaris™ operating system

Kelvin K. Yue, David J. Lilja

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Parallel applications typically do not perform well in a multiprogrammed environment that uses time-sharing to allocate processor resources to the applications' parallel threads. Co-scheduling related parallel threads, or statistically partitioning the system, often can reduce the applications' execution times, but at the expense of reducing the overall system utilization. To address this problem, there has been increasing interest in dynamically allocating processors to applications based on their resource demands and the dynamically varying system load. The Loop-Level Process Control (LLPC) policy (Yue K, Lilja D. Efficient execution of parallel applications in multiprogrammed multiprocessor systems. 10th International Parallel Processing Symposium, 1996; 448-456) dynamically adjusts the number of threads an application is allowed to execute based on the application's available parallelism and the overall system load. This study demonstrates the feasibility of incorporating the LLPC strategy into an existing commercial operating system and parallelizing compiler and provides further evidence of the performance improvement that is possible using this dynamic allocation strategy. In this implementation, applications are automatically parallelized and enhanced with the appropriate LLPC hooks so that each application interacts with the modified version of the Solaris operating system. The parallelism of the applications are then dynamically adjusted automatically when they are executed in a multiprogrammed environment so that all applications obtain a fair share of the total processing resources.

Original languageEnglish (US)
Pages (from-to)449-464
Number of pages16
JournalConcurrency Computation
Issue number6
StatePublished - May 2001


  • Multiprogramming
  • Operating system
  • Parallelizing compiler
  • Performance measurement
  • Process scheduling
  • Processor allocation
  • Shared-memory multiprocessor


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