Using Idle Memory Anurag Acharya Dept. of Computer Science University of California Santa Barbara, CA 93106 for Data-Intensive Computations Sanjeev Setia Dept. of Computer Science George Mason University Fairfax, VA 22030 Exploiting idle workstations for hosting guest computation has been a popular research area [l, 2, 3, 4, 5, 61. With the current growth in the number and the size of data-intensive tasks, exploiting idle workstations for their memory is an attractive option. This would be particularly attractive for programs with transient peaks in their memory requirements or for data-intensive programs that are run infrequently. In the research described in this paper, we examine the utility of exploiting idle memory in workstation pools. We attempt to answer the following questions. First, given a workstation pool, what fraction of the memory can be expected to be idle? This provides an estimate of the opportunity for hosting guest data. Second, what fraction of a individual host s memory can be expected to be idle? This helps determine the recruitment policy - what is the maximum amount of memory that should be recruited on a single host? Third, what is the distribution of memory idletimes? This indicates how long guest data
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Using idle memory for data-intensive computations (extended abstract)
Acharya, Anurag; Setia, Sanjeev
Follow ACM SIGMETRICS Performance Evaluation Review
, Volume 26 (1)
Association for Computing Machinery – Jun 1, 1998
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