Performance-driven scheduling for malleable workloads
NJOUD OMAR ALMAAITAH,
David E. Singh,
Taylan Özden
et al.
Abstract:The development of adaptive scheduling algorithms that take advantage of malleability has become a crucial area of research in many large-scale projects. Malleable workloads can improve the system's performance but at the same time provide an extra dimension to the scheduling problem. This paper proposes an adaptive, performance-based job scheduling method that emphasizes the backfilling concept with malleability. The proposed method performs the malleability operations only when the estimated execution time o… Show more
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