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While technology trends have ushered in the age of chip multiprocessors (CMP) and enabled designers to place an increasing number of cores on chip, a fundamental question is what size to make each core. Most current commercial designs are symmetric CMPs in which each core is identical and range from a relatively simple RISC pipeline to a large and complicated out-of-order x86 core. When the granularity of parallelism in the tasks matches the granularity of the processing cores, a CMP will be at its most efficient. To adjust the granularity of a core to the tasks running on it, recent research has proposed flexible-core chip multiprocessors, which typically consist of a number of small processing cores that can be aggregated to form larger logical processors. These architectures introduce a new resource allocation and scheduling problem which must determine how many logical processors should be configured, how powerful each processor should be, and where/when each task should run. This paper introduces and motivates this new scheduling problem, describes the challenges associated with it, and examines and evaluates several algorithms (amenable to implementation in an operating system) appropriate for such flexible-core CMPs. We also describe how scheduling for flexible-core architectures differs from scheduling for fixed multicore architectures, and compare the performance of flexible-core CMPs to both symmetric and asymmetric fixed-core CMPs.

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Multitasking workload scheduling on flexible core chip multiprocessors

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