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Multitasking Workload Scheduling on Flexible Core Chip Multiprocessors

机译:柔性核心芯片多处理器上的多任务工作负荷调度

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摘要

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 multi-core architectures, and compare the performance of flexible-core CMPs to both symmetric and asymmetric fixed-core CMPs.
机译:尽管技术发展趋势已进入芯片多处理器(CMP)时代,并使设计人员能够在芯片上放置越来越多的内核,但一个基本的问题是每个内核的尺寸如何。当前大多数商用设计都是对称CMP,其中每个内核都是相同的,范围从相对简单的RISC管线到大型复杂的无序x86内核。当任务中并行性的粒度与处理核心的粒度匹配时,CMP将是最有效的。为了调整内核的粒度以适应在其上运行的任务,最近的研究提出了柔性内核芯片多处理器,该处理器通常由许多小的处理内核组成,这些小处理内核可以聚合形成更大的逻辑处理器。这些体系结构引入了新的资源分配和调度问题,该问题必须确定应该配置多少个逻辑处理器,每个处理器应该有多强大以及每个任务应该在哪里/何时运行。本文介绍并激发了这个新的调度问题,描述了与之相关的挑战,并研究和评估了适用于此类灵活核CMP的几种算法(适合在操作系统中实现)。我们还将描述灵活核心体系结构的调度与固定多核体系结构的调度有何不同,并比较灵活核心CMP与对称和不对称固定核心CMP的性能。

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