数据流:超标量的补充

M. Budiu, Pedro V. Artigas, S. Goldstein
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引用次数: 44

摘要

人们对数据流体系结构的兴趣已经重新抬头,因为它们具有利用低开销的并行性的潜力。在本文中,我们分析了一类静态数据流机器在整数媒体和控制密集型程序上的性能,并解释了为什么数据流机器,即使拥有无限的资源,在假设两台机器执行基本操作所需的时间相同的情况下,在通用代码上并不总是优于超标量处理器。我们将具有无限并行性的特定于程序的数据流机器与运行相同程序的超标量处理器进行比较。虽然数据流机器在大多数数据并行程序上提供了非常好的性能,但我们表明数据流机器并不总是能够利用可用的并行性。使用动态关键路径,我们研究了超标量处理器用于提供性能优势的机制及其对数据流模型的影响
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Dataflow: A Complement to Superscalar
There has been a resurgence of interest in dataflow architectures, because of their potential for exploiting parallelism with low overhead. In this paper we analyze the performance of a class of static dataflow machines on integer media and control-intensive programs and we explain why a dataflow machine, even with unlimited resources, does not always outperform a superscalar processor on general-purpose codes, under the assumption that both machines take the same time to execute basic operations. We compare a program-specific dataflow machine with unlimited parallelism to a superscalar processor running the same program. While the dataflow machines provide very good performance on most data-parallel programs, we show that the dataflow machine cannot always take advantage of the available parallelism. Using the dynamic critical path we investigate the mechanisms used by superscalar processors to provide a performance advantage and their impact on a dataflow model
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