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CTA-Aware Dynamic Scheduling Scheme for Streaming Multiprocessors in High-Performance GPUs

机译:用于高性能GPU中流式处理多处理器的CTA感知动态调度方案

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GPGPUs can provide powerful computational capability and are employed to execute both graphics and general-purpose applications. Hardware resource utilization is one of the most important factors in determining the GPGPU performance. For GPGPUs, multiple-application execution can increase the data parallelism, resulting in high resource utilization. However, applications have different execution time depending on their workload sizes. Therefore, if one application is completed earlier than the other ones, resource underutilization problem may happen because the hardware resource allocated for the early completed application become idle. In this work, a CTA-aware dynamic streaming multiprocessors scheduling scheme is proposed for multiple-application execution in the GPGPU to efficiently manage hardware resources. Compared to the baseline architecture, the proposed CTA-aware dynamic SM scheduling scheme can increase GPU performance by up to 25.6% on average.
机译:GPGPU可提供强大的计算能力,可用于执行图形和通用应用程序。硬件资源利用率是确定GPGPU性能的最重要因素之一。对于GPGPU,多应用程序执行可以提高数据并行性,从而提高资源利用率。但是,应用程序根据其工作负载大小具有不同的执行时间。因此,如果一个应用程序比其他应用程序更早完成,则可能会出现资源利用不足的问题,因为分配给较早完成的应用程序的硬件资源变得空闲。在这项工作中,提出了一种CTA感知的动态流多处理器调度方案,用于GPGPU中的多应用程序执行,以有效地管理硬件资源。与基准架构相比,建议的CTA感知动态SM调度方案可以将GPU性能平均提高多达25.6%。

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