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

机译:用于高性能GPU中的流式多处理器的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可以提供强大的计算能力,并用于执行图形和通用应用。硬件资源利用是确定GPGPU性能的最重要因素之一。对于GPGPU来说,多应用程序执行可以增加数据并行性,从而产生高资源利用率。但是,应用程序具有不同的执行时间,具体取决于其工作量大小。因此,如果一个应用程序早于其他应用程序,则可能发生资源未充分利用问题,因为为早期完成的应用程序分配的硬件资源变为空闲。在这项工作中,提出了一种CTA感知动态流式多处理器调度方案,用于GPGPU中的多应用程序执行,以有效地管理硬件资源。与基线架构相比,所提出的CTA感知动态SM调度方案可以平均增加GPU性能高达25.6%。

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