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Fast and efficient automatic memory management for GPUs using compiler-assisted runtime coherence scheme

机译:使用编译器辅助的运行时一致性方案对GPU进行快速高效的自动内存管理

摘要

ududExploiting the performance potential of GPUs requires managing the data transfers to and from them efficiently which is an error-prone and tedious task. In this paper, we develop a software coherence mechanism to fully automate all data transfers between the CPU and GPU without any assistance from the programmer. Our mechanism uses compiler analysis to identify potential stale accesses and uses a runtime to initiate transfers as necessary. This allows us to avoid redundant transfers that are exhibited by all other existing automatic memory management proposals.udWe integrate our automatic memory manager into the X10 compiler and runtime, and find that it not only results in smaller and simpler programs, but also eliminates redundant memory transfers. Tested on eight programs ported from the Rodinia benchmark suite it achieves (i) a 1.06x speedup over hand-tuned manual memory management, and (ii) a 1.29x speedup over another recently proposed compiler--runtime automatic memory management system. Compared to other existing runtime-only and compiler-only proposals, it also transfers 2.2x to 13.3x less data on average.
机译:ud ud要充分利用GPU的性能潜力,需要高效地管理往返GPU的数据传输,这是一个容易出错且繁琐的任务。在本文中,我们开发了一种软件一致性机制,可以完全自动化CPU和GPU之间的所有数据传输,而无需程序员的任何帮助。我们的机制使用编译器分析来识别潜在的过时访问,并根据需要使用运行时来启动传输。这使我们避免了所有其他现有的自动内存管理建议所表现出的冗余传输。 ud我们将自动内存管理器集成到X10编译器和运行时中,发现它不仅导致程序更小,更简单,而且消除了冗余内存传输。在Rodinia基准套件中移植的八个程序上进行了测试,它达到(i)比手动调整的手动内存管理快1.06倍,以及(ii)比另一个最近提出的编译器-运行时自动内存管理系统快1.29倍。与其他现有的仅运行时和仅编译器建议相比,它平均传输的数据量也要少2.2倍至13.3倍。

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