论文标题
在GPU系统上有效执行不规则消息驱动的并行应用程序的策略
Strategies for Efficient Executions of Irregular Message-Driven Parallel Applications on GPU Systems
论文作者
论文摘要
通过过度分组任务的消息驱动执行构成了并行编程的重要模型，并且已被证明针对不规则应用程序。在GPU系统上支持有效执行此类消息驱动的不规则应用程序，提出了许多与不规则数据访问和计算有关的挑战。在这项工作中，我们制定了策略，包括合并不规则的数据访问并与数据再利用结合，以及用于最小化空转的混合执行方法的自适应方法。我们已经将这些运行时策略集成到我们的{\ em G-Charm}框架中，以有效执行混合GPU系统上的消息驱动并行应用程序。我们通过N体模拟和分子动力学应用来证明我们针对不规则应用的策略，并表明我们的动态策略导致这些不规则应用的执行时间减少了8-38 \％，而对于常规应用可调节的相应静态策略。
Message-driven executions with over-decomposition of tasks constitute an important model for parallel programming and have been demonstrated for irregular applications. Supporting efficient execution of such message-driven irregular applications on GPU systems presents a number of challenges related to irregular data accesses and computations. In this work, we have developed strategies including coalescing irregular data accesses and combining with data reuse, and adaptive methods for hybrid executions to minimize idling. We have integrated these runtime strategies into our {\em G-Charm} framework for efficient execution of message-driven parallel applications on hybrid GPU systems. We demonstrate our strategies for irregular applications with an N-Body simulations and a molecular dynamics application and show that our dynamic strategies result in 8-38\% reduction in execution times for these irregular applications over the corresponding static strategies that are amenable for regular applications.
