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Optimistic simulation of parallel message-passing applications

机译:并行消息传递应用程序的乐观模拟

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Optimistic techniques can improve the performance of discrete-event simulations, but one area where optimistic simulators have been unable to show performance improvement is in the simulation of parallel programs. Unfortunately parallel program simulation using direct execution is difficult: the use of direct execution implies that the memory and computation requirements of the simulator are at least as large as that of the target application, which restricts the target systems and application problem sizes that can be studied. Memory usage is especially important for optimistic simulators due to the need for periodic state-saving and rollback. In our research we addressed this problem and have implemented a simulation library running a Time-Warp-based optimistic engine that uses direct execution to simulate and predict the performance of parallel MPI programs while attaining good simulation speedup. For programs with data sets too large to be directly executed with our optimistic simulator,we reduced the memory and computational needs of these programs by utilizing a static task graph and code-slicing methodology; an approach which also exhibited good performance speedup.

机译:乐观技术可以提高离散事件仿真的性能,但是乐观仿真器无法显示性能提高的领域之一是并行程序的仿真。不幸的是,使用直接执行的并行程序模拟很困难:直接执行的使用意味着模拟器的内存和计算需求至少与目标应用程序的内存和计算需求一样大,这限制了可以研究的目标系统和应用程序问题的大小。 。由于需要定期保存状态和回滚,因此对于乐观型模拟器,内存使用尤其重要。在我们的研究中,我们解决了这个问题,并实现了一个运行基于时间扭曲的乐观引擎的仿真库,该引擎使用直接执行来仿真和预测并行MPI程序的性能,同时获得良好的仿真速度。对于数据集太大而无法使用我们的乐观模拟器直接执行的程序,我们通过使用静态任务图和代码切片方法来减少这些程序的内存和计算需求;一种表现出良好的性能提速的方法。

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