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:用于云计算的消息传递并行应用程序的建模和仿真环境
机译:消息传递并行程序的并行直接执行仿真
机译:用于消息传递应用程序的主动乐观和分布式消息日志记录
机译:并行消息传递应用程序的乐观模拟
机译:使用乐观并行仿真的高效大型计算机和网络模型。
机译:快速多极方法中数据扩散通信模型的消息传递实现:大规模生物分子模拟
机译:消息传递并行程序的并行直接执行仿真
机译:消息传递并行程序的并行化直接执行仿真