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A comparison of task pools for dynamic load balancing of irregular algorithms

机译:不规则算法的动态负载均衡任务池比较

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Since a static work distribution does not allow for satisfactory speed-ups of parallel irregular algorithms, there is a need for a dynamic distribution of work and data that can be adapted to the runtime behavior of the algorithm. Task pools are data structures which can distribute tasks dynamically to different processors where each task specifies computations to be performed and provides the data for these computations. This paper discusses the characteristics of task-based algorithms and describes the implementation of selected types of task pools for shared-memory multiprocessors. Several task pools have been implemented in C with POSIX threads and in Java. The task pools differ in the data structures to store the tasks, the mechanism to achieve load balance, and the memory manager used to store the tasks. Runtime experiments have been performed on three different shared-memory systems using a synthetic algorithm, the hierarchical radiosity method, and a volume rendering algorithm.
机译:由于静态工作分配不允许令人满意的并行不规则算法加速,因此需要一种动态分配的工作和数据,以适应算法的运行时行为。任务池是可以将任务动态分配到不同处理器的数据结构,其中每个任务指定要执行的计算并为这些计算提供数据。本文讨论了基于任务的算法的特征,并介绍了共享内存多处理器的选定类型任务池的实现。在带有POSIX线程的C和Java中已经实现了几个任务池。任务池的不同之处在于用于存储任务的数据结构,实现负载平衡的机制以及用于存储任务的内存管理器。使用合成算法,分层光能传递方法和体绘制算法,已经在三个不同的共享内存系统上执行了运行时实验。

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