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Hybrid work stealing of locality-flexible and cancelable tasks for the APGAS library

机译:APGAS库的混合工作窃取本地灵活且可取消的任务

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Since large parallel machines are typically clusters of multicore nodes, parallel programs should be able to deal with both shared memory and distributed memory. This paper proposes a hybrid work stealing scheme, which combines the lifeline-based variant of distributed task pools with the node-internal load balancing of Java's Fork/Join framework. We implemented our scheme by extending the APGAS library for Java, which is a branch of the X10 project. APGAS programmers can now spawn locality-flexible tasks with a new asyncAny construct. These tasks are transparently mapped to any resource in the overall system, so that the load is balanced over both nodes and cores. Unprocessed asyncAny-tasks can also be cancelled. In performance measurements with up to 144 workers on up to 12 nodes, we observed near linear speedups for four benchmarks and a low overhead for cancellation-related bookkeeping.
机译:由于大型并行机通常是多核节点的群集,因此并行程序应该能够处理共享内存和分布式内存。本文提出了一种混合工作窃取方案,该方案将基于生命线的分布式任务池变体与Java的Fork / Join框架的节点内部负载平衡相结合。我们通过扩展Java的APGAS库(这是X10项目的一个分支)来实现我们的方案。 APGAS程序员现在可以使用新的asyncAny构造产生可灵活执行本地性的任务。这些任务透明地映射到整个系统中的任何资源,以便在节点和核心上平衡负载。也可以取消未处理的asyncAny-tasks。在多达12个节点上最多144个工作人员的性能测量中,我们观察到四个基准的线性加速接近,而取消相关簿记的开销却很低。

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