Self-scheduling on distributed-memory machines
Self-scheduling on distributed-memory machines
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DOI：
10.1145/169627.169841
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发表时间：
1993-12
期刊：
影响因子：
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通讯作者：
J. Liu-;V. Saletore
中科院分区：
文献类型：
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作者：
J. Liu-;V. Saletore
作者提出了一种通用的方法，自调度的非均匀并行循环上的分布式存储器的机器。该方法有两个阶段：静态调度阶段和动态调度阶段。除了减少调度开销之外，使用静态调度阶段还允许预取静态调度迭代所需的数据。动态调度阶段平衡工作负载。自调度的数据分发方法也是本文的重点。作者将数据分布方法分为四类，并提出部分重复，这种方法允许问题的大小在处理器的数量上线性增长。在一个64节点的NCUBE上进行的实验表明，高达79%的改善是实现了静态调度上的假彩色图像的生成。
The authors present a general approach of self-scheduling a non-uniform parallel loop on a distributed-memory machine. The approach has two phases: a static scheduling phase and a dynamic scheduling phase. In addition to reduce scheduling overhead, using the static scheduling phase allows the data needed by the statically scheduled iterations to be prefetched. The dynamic scheduling phase balances the workload. Data distribution methods for self-scheduling are also the focus of this paper. The authors classify the data distribution methods into four categories and present partial duplication, a method that allows the problem size to grow linearly in the number of processors. The experiments conducted on a 64-node NCUBE show that as much as 79% improvement is achieved over static scheduling on the generation of a false-color image.