標題: Clustered affinity scheduling on large-scale NUMA multiprocessors
作者: Wang, YM
Wang, HH
Chang, RC
資訊工程學系
Department of Computer Science
公開日期: 1-十月-1997
摘要: Modern shared-memory multiprocessors have high and non-uniform memory access (NUMA) costs. The communication cost gradually dominates the source of parallel applications' execution. Algorithms based on affinity, like affinity scheduling algorithm (AFS), perform better than dynamic algorithms, such as guided self-scheduling (GSS) and trapezoid self-scheduling (TSS). However, as the number of processors increases, AFS suffers heavy overheads for migrating workload. The overheads include remote reads to the queues for the indices information, synchronous writes to the queues for migrating iterations, and the time in loading data into cache. In this paper, we propose a new loop scheduling algorithm, clustered affinity scheduling (CAFS), to improve affinity scheduling algorithm. We distribute the processors into several clusters, and cluster-based migrations are carried on when imbalance occurs. We confirm our idea by running many applications under a realistic hierarchy memory simulator. Our results show that CAFS reduces at least 1/3 of both remote reads and synchronous writes to the queues under most applications. CAFS also improves the cache hit ratios, and balances the workload. Therefore, we conclude that under large NUMA multiprocessor, CAFS is a better choice among loop scheduling algorithms. (C) 1997 Elsevier Science Inc.
URI: http://hdl.handle.net/11536/269
ISSN: 0164-1212
期刊: JOURNAL OF SYSTEMS AND SOFTWARE
Volume: 39
Issue: 1
起始頁: 61
結束頁: 70
顯示於類別:期刊論文


文件中的檔案:

  1. A1997XM94400007.pdf