Low Depth Cache-Oblivious Algorithms

被引:0
|
作者
Blelloch, Guy E. [1 ]
Gibbons, Phillip B.
Simhadri, Harsha Vardhan [1 ]
机构
[1] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
基金
美国国家科学基金会;
关键词
Cache-oblivious algorithms; sorting; sparse-matrix vector multiply; graph algorithms; parallel algorithms; multiprocessors; schedulers;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper we explore a simple and general approach for developing parallel algorithms that lead to good cache complexity on parallel machines with private or shared caches The approach is to design nested-parallel algorithms that have low depth (span. critical path length) and for which the natural sequential evaluation order has low cache complexity in the cache-oblivious model We describe several cache-oblivious algorithms with optimal work, polylogarithmic depth, and sequential cache complexities that match the best sequential algorithms, including the first such algorithms for sorting and for sparse-matrix vector multiply on matrices with good vertex separators Using known mappings. our results lead to low cache complexities on shared-memory multiprocessors with a single level of private caches or a single shared cache We generalize these mappings to multi-level cache hierarchies of private or shared caches, implying that our algorithms also have low cache complexities on such hierarchies The key factor in obtaining these low parallel cache complexities is the low depth of the algorithms we propose.
引用
收藏
页码:189 / 199
页数:11
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