.png){kind=icon}
返回
Tlib -: a library to support programming with hierarchical multi-processor tasks
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jpdc.2004.10.006.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The paper considers the modular programming with hierarchically structured multi-processor tasks on top of SPMD tasks for distributed memory machines. The parallel execution requires a corresponding decomposition of the set of processors into a hierarchical group structure onto which the tasks are mapped. The result is a multi-level group SPMD computation model with varying processor group structures. The advantage of this kind of mixed task and data parallelism is a potential to reduce the communication overhead and to increase scalability. We present a runtime library to support the coordination of hierarchically structured multi-processor tasks. The library exploits an extended parallel group SPMD programming model and manages the entire task execution including the dynamic hierarchy of processor groups. The library is built on top of MPI, has an easy-to-use interface, and leads to only a marginal overhead while allowing static planning and dynamic restructuring. (c) 2004 Elsevier Inc. All rights reserved.
Keyword:
mixed task and data parallelism
multi-processor tasks
multilevel group SPMD
hierarchical decomposition of processor sets
library support
distributed memory
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4
论文数:
3.8K
被引数:
4.8K
机构
暂无机构信息
引用论文
Optimal DSI reconstruction parameter recommendations: Better ODFs and better connectivity.png)
NeuroImage
NeuroImageIF0
PREAI
分享收藏Experimental Measurement of P-wave Attenuation Due to Fractures Over the 100 to 300 kHz Bandwidth
PREAI
分享收藏
分享收藏
查看更多内容