Dynamic task discovery in PaRSEC: a data-flow task-based runtime
Dynamic task discovery in PaRSEC: a data-flow task-based runtime
复制标题
PaRSEC 中的动态任务发现：基于数据流任务的运行时
DOI：
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发表时间：
2017
期刊：
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通讯作者：
J. Dongarra
中科院分区：
文献类型：
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作者：
Reazul Hoque;T. Hérault;G. Bosilca;J. Dongarra
通过可移植编程模型成功利用具有复杂内存层次结构的异构多核架构的分布式集合是应用程序开发人员面临的一个挑战。文献中不乏解决此问题的建议，包括许多寻求扩展具有节点内特征（MPI+X）的当前消息传递范例功能的进化解决方案。一种不同的、更具革命性的解决方案探索了基于数据流任务的运行时系统，作为本地和分布式数据依赖关系管理的替代品。本文探讨的解决方案PaRSEC就是基于这样的编程范例，并由高效的基于任务的运行时提供支持。本文比较了PaRSEC中存在的两种编程范式，参数化任务图（PTG）和动态任务发现（DTD）在功能、开销和潜在收益方面的差异。
Successfully exploiting distributed collections of heterogeneous many-cores architectures with complex memory hierarchy through a portable programming model is a challenge for application developers. The literature is not short of proposals addressing this problem, including many evolutionary solutions that seek to extend the capabilities of current message passing paradigms with intra-node features (MPI+X). A different, more revolutionary, solution explores data-flow task-based runtime systems as a substitute to both local and distributed data dependencies management. The solution explored in this paper, PaRSEC, is based on such a programming paradigm, supported by a highly efficient task-based runtime. This paper compares two programming paradigms present in PaRSEC, Parameterized Task Graph (PTG) and Dynamic Task Discovery (DTD) in terms of capabilities, overhead and potential benefits.