全球分布式关联环境——并行数据流计算系统“Buran”的演进

A. Ivannikov, N. Levchenko, A. Okunev, A. Stempkovsky, D. Zmejev
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引用次数: 4

摘要

实现数据流计算模型的高性能并行数据流计算系统解决了超级计算领域中存在的问题,主要是数十万计算核并行处理任务时实际性能较低。本文提出了一种新的并行数据流计算体系结构——全局分布式关联环境。描述了计算系统组织的概念,它包括将系统划分为关联计算核,而关联计算核又由一组局部关联元素组成。与以前的体系结构相比,新的体系结构显示出显著的优势,主要是由于系统可靠性的提高和编程的简化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Global Distributed Associative Environment - Evolution of Parallel Dataflow Computing System “Buran”
A high-performance parallel dataflow computing system that implements a dataflow computing model solves problems in the field of supercomputing, the main one of which is low real performance when parallelizing tasks for hundreds of thousands of computational cores. In this article, a new architecture for the parallel dataflow computing system is proposed - a global distributed associative environment. The concept of the computing system organization is described, which consists in dividing the system into associative computational cores, which in turn consist of a set of local associative elements. The new architecture demonstrates significant advantages over the previous architecture, primarily due to the increased reliability of the system and the simplification of programming.
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