The Open Community Runtime: A runtime system for extreme scale computing

The Open Community Runtime: A runtime system for extreme scale computing
复制标题

开放社区运行时：用于超大规模计算的运行时系统

DOI：
--
复制
发表时间：
2016
期刊：
IEEE Conference on High Performance Extreme Computing
影响因子：
--
通讯作者：
Nick Vrvilo
Nick Vrvilo
中科院分区：
--
文献类型：
--
作者：
T. Mattson;R. Cledat;Vincent Cavé;Vivek Sarkar;Zoran Budimlic;S. Chatterjee;J. Fryman;Ivan B. Ganev;Rob C. Knauerhase;Min Lee;Benoît Meister;Brian R. Nickerson;Nick Pepperling;B. Seshasayee;Sagnak Tasirlar;J. Teller;Nick Vrvilo

文献摘要

被引文献

相似文献

开放社区运行时(Open Community Runtime，OCR)是一个新的运行时系统，旨在满足极端规模计算的需求。虽然越来越多的人支持未来的执行模型将基于动态任务的想法，但对于应该包括哪些其他内容，几乎没有达成一致意见。OCR最小限度地增加了用于同步的事件和用于数据管理的可重定位数据块，以形成支持广泛的高级编程模型的完整系统。本文阐述了OCR背后的基本概念，并通过两个简单的基准比较了OCR和MPI的性能。OCR是在开放的社区模型中开发的，其支持灵活的算法表达的功能与极限规模计算的预期现实进行了权衡：功率受限的执行、计算资源数量的急剧增长、加深的内存层次结构和较低的平均无故障时间。
The Open Community Runtime (OCR) is a new runtime system designed to meet the needs of extreme-scale computing. While there is growing support for the idea that future execution models will be based on dynamic tasks, there is little agreement on what else should be included. OCR minimally adds events for synchronization and relocatable data-blocks for data management to form a complete system that supports a wide range of higher-level programming models. This paper lays out the fundamental concepts behind OCR and compares OCR performance to that from MPI for two simple benchmarks. OCR has been developed within an open community model with features supporting flexible algorithm expression weighed against the expected realities of extreme-scale computing: power-constrained execution, aggressive growth in the number of compute resources, deepening memory hierarchies and a low mean-time between failures.