第三届MapReduce及Beyond算法与系统研讨会报告(BeyondMR’16)

F. Afrati, J. Hidders, C. Ré, J. Sroka, J. Ullman
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引用次数: 1

摘要

本报告总结了第三届MapReduce和Beyond算法和系统研讨会(BeyondMR'16)的演讲和讨论。BeyondMR研讨会与2016年SIGMOD会议于2016年7月1日在美国加利福尼亚州旧金山举行。研讨会的目标是将研究人员和实践者聚集在一起,探索需要大规模并行化的系统的算法、计算模型、体系结构、语言和接口,以及旨在支持高效并行化和容错的系统。其中包括基于MapReduce及其扩展的专门编程和数据管理系统、图形处理系统、数据密集型工作流和数据流系统。该项目邀请了来自AMPLab、加州大学伯克利分校的Ion Stoica和来自华盛顿大学的Carlos Guestrin进行了两场非常受欢迎的演讲。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Report from the third workshop on Algorithms and Systems for MapReduce and Beyond (BeyondMR'16)
This report summarizes the presentations and discussions of the third workshop on Algorithms and Systems for MapReduce and Beyond (BeyondMR'16). The BeyondMR workshop was held in conjunction with the 2016 SIGMOD conference in San Francisco, California, USA on July 1, 2016. The goal of the workshop was to bring together researchers and practitioners to explore algorithms, computational models, architectures, languages and interfaces for systems that need largescale parallelization and systems designed to support efficient parallelization and fault tolerance. These include specialized programming and data-management systems based on MapReduce and extensions, graph processing systems, data-intensive workflow and dataflow systems. The program featured two very well attended invited talks by Ion Stoica from AMPLab, University of California Berkeley and Carlos Guestrin from the University of Washington.
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