异构集群下的MapReduce编程环境  

A Map Reduce Programming Enviornment for Hetergeneous Clusters

作　　者：吴承勇[1] 崔慧敏[1] 

机构地区：[1]中国科学院计算技术研究所

出　　处：《科技创新导报》2016年第9期170-170,共1页Science and Technology Innovation Herald

摘　　要：该报告针对Godson-D的芯片特征和亿级并发负载的特征,研究了层次化Map Reduce编程模型,对上层应用呈现简洁的编程接口,并利用Open CL来开发Godson-D芯片的计算能力。对其中的3个关键问题进行了阐述:形成了完整的层次化Map Reduce编程模型的框架,并实现了原型系统,旨在解决现有Map Reduce模型在多核/众核芯片组成的集群中存在的性能墙、在适用场景方面存在的无法适应增量式分析这两个主要的问题;为了解决Godson-D上的编程困难问题,该研究提出使用Open CL编写程序,并配套开发CPU+Godson-D异构系统中Open CL编译/运行时系统的解决方案。在该研究中,首先完成了Open CL编译/运行时支持系统的框架设计,该框架采用层次化设计思想,分为功能层、优化层、平台层;多核/众核处理器及云计算被认为将会统治计算领域的未来,多核/众核处理器在目前的云计算数据中心中被广泛采用,但是目前其资源利用率非常低,主要原因在于核间性能干扰的存在,使得数据中心的调度程序不得不禁止关键应用的co-location来保证Qo S,为此,提出了一种基于统计学习的多核间性能干扰分析方法,可以量化地分析任意程序遭受的核间性能干扰,并根据干扰模型提高资源的利用率。Based on the chip architecture and the features of highly concurrent workloads, this report discussed the hierarchical MapReduce programming model, to expose a user--friendly programming interface and leverage OpenCL to take advantange of the computing power of Godson-D processor. This report presented three key ideas in detail：（1） Existing MapReduce programming model has two disadvantages： it cannot take advantage of the computing power of underlying multi/many-core processors, and it cannot adapt for increamental analysis. To address these two problems, we proposed the hierarchical MapReduce programming framework implements a prototype.（2） To provide a user--friendly programming interface for Godson-D, we proposed a OpenCL compiler/ runtime system for Godson-D. We designed a hierarchical hetergeneous compiler/runtime system for Godson--D, which includes functional level, optimization level and platform level.（3） Despite their widespread adoption in cloud computing, multicore processors are heavily under--utilized in terms of computing resources. To avoid the potential for negative and unpredictable interference, co--location of a latency--sensitive application with others on the same multicore processor is disallowed, leaving many cores idle and causing low machine utilization. To enable co--location while providing QoS guarantees, it is challenging but important to predict performance interference between co--located applications.We proposed a regression approach to predict the interference and improve the resource utilization.

关 键 词：异构集群 编程环境 异构芯片 编译技术 

分 类 号：TP393.03[自动化与计算机技术—计算机应用技术]