SI2-SSI: Collaborative: The XScala Project: A Community Repository for Model-Driven Design and Tuning of Data-Intensive Applications for Extreme-Scale Accelerator-Based Systems

SI2-SSI：协作：XScala 项目：用于基于超大规模加速器的系统的模型驱动设计和数据密集型应用程序调整的社区存储库

• 批准号: 1339745
• 负责人: David Bader
• 金额: $ 118.87万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1339745&HistoricalAwards=false
• 关键词: SI2; SSI; Collaborative; XScala; Project; SI2; SSI; Collaborative; XScala; Project

The increasing gap between processor and memory performance -- referred to as the memory wall -- has led high-performance computing vendors to design and incorporate new accelerators into their next-generation systems. Representative accelerators include reconfigurable hardware such as FPGAs, heterogeneous processors such as CPU+GPU processors, highly multicore and multithreaded processors, and manycore co-processors and general-purpose graphics processing units, among others. These accelerators contain myriad innovative architectural features, including explicit control of data motion, large-scale SIMD/vector processing, and multithreaded stream processing. Such features provide abundant opportunities for developers to achieve high-performance for applications that were previously deemed hard to optimize. This project aims to develop tools that will assist developers in using hardware accelerators (co-processors) productively and effectively. This project's specific technical focus is on data-intensive kernels including large dictionary string matching, dynamic programming, graph theory, and sparse matrix computations that arise in the domains of biology, network security, and the social sciences. The project is developing XScala, a software framework for designing efficient accelerator kernels. The framework contains a variety of design time and run-time performance optimization tools. The project concentrates on data-intensive kernels, bound by data movement. It proposes optimization techniques including (a) enhancing and exploiting maximal concurrency to hide data movement; (b) algorithmic reorganization to improve spatial and/or temporal locality; (c) data structure transformations to improve locality or reduce the size of the data (compressed structures); and (d) prefetching, among others. The project is also developing a public software repository and forum, called the XBazaar, for community-developed accelerator kernels. This project includes workshops, tutorials, and the PIs class and summer projects as various means by which to increase community involvement. The broader impacts include productive use of emerging classes of accelerator-augmented computer systems; creation of an open and accessible community repository, the XBazaar, for distributing accelerator-tuned computational kernels, software, and models; training of graduate and undergraduate students; and dissemination through publications, presentations at scientific meetings, lectures, workshops, and tutorials. The framework itself will be released as open-source code and as precompiled binaries for several common platforms, through the XBazaar, as an initial step toward building a community around accelerator kernels.

处理器和内存性能之间的差距增加（称为内存墙）导致高性能计算供应商设计并将新的加速器纳入其下一代系统。代表性的加速器包括Recon＆＃64257;可达的硬件，例如FPGA，异质处理器，例如CPU+GPU处理器，高度多层和多线程处理器，以及Manuscore的处理器以及多项处理的处理器以及通用用途图形处理单位。这些加速器包含无数创新的体系结构特征，包括对数据运动的明确控制，大规模的SIMD/向量处理以及多线程流处理。这些功能为开发人员提供了丰富的机会，可以为以前被认为难以优化的应用实现高性能。该项目旨在开发工具，以帮助开发人员有效，有效地使用硬件加速器（联合处理器）。该项目的特定技术重点是数据密集型内核，包括大型词典字符串匹配，动态编程，图形论以及在生物学，网络安全和社会科学领域中出现的稀疏矩阵计算。该项目正在开发Xscala，这是一个用于设计有效加速器内核的软件框架。该框架包含各种设计时间和运行时性能优化工具。该项目集中于数据流动限制的数据密集型内核。它提出了优化技术，包括（a）增强和利用最大并发性以隐藏数据移动； （b）算法重组以改善空间和/或时间位置； （c）数据结构转换以改善局部性或减少数据的大小（压缩结构）； （d）预摘要等。该项目还开发了一个公共软件存储库和论坛，称为XBAZAAR，用于社区开发的加速器内核。该项目包括研讨会，教程以及PIS类和夏季项目，作为增加社区参与的各种方式。更广泛的影响包括促进加速器增强计算机系统的新兴类别的生产性使用；创建开放且易于访问的社区存储库XBAZAAR，用于分发加速器调整的计算内核，软件和模型；培训研究生和本科生；以及通过出版物，科学会议，讲座，讲习班和教程的演讲进行传播。该框架本身将作为开源代码发布，并通过Xbazaar作为几个通用平台的预编译二进制文件，这是朝着加速器内核建立社区的第一步。