CSR: Medium: Collaborative Research: Enabling GPUs as First-Class Computing Engines

CSR：媒介：协作研究：使 GPU 成为一流的计算引擎

• 批准号: 1409095
• 负责人: Mahmut Kandemir
• 金额: $ 48.41万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1409095&HistoricalAwards=false
• 关键词: CSR; Medium; Collaborative; Research; Enabling

Graphics Processing Units (GPUs) are rapidly bringing the computingpower traditionally associated with massively parallel supercomputersinto the mainstream devices we use today. They have the power torevolutionize computing by enabling orders of magnitude faster andmore efficient execution of many applications. Unfortunately, manymodern applications and users cannot take advantage of the computingcapability present in today's GPUs because today's GPUs are used assecondary devices to the much less powerful CPUs. As a result, the massivecomputing power of GPUs gets wasted and underutilized for a largenumber of important applications.This project aims to take a fresh and comprehensive look at GPU designwith the goal of enabling GPUs as first-class computing engines thatcan benefit an overwhelming majority of real-world applications andusers. To this end, this project systematically investigates thehardware/software design space of three new execution models, whichprogressively turn a GPU into an independent, first-class computeengine in a hybrid computing system: 1) an enhanced master-slave modelwhere the GPU is able to perform multiple-application execution, 2) anew peer-to-peer model where the GPU is autonomous of the CPU, 3) ahybrid model where GPUs and CPUs are integrated on the same die andare equals from the applications' and system's viewpoint. The projectcomprehensively develops software, hardware and software/hardwarecooperative scheduling, resource management, and system designtechniques for all three models.If successful, this project can pave the way to making GPUsfirst-class computing engines used in all aspects of our everydaylives for a majority of applications. Doing so is not only expected tolead to much higher degrees of energy efficiency and user productivitybut can also potentially enable new applications and devices that cantake advantage GPUs.

图形处理器（GPU）正在迅速将传统上与大规模并行超级计算机相关的计算能力带入我们今天使用的主流设备。它们有能力通过使许多应用程序的执行速度更快、更高效地提高几个数量级来彻底改变计算。不幸的是，许多现代应用程序和用户无法利用当今GPU的计算能力，因为今天的GPU被用作功能较弱的CPU的辅助设备。本项目旨在对GPU设计进行全新而全面的审视，旨在使GPU成为一流的计算引擎，使绝大多数现实世界的应用程序和用户受益。为此，该项目系统地研究了三种新的执行模型的硬件/软件设计空间，这些模型逐步将GPU转变为混合计算系统中独立的一流计算引擎：1）增强的主从模型，其中GPU能够执行多应用程序执行，2）新的对等模型，其中GPU独立于CPU，3）混合模型，GPU和CPU集成在同一个芯片上，从应用和系统的角度来看是平等的。该项目全面开发了这三种型号的软件、硬件和软硬件协同调度、资源管理和系统设计技术，如果成功，该项目将为使GPU成为我们日常生活的各个方面的一流计算引擎铺平道路。这样做不仅有望导致更高程度的能源效率和用户生产力，而且还可能使新的应用程序和设备能够利用GPU。