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

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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.