CAREER: Architectural Support for CPU / GPU Hybridization

当今处理器行业面临的基本挑战之一是，在能源和程序员效率的限制下，继续满足性能和可扩展性要求。这个职业项目建立在最近推出的融合设计的基础上，该设计将传统微处理器和图形处理器整合到同一封装中，以便通过开发更可编程、更灵活、更可扩展和更安全的混合架构来应对这些挑战。为了实现这一长期目标，该项目研究了将传统协处理模型的局限性降至最低的技术，包括性能瓶颈、易受攻击的共享内存空间和僵化的资源管理。具体地说，该项目探讨了复杂的控制流和内存访问导致的线程分歧、核心之间的线程迁移、针对传统图形处理之外的任务的硬件加速器设计，以及添加安全保障以匹配当前在传统微处理器上可用的安全保护。此外，该项目还研究了各种指令集扩展、加速器体系结构和计算模型，这些都有可能显著提高效率和程序员的灵活性。预计的影响是，这个职业项目有朝一日将以计算行业另一个新细分市场的形式结出硕果，这个细分市场专门研究混合架构，可以扩展到数千个独立线程，同时保持传统的多用户操作系统和中间件的功能。一般而言，通过推进最先进的计算机体系结构，这项研究将导致消费类设备在尺寸和外形因素、能效和电池寿命以及支持的应用程序的复杂性和图形保真度方面的改进。同样，使用这些架构来实现持续的性能扩展有可能产生广泛的社会影响，因为这些领域(例如生物信息学、气候建模、商业智能)利用高性能计算来实现创新发现。该项目还包括重点扩展PI开发的现有课程，该课程采用了一种新颖的方法，从硬件设计的角度介绍图形处理和架构。

One of the fundamental challenges facing the processor industry today is in continuing to address performance and scalability demands given the constraints of both energy and programmer efficiency. This CAREER project builds upon recently-introduced fused designs, which incorporate conventional microprocessors and graphics processors in the same package, in order to address these challenges through the development of more programmable, flexible, scalable, and secure hybrid architectures. Towards this long-term goal, this project investigates techniques that minimize limitations of the traditional coprocessing model, including performance bottlenecks, vulnerable shared memory spaces, and inflexible resource management. Specifically, this project explores thread divergence caused by complex control-flow and memory access, thread migration between cores, hardware accelerator design for tasks beyond traditional graphics processing, and adding security safeguards to match what is currently available on conventional microprocessors. In addition, this project also examines a variety of instruction set extensions, accelerator architectures, and models of computation that have the potential to lead to significant efficiency and programmer flexibility improvements. The expected impact is that this CAREER project will one day bear fruit in the form of another new segment of the computing industry, one that specializes in hybrid architectures that can scale to thousands of independent threads, while maintaining the capabilities of a traditional multi-user operating system and middleware. Broadly speaking, by advancing the state-of-the-art in computer architecture, this research will lead to improvements in consumer devices in terms of size and form factor, energy efficiency and battery life, and complexity and graphical fidelity of supported applications. Similarly, the usage of these architectures to enable continued performance scaling has the potential to have wide-ranging societal impact, through the advancement of those fields (e.g. bioinformatics, climate modeling, business intelligence) that utilize high-performance computing to enable innovative discovery. This project also includes a focus on expanding an existing course that the PI has developed, that takes a novel approach in introducing graphics processing and architecture from a hardware design perspective.