XPS: FULL:CCA: Extracting Scalable Parallelism by Relaxing the Contracts across the System Stack

技术扩展趋势已经使并行性成为事实上的标准，用于提高从高端计算到嵌入式平台的各种计算环境的性能。然而，软件在提取底层硬件平台提供的可用并行性方面严重滞后，这主要是因为系统堆栈不同层之间的划分合同。刚性契约限制了在层内和层间利用丰富的性能/功耗/正确性权衡设计空间的能力，这可以通过稍微偏离契约来实现。虽然这种被称为近似计算的宽松契约最近受到了关注，但这一领域的大部分工作仍然是划分的，缺乏一个整体的跨层策略来最大限度地提高并行性，同时坚持权力和正确性要求。 因此，这个项目的动机是探索一个整体的跨层方法，以近似计算跨越应用程序，运行时系统，编译器和硬件，从而打破了刚性的合同层之间，同时仍然允许他们合作，提取可实现的并行跨不同的应用程序集在高端和移动的计算环境。具体来说，它涉及对计算、数据访问和同步的逼近范围的应用程序级分析，设计可以促进逼近并从中受益的高效硬件机制，以及开发用于表达、利用和评估/验证逼近的编译器和运行时支持。以架构感知的方式。这种跨层近似计算方法预计将在未来十年及以后实现可扩展并行性方面发挥关键作用，对计算行业具有潜在的重大影响。此外，从这个项目开发的工具和模型在公共领域传播到更广泛的研究界，PI参与各种外联活动，如招募妇女和少数民族，并通过宾夕法尼亚州立大学Eberly学院的Exploration-U倡议让当地高中生参与。

Technology scaling trends have made parallelism the de-facto standard for enhancing performance across a spectrum of computing environments spanning from high-end computing to embedded platforms. Yet, the software is woefully lagging in its ability to extract usable parallelism offered by the underlying hardware platforms primarily because of the compartmentalized contracts between the different layers of the system stack. Rigid contracts restrict the ability to leverage a rich design space of performance/power/correctness trade-offs within and across layers, that could be achievable by straying slightly from the contract. Although such a relaxed contract, referred to as approximate computing, has received attention recently, much of the work in this area is still compartmentalized and lacks a holistic cross-layer strategy to maximize parallelism, while adhering to power and correctness mandates. Thus, the motivation of this project is to explore a holistic cross-layer approach to approximate computing spanning application, runtime system, compiler and hardware, thereby breaking the rigidity of the contracts between the layers, while still allowing them to cooperate for extracting the achievable parallelism across a diverse set of applications in both the high-end and mobile computing environments. Specifically, it involves application-level analysis of the scope of approximation for computation, data access and synchronization, designing efficient hardware mechanisms that could facilitate and benefit from approximation, and developing compiler and runtime support for expressing, exploiting and evaluating/validating the approximations in an architecture-aware fashion. This cross-layer approach to approximate computing is expected to play a crucial role towards achieving scalable parallelism for the next decade and beyond, with a potentially high impact to the computing industry. In addition, the tools and models developed from this project are disseminated in the public domain to a broader research community, and the PIs engage in a variety of outreach activities such as recruiting women and minority and involvement of local high school students through Penn State Eberly College's Exploration-U initiatives.