CAREER: Accessible Accelerators: Leveraging Productive Software on Efficient Hardware

未来的经济依赖于软件、编写它的人和运行它的硬件。在过去的几十年里，计算机行业出现了两种截然相反的趋势。在软件级别，对简单性、可重用性和程序员生产力的渴望将软件中的抽象级别推到了更高的级别，将大多数程序员从了解底层机器的负担中解脱出来。在硬件层面，对性能和能效的需求导致了可编程硬件加速器的发展。然而，将抽象程序移植到加速器所需的工作是采用它们的一个重大障碍，特别是对于那些不想创建不可移植的、加速器特定的代码的通才程序员来说。该项目旨在通过开发新的跨堆栈技术来同时解决这些挑战，以在高效的硬件上加速生产软件。该项目旨在增加可以从节能、加速计算中受益的个人数量和问题。综合教育计划通过图形加速器和视频游戏向K-12学生介绍加速，同时教导大学本科生和毕业生思考如何通过空间思维将问题映射到加速器。具体地说，该项目专注于改善与提高程序员生产力的成熟软件原则相关的管理费用，并找到创新的方法来改进硬件加速器，以支持生产实践。该项目首先在大规模并行的面向对象代码中探索新的优化机会，其中对象数据布局和调用虚拟函数的高成本会降低性能。该项目将开发轻量级的虚拟函数省略机制、支持并行性的编译过程、支持加速器的虚拟内存系统，以及协调一致的跨栈工作，以减少内存压力。最后，该项目将探索在加速器上使用生产性语言的全系统解决方案，聚合项目的创新，并提供一个开源平台来简化加速器软件的开发。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The economy of the future relies on software, the people who will write it, and the hardware that will run it. The last several decades have given rise to two opposing trends in the computing industry. At the software level, a desire for simplicity, reusability, and programmer productivity has pushed the level of abstraction in software to higher levels, removing most programmers from the burden of understanding the underlying machine. At the hardware level, the demand for both performance and energy-efficiency has led to the development of programmable hardware accelerators. However, the effort required to port abstract programs to accelerators is a significant barrier to their adoption, particularly for generalist programmers that have little desire to create un-portable, accelerator-specific code. This project aims to address these challenges in tandem by developing novel cross-stack techniques to accelerate productive software on efficient hardware. The project aims to increase the number of individuals and problems that can benefit from energy-efficient, accelerated computing. An integrated education plan introduces K-12 students to acceleration through graphics accelerators and video games while teaching college undergraduates and graduates to think about how problems map to accelerators by thinking spatially.Concretely, this project focuses on ameliorating the overheads associated with well-established software principles that increase programmer productivity and finding innovative ways to improve hardware accelerators to support productive practices. The project first explores new optimization opportunities in massively parallel, object-oriented code where object data layout and the high cost of invoking virtual functions degrade performance. The project will develop lightweight, virtual function elision mechanisms, parallelism-aware compilation passes, an accelerator-aware virtual memory system, and a coordinated cross-stack effort to reduce memory pressure. Finally, the project will explore a full-system solution for productive languages on accelerators, aggregate the project's innovations, and provide an open-source platform to ease accelerator software development.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.