Applications and Programming Models for Large-Scale Heterogeneous Computing with FPGAs

使用 FPGA 进行大规模异构计算的应用程序和编程模型

• 批准号: RGPIN-2017-06577
• 负责人: Chow, Paul
• 金额: $ 3.42万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=637688
• 关键词: Applications; Programming; Models; Large; Scale

As we enter into the era of the Cloud and the Internet of Things (IoT), issues around the power and performance of computing are becoming ever more important. Computing using microprocessors is still the mainstay of all forms of computing but microprocessors are no longer enough because they are not always the most efficient in terms of power or performance. As a result, non-traditional computing approaches are being explored with more urgency. The acquisition of Altera by Intel in 2015 for USD$16.7B has woken up the world to the benefits of using Field-Programmable Gate Arrays (FPGAs), but also made the computing world more heterogeneous. For many applications, FPGAs can provide both a performance benefit and do it with lower power requirements. The problem is that they are difficult to use. The motivation and challenge of our work is to make FPGAs accessible by all application developers. This proposal focuses on the exploration of programming models and driving applications for using distributed FPGAs in high-performance computing, but many of the techniques can also be applied at the other end of the computing spectrum in the IOT world.

随着我们进入云和物联网（IoT）时代，围绕计算能力和性能的问题变得越来越重要。使用微处理器的计算仍然是所有计算形式的支柱，但微处理器不再足够，因为它们在功率或性能方面并不总是最有效的。因此，非传统的计算方法正在探索与更紧迫。英特尔在2015年以167亿美元收购Altera，唤醒了世界使用现场可编程门阵列（FPGA）的好处，但也使计算世界变得更加异构。对于许多应用，FPGA可以提供性能优势，并以较低的功耗要求实现。问题是它们很难使用。我们工作的动机和挑战是让所有应用程序开发人员都可以访问FPGA。该提案的重点是探索在高性能计算中使用分布式FPGA的编程模型和驱动应用程序，但许多技术也可以应用于物联网世界计算频谱的另一端。