Enabling FPGAs in new HPC heterogeneous systems through dataflow abstractions and enhanced flexibility

通过数据流抽象和增强的灵活性在新的 HPC 异构系统中启用 FPGA

• 批准号: 2608171
• 金额: --
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2608171
• 关键词: Enabling; FPGAs; new; HPC; heterogeneous

Scientific computing makes extensive use of the very large collections of hardware resources found inHPC systems. The ever growing demand of this domain requires the search of new strategies to deal withincreasing amounts of data in feasible time to solution. One of these strategies is the use of FPGAs, since theirreconfigurability allows them to overcome some of the limitations faced by the traditional HPC hardware. However, programming themrequires specific knowledge foreign to HPC software developers and they are also very rigid, which hinders their integration in HPCsystems.Our hypothesis is that improved tooling for FPGAs with HPC workloads in mind will result in the technology better suiting supercomputing.To answer this research question we focus both on the issues of performance and flexibility. The architecture of the FPGA maps better to adataflow approach than the traditional programming languages. Hence, we are exploring the performance improvements provided by a dataflow layerexposed to the programmer. At the same time, we are looking into how advanced reconfiguration techniques help dynamic management of the workloads on FPGA and allow to overcome their native rigidity.

科学计算广泛使用HPC系统中的大量硬件资源。这一领域不断增长的需求需要寻找新的策略来处理越来越多的数据在可行的时间解决方案。这些策略之一是使用FPGA，因为它们的可重新配置性使它们能够克服传统HPC硬件面临的一些限制。然而，它们的编程需要专门的知识外国HPC软件开发人员，他们也是非常僵化，这阻碍了他们在HPC systems.We的假设是，提高工具的FPGA与HPC工作负载的想法将导致技术更好地适应超级计算。FPGA的体系结构比传统的编程语言更好地映射到adataflow方法。因此，我们正在探索由暴露给程序员的低层提供的性能改进。与此同时，我们正在研究先进的重新配置技术如何帮助动态管理FPGA上的工作负载，并克服其固有的刚性。