CAREER: Dynamic and Autonomous Software-to-Hardware Translation for High-Performance and Low-Power Embedded Computing

职业：高性能和低功耗嵌入式计算的动态和自主软件到硬件转换

• 批准号: 0844565
• 负责人: Roman Lysecky
• 金额: $ 41.59万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-02-01 至 2015-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0844565&HistoricalAwards=false
• 关键词: CAREER; Dynamic; Autonomous; Software; Hardware

CAREER: Dynamic and Autonomous Software-to-Hardware Translation for High-Performance and Low-Power Embedded ComputingCircuits implemented using field-programmable gate arrays (FPGAs) share many of the same advantages of software solutions and provide a complimentary technology for increasing system performance of reducing power. Implementing critical kernels of a software application within an FPGA can provide substantial speedups in application execution time. However, traditional hardware/software partitioning approaches either require extensive manual efforts or rely on automated partitioning compilers that significantly depart from mainstream software development tools and practices. This CAREER project seeks to overcome these challenges by investigating and developing new methods for dynamically translating kernels within an executing application binary into circuits executing on an FPGA ? a process referred to as warp processing. Warp processing provides an innovative technology that allows FPGAs to be readily integrated into computing systems without requiring hardware design expertise, specialized tools, or even knowledge of the FPGA. This CAREER project will investigate several interrelated research problems, including: 1) dynamic application profiling, 2) dynamic optimization of multitasked applications, 3) adaptable fixed point representations for efficient support of floating point arithmetic in hardware circuits, and 4) low-power warp processing. This CAREER project also seeks to significantly improve embedded systems education through several concerted efforts aimed at training engineers to understand the fundamental similarities and differences between software and hardware implementations and enable those engineers to apply that knowledge to evaluate the tradeoffs between alternative design solutions.

职业：用于高性能和低功耗嵌入式计算的动态和自主软件到硬件转换使用现场可编程门阵列（FPGA）实现的电路具有许多软件解决方案的相同优势，并提供了一种补充技术，用于提高系统性能并降低功耗。在FPGA内实现软件应用程序的关键内核可以在应用程序执行时间方面提供实质性的加速。然而，传统的硬件/软件分区方法要么需要大量的手动工作，要么依赖于自动分区编译器，这些编译器与主流软件开发工具和实践明显不同。这个CAREER项目旨在通过调查和开发新的方法来克服这些挑战，这些方法用于动态地将执行应用程序中的内核二进制转换为在FPGA上执行的电路。一种称为翘曲处理的工艺。Warp处理提供了一种创新技术，使FPGA能够轻松集成到计算系统中，而无需硬件设计专业知识，专业工具甚至FPGA知识。这个CAREER项目将研究几个相关的研究问题，包括：1）动态应用程序分析，2）多任务应用程序的动态优化，3）可适应的定点表示，以有效支持硬件电路中的浮点运算，以及4）低功耗翘曲处理。该CAREER项目还旨在通过几项旨在培训工程师了解软件和硬件实现之间的基本相似性和差异的协同努力来显着改善嵌入式系统教育，并使这些工程师能够应用这些知识来评估替代设计解决方案之间的权衡。