I-Corps: Hardware Acceleration of Scientific Computing and Intelligent Instrumentation

这个I-Corps项目更广泛的影响/商业潜力是为科学计算应用开发更快的微处理器。目前，科学计算严重依赖于由大型通用微处理器集群组成的超级计算机。这种方法是昂贵的，并且不能为科学计算应用程序提供最佳性能。在提议的技术中，正在开发的硬件软件框架可以为物理学家，生物学家，化学家，环境科学家和跨学科研究人员提供更快，更轻松地运行模拟的更快方法。此外，所建议的技术可以提供与多种微处理器集成的更丰富的计算系统，而不仅仅是通用微处理器或以图形为中心的图形处理单元。专门的微处理器设计可能适用于便携式仪器设备的低功耗应用。预计定制芯片将集成到广泛的应用领域，如需要实时和预测控制的航空航天，制药和多物理场系统。这个I-Corps项目是基于特定应用程序微处理器的开发，包括一个健壮的编程框架。提出的技术解决了相关算法的发展，以分析目标软件应用程序的计算行为。为这个项目开发的专用微处理器将主要集中在加速微分方程的数值解上。微分方程是许多计算动力学系统的数学基础，快速有效地求解微分方程是非常重要的。开源指令集架构的普及使新的微处理器设计成为可能，而现场可编程门阵列（FPGA）技术的进步使快速原型和评估成为可能。这些发展的交集促进了低成本目标应用特定微处理器设计的发展。初步结果表明，所设计的硬件加速器在仅增加13.3%的硬件资源和8.1%的额外功耗的情况下，实现了高达4.8倍的加速。在未来，也有可能设计出低功耗的微处理器，可以执行机载测量仪器的信号分析。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is the development of faster microprocessors for scientific computing applications. Currently, scientific computing relies heavily on supercomputers comprised of large clusters of general-purpose microprocessors. Such an approach is expensive, and does not deliver the optimal performance for scientific computing applications. In the proposed technology, the hardware-software framework under development may provide a faster way for physicists, biologists, chemists, environmental scientists, and interdisciplinary researchers to run their simulations faster, and with greater ease. In addition, the proposed technology may provide for more enriched computing systems integrated with multiple types of microprocessors, not simply general-purpose microprocessors or graphics-focused graphics processing units. Specialized microprocessor designs may be suitable for low-power applications in portable instrumentation devices. It is anticipated that customized chips to be integrated into a broad array of application areas such as aerospace, pharmaceutical and multi-physics systems with a need for real-time and predictive control.This I-Corps project is based on the development of application-specific microprocessors including a robust programming framework. The proposed technology addresses the development of relevant algorithms to analyze the computational behavior of targeted software applications. The application-specific microprocessors developed for this project will focus primarily on accelerating the numerical solution of differential equations. Differential equations form the mathematical basis for many computational dynamics systems, and it is important to solve them in a rapid and efficient manner. The popularization of open-source instruction set architectures has enabled new microprocessor design while the advancement of field programmable gate array (FPGA) technology has enabled rapid prototyping and evaluation. The intersection of these developments has facilitated development of target application-specific microprocessor designs at low cost. Initial results have shown that the designed hardware accelerator attains up to 4.8x speedup, at the cost of merely 13.3% more hardware resources and 8.1% additional power dissipation. In the future, it also may be possible to design low-power microprocessors that can perform signal analysis on-board measurement instruments.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.