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

这个I-Corps项目的更广泛的影响/商业潜力是为科学计算应用开发更快的微处理器。目前，科学计算在很大程度上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提供最佳性能。在所提出的技术中，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的方式来更轻松地运行他们的模拟。此外，所提出的技术可以提供与多种类型的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关注图形的图形处理单元。专用微处理器设计可适用于便携式仪器设备中的低功率应用。 预计定制芯片将被集成到广泛的应用领域，如航空航天，制药和多物理系统的实时和预测控制的需要。这个I-Corps项目是基于特定应用微处理器的开发，包括一个强大的编程框架。所提出的技术解决了相关算法的开发，以分析目标软件应用程序的计算行为。为该项目开发的专用微处理器将主要侧重于加速微分方程的数值求解。 微分方程构成了许多计算动力学系统的数学基础，以快速有效的方式求解它们是很重要的。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。这些发展的交叉促进了目标应用特定微处理器设计的低成本开发。 初步结果表明，所设计的硬件加速器达到高达4.8倍的加速比，在成本只有13.3%以上的硬件资源和8.1%的额外功耗。 将来，也有可能设计出能够在机载测量仪器上进行信号分析的低功耗微处理器。该奖项反映了NSF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.