神经形态计算设备与应用的统一软硬件协同设计框架

J. Plank, G. Rose, Mark E. Dean, Catherine D. Schuman, N. Cady
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引用次数: 16

摘要

随着摩尔定律的消亡,计算社区正处于一个探索时期,专注于新颖的计算设备、范式和编程技术。TENN-Lab小组为这项探索开发了一个硬件/软件协同设计框架,我们在此基础上进行了三个重点的研究:(1)计算设备,如忆阻器和仿生膜。(2)使用尖峰神经网络进行处理的应用。(3)机器学习编程技术。设计框架是统一的,因为它允许所有三个重点协同工作,因此,例如,设备设计的新结果可以立即应用于应用程序和学习的当前结果。在本文中,我们详细介绍了设计框架的交织组件。然后,我们描述了上面每个研究重点的案例研究,强调了统一框架如何使每个案例研究成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Unified Hardware/Software Co-Design Framework for Neuromorphic Computing Devices and Applications
With the death of Moore's law, the computing community is in a period of exploration, focusing on novel computing devices, paradigms, and techniques for programming. The TENN-Lab group has developed a hardware/software co- design framework for this exploration, on which we perform research with three thrusts: (1) Devices for computing, such as memristors and biomimetic membranes. (2) Applications that employ spiking neural networks for processing. (3) Machine learning techniques to program. The design framework is unified, because it allows all three thrusts to work in concert, so that, for example, new results on device design can apply instantly to the current results of applications and learning. In this paper, we detail the interweaving components of the design framework. We then describe case studies on each of the research thrusts above, highlighting how the unified framework is enabling to each case study.
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