Low Power Computing and Simultaneous Electro-Optical/Radar Data Processing using IBM’s NS16e 16-chip Neuromorphic Hardware

Mark D. Barnell, Courtney Raymond, Daniel Brown, Matthew Wilson, Éric Côté
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Abstract

For the first time ever, advanced machine learning (ML) compute architectures, techniques, and methods were demonstrated on United States Geological Survey (USGS) optical imagery and Department of Defense (DoD) Synthetic Aperture Radar (SAR) imagery, simultaneously, using IBM’s new NS16e neurosynaptic processor board comprised of 16 TrueNorth chips. The Air Force Research Laboratory (AFRL) Information Directorate Advanced Computing and Communications Division continues to develop and demonstrate new bio-inspired computing algorithms and architectures, designed to provide advanced, ultra-low power, ground and airborne High-Performance Computing (HPC) solutions to meet operational and tactical, real-time processing needs for Intelligence, Surveillance, and Reconnaissance (ISR) missions on small form factor hardware, and in Size, Weight and Power (SWaP) constrained environments. With an average throughput of 16,000 inferences per second, the system provided a processing efficiency of 1,066 inferences per Watt. The NS16e power utilization never exceeded 15 Watts for this application. The contribution of power consumption from TrueNorth processors was bound to less than 5.5 Watts.
使用IBM的NS16e 16芯片神经形态硬件的低功耗计算和同步光电/雷达数据处理
先进的机器学习(ML)计算架构、技术和方法首次在美国地质调查局(USGS)光学图像和国防部(DoD)合成孔径雷达(SAR)图像上同时展示,使用IBM的新型NS16e神经突触处理器板,该处理器板由16个TrueNorth芯片组成。美国空军研究实验室(AFRL)信息理事会高级计算和通信部门继续开发和演示新的生物启发计算算法和架构,旨在提供先进、超低功耗、地面和机载高性能计算(HPC)解决方案,以满足情报、监视和侦察(ISR)任务在小尺寸硬件上的作战和战术实时处理需求。重量和功率(SWaP)受限的环境。该系统的平均吞吐量为每秒16,000次推理,处理效率为每瓦特1,066次推理。在此应用中,NS16e的功率利用率从未超过15瓦。TrueNorth处理器的功耗贡献将低于5.5瓦。
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