红外焦平面阵列与大规模并行处理器的集成

P. Esfandiari, P. Koskey, K. Vaccaro, W. Buchwald, F. Clark, B. Krejca, C. Rekeczky, Á. Zarándy
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引用次数: 0

摘要

本研究的目的是用InGaAs焦平面阵列(FPA)取代细胞神经网络(CNN)处理器的低填充因子可见传感器,采用碰撞键合和外延层转移技术,用于弹道导弹防御系统(BMDS)拦截导引头。目标是制造一个具有本地和全球互连架构的大规模并行数字处理器。目前,这种独特的CNN处理器能够通过其可见传感器以每秒超过10,000帧的速度处理目标场景。CNN处理器的独特之处在于,每个处理元件包括存储器、本地数据存储、本地和全局通信设备以及由可编程模拟或数字计算机程序支持的可见传感器。
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Integration of IR focal plane arrays with massively parallel processor
The intent of this investigation is to replace the low fill factor visible sensor of a Cellular Neural Network (CNN) processor with an InGaAs Focal Plane Array (FPA) using both bump bonding and epitaxial layer transfer techniques for use in the Ballistic Missile Defense System (BMDS) interceptor seekers. The goal is to fabricate a massively parallel digital processor with a local as well as a global interconnect architecture. Currently, this unique CNN processor is capable of processing a target scene in excess of 10,000 frames per second with its visible sensor. What makes the CNN processor so unique is that each processing element includes memory, local data storage, local and global communication devices and a visible sensor supported by a programmable analog or digital computer program.
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