Scalable Compute Platform For Sensor Processing

被引:0
|
作者
Land, Ian [1 ]
Parker, Michael [2 ]
机构
[1] Synopsys Inc, A&G Solut, Sunnyvale, CA 94085 USA
[2] Raytheon Technol, El Segundo, CA 90245 USA
关键词
RF; EW; ISR; AI; EOIR; Radar; LiDAR; Radio Frequency; Electronic Warfare; Artificial Intelligence; Machine Learning; Communications; Array Sensor Processing; Video; Imaging; Autonomy;
D O I
10.1109/NAECON61878.2024.10670682
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
High-performance DoD applications like sensor arrays must continue to push the state-of-the-art (SOTA) size, weight, and power (SWaP) while advancing system performance processing of the individual sensors. A scalable Vector Processor (VP) based compute platform can be created to deliver ASIC-like performance/power while incorporating FPGA-like flexibility and latency. This paper presents a study of key processors and assesses the strengths and challenges where a vector-engine based platform can deliver capabilities beyond the traditional methods that leverage FPGAs, while adding in AI acceleration and consideration of multiple sensors, sensor fusion, and strategic applications.
引用
收藏
页码:241 / 246
页数:6
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