面向自动驾驶的2.5D CMOS图像传感器和FPGA集成封装热建模

Janak Sharda, Madison Manley, Ankit Kaul, Wantong Li, M. Bakir, Shimeng Yu
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引用次数: 0

摘要

用于自动驾驶的深度学习算法需要在摄像头和处理器之间进行大量数据移动。我们建议在硅中间层上使用CMOS图像传感器(CIS)和FPGA的2.5D集成,以减少由于数据移动而导致的延迟和能耗。整个系统的热模拟表明,由于2.5D集成,CIS温度升高。由于数据移动而减少的能耗是$48\times$,延迟是$24\times$。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Thermal Modeling of 2.5D Integrated Package of CMOS Image Sensor and FPGA for Autonomous Driving
Deep learning algorithms for autonomous driving require significant data movement between the camera and the processor. We propose using 2.5D integration of a CMOS image sensor (CIS) and FPGA on silicon interposer to reduce the latency and energy consumption due to data movement. Thermal simulations of the full system show an increase in CIS temperature due to 2.5D integration. The reduction in energy consumption due to data movement is $48\times$ and in latency is $24\times$.
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