Memristive In‐Memory Object Detection with 128 Mb C‐Doped Ge ₂ Sb ₂ Te ₅ PCM Chip

Abstract Object detection, as a fundamental task in computer vision, mainly performs the classification and localization of objects in images or videos. However, traditional edge computing platforms fall short of meeting the demands for state‐of‐the‐art object detection model size and computing power. Here, a 128 Mb phase change memory chip is fabricated with a high memory yield of 99.99999% in a 40 nm node and utilized for efficient in‐memory vector‐matrix multiplication and in‐memory max computation. In particular, in order to mitigate the significant programming energy overheads for large‐scale memristor arrays and the reliance on high‐precision analog‐to‐digital‐converter (ADC) in compute‐in‐memory operations, a novel mixed‐precision weight mapping strategy is adopted. Compared with traditional schemes, the ADC modules achieve up to a 22.3× reduction in energy consumption while maintaining equivalent network performance. Ultimately, this memristive in‐memory object detection system demonstrates 4,180× higher energy efficiency and 228× greater computational throughput compared to GPU implementations.