In-Sensor-Memory Computing for Post-Von Neumann Intelligence
A Perspective
Hongyu Tang (Fudan University)
Ninghai Yu (Fudan University)
Pengsheng Min (Fudan University)
Ruiqian Guo (Fudan University)
Guoqi Zhang (TU Delft - Electronic Components, Technology and Materials)
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Abstract
In-sensor-memory computing (ISMC) resolves von Neumann bottlenecks via synergistic innovations across multi-dimensional functional materials, hybrid architectures, and algorithm-hardware co-design. This paradigm empowers ultra-low-latency edge applications, paving the way for autonomous systems, bio-integrated healthcare, and decentralized swarm intelligence. Translating ISMC into scalable commercialization necessitates global Industry-Academia-Research collaboration, application-centric benchmarking protocols, and cross-disciplinary ecosystem enablers.
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