Section I covers foundational principles of AI-driven circuit design, featuring how AI empowers the design and optimization of analog-to-digital converters. Section II delves into Near-Memory Computing (NMC), with an in-depth exploration of NMC architectures and their transformative potential for computing efficiency. Section III focuses on Processing-In-Memory paradigms, where ReRAM-based accelerators are tailored for scientific computing workloads, alongside a comprehensive overview of in-memory hyperdimensional computing algorithms, circuit implementations, and applications.
This collection offers a focused yet broad perspective on emerging AI-enhanced design methodologies and memory-centric computing architectures, serving as a valuable resource for researchers, engineers, and technologists advancing next-generation computing systems.
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