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Showing 1 to 3 of 3 for “"analog in-memory computing"”.
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Geometrically Programmed Nano-Resistors for Ultra-Robust Artificial Neural Network Accelerator
Despite the transformative advance in artificial intelligence (AI), the AI processing hardware have not matched the speed and power-efficiency requirement, restricting the realization of the full potential of AI and requiring innovation in AI hardware. Data transmission bottleneck between memory …
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Analog On-chip Training and Inference with Non-volatile Memory Devices
As the demand for computation in neural networks continues to rise, conventional computing resources are increasingly constrained by their limited energy efficiency. One promising solution to this challenge is analog in-memory computing (AIMC), which enables efficient matrix-vector multiplications …
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Energy-Efficient Data-Processing Architectures - Coping with device and circuit-level nonidealities
… è presente nell'allegato / the abstract is in the attachment