arXiv Machine Learning July 16, 2026 By Rebecca Pelke, Jos\'e Cubero-Cascante, Nils Bosbach, Niklas Degener, Florian Idrizi, Lennart M. Reimann, Jan Moritz Joseph, Rainer Leupers

Optimizing Binary and Ternary Neural Network Inference on RRAM Crossbars using CIM-Explorer

Read the original on arXiv Machine Learning →

arXiv:2505. 14303v3 Announce Type: replace-cross Abstract: Using Resistive Random Access Memory (RRAM) crossbars in Computing-in-Memory (CIM) architectures offers a promising solution to overcome the von Neumann bottleneck.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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