most citedALPINE: Analog In-Memory Acceleration with Tight Processor Integration for Deep Learning

14 citations · 14 across the 1 of their papers we have counts for

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1 paper

cs.AR2022★ 14 cited

ALPINE: Analog In-Memory Acceleration with Tight Processor Integration for Deep Learning

Joshua Klein, Irem Boybat, Yasir Qureshi +6

Analog in-memory computing (AIMC) cores offers significant performance and energy benefits for neural network inference with respect to digital logic (e.g., CPUs). AIMCs accelerate…