Original paper
Neural-PIM: Efficient Processing-In-Memory with Neural Approximation of Peripherals
Abstract
Processing-in-memory (PIM) architecture has demonstrated great potentials in accelerating numerous deep learning tasks. In particular, resistive random-access memory (RRAM) technology provides a promising hardware substrate for PIM accelerators, because it can support efficient in-situ vector-matrix multiplications (VMMs) with high-density RRAM crossbar arrays. However, such accelerators suffer from frequent and energy-intensive...
Paper Details
Title
Neural-PIM: Efficient Processing-In-Memory with Neural Approximation of Peripherals
Published Date
Jan 1, 2021
Pages
1 - 1
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History