A Variation-Aware Binary Neural Network Framework for Process Resilient In-Memory Computations
Minh-Son Le,
Thi-Nhan Pham,
Thanh-Dat Nguyen
et al.
Abstract:Binary neural networks (BNNs) that use 1-bit weights and activations have garnered interest as extreme quantization provides low power dissipation. By implementing BNNs as computation-in-memory (CIM), which computes multiplication and accumulations on memory arrays in an analog fashion, namely, analog CIM, we can further improve the energy efficiency to process neural networks. However, analog CIMs are susceptible to process variation, which refers to the variability in manufacturing that causes fluctuations i… Show more
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