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Found 4 papers, 0 papers with code
Heterogeneous Integration of In-Memory Analog Computing Architectures with Tensor Processing Units
To leverage the strengths of TPUs for convolutional layers and IMAC circuits for dense layers, we propose a unified learning algorithm that incorporates mixed-precision training techniques to mitigate potential accuracy drops when deploying models on the TPU-IMAC architecture.
An In-Memory Analog Computing Co-Processor for Energy-Efficient CNN Inference on Mobile Devices
In this paper, we develop an in-memory analog computing (IMAC) architecture realizing both synaptic behavior and activation functions within non-volatile memory arrays.
TSV Extrusion Morphology Classification Using Deep Convolutional Neural Networks
Results obtained show that the CNN model with optimized complexity, dropout, and data augmentation can achieve a classification accuracy comparable to that of a human expert.
SOT-MRAM based Sigmoidal Neuron for Neuromorphic Architectures
In this paper, the intrinsic physical characteristics of spin-orbit torque (SOT) magnetoresistive random-access memory (MRAM) devices are leveraged to realize sigmoidal neurons in neuromorphic architectures.
