2018/07/25 · We evaluate our crossbar-aware pruning framework on median-scale CIFAR10 dataset and large-scale ImageNet dataset with VGG and ResNet models.
2018/10/07 · This paper proposes a crossbar-aware pruning framework based on a formulated L_{0} -norm constrained optimization problem. Specifically, we ...
Network pruning is a promising and widely studied method to shrink the model size, whereas prior work for CNNs compression rarely considered the crossbar ...
The proposed crossbar-aware pruning framework is able to reduce the resource overhead and the related energy cost and provides a new co-design solution for ...
2018/10/31 · ABSTRACT Crossbar architecture has been widely adopted in neural network accelerators due to the efficient implementations on vector-matrix ...
ReaLPrune: ReRAM Crossbar-Aware Lottery Ticket Pruning for CNNs
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In this paper, we address this problem by proposing a novel crossbar-aware pruning strategy, referred as ReaLPrune, which can prune more than 90% of CNN weights ...
We propose a learning-for-data-pruning framework, which leverages a trained Binary Graph Classifier (BGC) to reduce the size of the input data graph.
2022/02/03 · In this work, PRUNIX, a framework for training and pruning convolutional neural networks is proposed for deployment on memristor crossbar based accelerators.
2022/12/20 · In this study, we propose XMA 2, a novel crossbar-aware learning method with a 2-tier masking technique to efficiently adapt a DNN backbone model.
In this paper, we first propose crossbar-aligned pruning to reduce the usage of crossbars without hardware overhead. Then, we introduce a quantization scheme ...