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06/15/2021
S2Engine: A Novel Systolic Architecture for Sparse Convolutional Neural Networks
Convolutional neural networks (CNNs) have achieved great success in perf...
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04/07/2021
Optimizing Memory Efficiency of Graph NeuralNetworks on Edge Computing Platforms
Graph neural networks (GNN) have achieved state-of-the-art performance o...
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07/21/2020
SparseTrain: Exploiting Dataflow Sparsity for Efficient Convolutional Neural Networks Training
Training Convolutional Neural Networks (CNNs) usually requires a large n...
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08/01/2019
Accelerating CNN Training by Sparsifying Activation Gradients
Gradients to activations get involved in most of the calculations during...
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02/19/2019
SPINBIS: Spintronics based Bayesian Inference System with Stochastic Computing
Bayesian inference is an effective approach for solving statistical lear...
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10/26/2018