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07/11/2023
Mixed-Precision Quantization with Cross-Layer Dependencies
Quantization is commonly used to compress and accelerate deep neural net...
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05/10/2018
Laconic Deep Learning Computing
We motivate a method for transparently identifying ineffectual computati...
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04/17/2018
DPRed: Making Typical Activation Values Matter In Deep Learning Computing
We show that selecting a fixed precision for all activations in Convolut...
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03/09/2018
Bit-Tactical: Exploiting Ineffectual Computations in Convolutional Neural Networks: Which, Why, and How
We show that, during inference with Convolutional Neural Networks (CNNs)...
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07/27/2017
Tartan: Accelerating Fully-Connected and Convolutional Layers in Deep Learning Networks by Exploiting Numerical Precision Variability
Tartan (TRT), a hardware accelerator for inference with Deep Neural Netw...
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06/23/2017
Loom: Exploiting Weight and Activation Precisions to Accelerate Convolutional Neural Networks
Loom (LM), a hardware inference accelerator for Convolutional Neural Net...
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06/01/2017
