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10/02/2022
Approximate Computing and the Efficient Machine Learning Expedition
Approximate computing (AxC) has been long accepted as a design alternati...
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06/16/2022
Accelerating Inference and Language Model Fusion of Recurrent Neural Network Transducers via End-to-End 4-bit Quantization
We report on aggressive quantization strategies that greatly accelerate ...
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08/27/2021
4-bit Quantization of LSTM-based Speech Recognition Models
We investigate the impact of aggressive low-precision representations of...
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04/21/2021
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training
Large-scale distributed training of Deep Neural Networks (DNNs) on state...
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11/05/2018
Workload-aware Automatic Parallelization for Multi-GPU DNN Training
Deep neural networks (DNNs) have emerged as successful solutions for var...
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07/17/2018
Bridging the Accuracy Gap for 2-bit Quantized Neural Networks (QNN)
Deep learning algorithms achieve high classification accuracy at the exp...
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05/16/2018
PACT: Parameterized Clipping Activation for Quantized Neural Networks
Deep learning algorithms achieve high classification accuracy at the exp...
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11/07/2017
SparCE: Sparsity aware General Purpose Core Extensions to Accelerate Deep Neural Networks
Deep Neural Networks (DNNs) have emerged as the method of choice for sol...
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04/04/2017
DyVEDeep: Dynamic Variable Effort Deep Neural Networks
Deep Neural Networks (DNNs) have advanced the state-of-the-art in a vari...
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02/27/2016
