Patrick Judd

IEEE Micro, 2019

ShapeShifter: Enabling Fine-Grain Data Width Adaptation in Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture, 2019

Bit-Tactical: A Software/Hardware Approach to Exploiting Value and Bit Sparsity in Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems, 2019

2018

Proteus: Exploiting precision variability in deep neural networks.

[BibT_eX]

[DOI]

Raquel Urtasun

Parallel Comput., 2018

Value-Based Deep-Learning Acceleration.

[BibT_eX]

[DOI]

IEEE Micro, 2018

DPRed: Making Typical Activation Values Matter In Deep Learning Computing.

[BibT_eX]

[DOI]

CoRR, 2018

Bit-Tactical: Exploiting Ineffectual Computations in Convolutional Neural Networks: Which, Why, and How.

[BibT_eX]

[DOI]

CoRR, 2018

Exploiting Typical Values to Accelerate Deep Learning.

[BibT_eX]

[DOI]

Zissis Poulos

Computer, 2018

Identifying and Exploiting Ineffectual Computations to Enable Hardware Acceleration of Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the 16th IEEE International New Circuits and Systems Conference, 2018

Loom: exploiting weight and activation precisions to accelerate convolutional neural networks.

[BibT_eX]

[DOI]

Kevin Siu

Proceedings of the 55th Annual Design Automation Conference, 2018

2017

Loom: Exploiting Weight and Activation Precisions to Accelerate Convolutional Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2017

Cnvlutin2: Ineffectual-Activation-and-Weight-Free Deep Neural Network Computing.

[BibT_eX]

[DOI]

CoRR, 2017

Tartan: Accelerating Fully-Connected and Convolutional Layers in Deep Learning Networks by Exploiting Numerical Precision Variability.

[BibT_eX]

[DOI]

CoRR, 2017

Dynamic Stripes: Exploiting the Dynamic Precision Requirements of Activation Values in Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2017

Stripes: Bit-Serial Deep Neural Network Computing.

[BibT_eX]

[DOI]

IEEE Comput. Archit. Lett., 2017

Bit-pragmatic deep neural network computing.

[BibT_eX]

[DOI]

Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture, 2017

Bit-Pragmatic Deep Neural Network Computing.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Stripes: Bit-serial deep neural network computing.

[BibT_eX]

[DOI]

Proceedings of the 49th Annual IEEE/ACM International Symposium on Microarchitecture, 2016

Cnvlutin: Ineffectual-Neuron-Free Deep Neural Network Computing.

[BibT_eX]

[DOI]

Proceedings of the 43rd ACM/IEEE Annual International Symposium on Computer Architecture, 2016

Proteus: Exploiting Numerical Precision Variability in Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 2016 International Conference on Supercomputing, 2016

2015

Reduced-Precision Strategies for Bounded Memory in Deep Neural Nets.

[BibT_eX]

[DOI]

Raquel Urtasun

CoRR, 2015

2014

Evaluating the memory system behavior of smartphone workloads.

[BibT_eX]

[DOI]