Thierry Moreau

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University of Washington

Relay: A High-Level Compiler for Deep Learning

Frameworks for writing, compiling, and optimizing deep learning (DL) mod...
04/17/2019 ∙ by Jared Roesch, et al. ∙ 0 ∙ share

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Relay: A High-Level IR for Deep Learning

Frameworks for writing, compiling, and optimizing deep learning (DL) mod...
04/17/2019 ∙ by Jared Roesch, et al. ∙ 0 ∙ share

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Automating Generation of Low Precision Deep Learning Operators

State of the art deep learning models have made steady progress in the f...
10/25/2018 ∙ by Meghan Cowan, et al. ∙ 0 ∙ share

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Exploiting Errors for Efficiency: A Survey from Circuits to Algorithms

When a computational task tolerates a relaxation of its specification or...
09/16/2018 ∙ by Phillip Stanley-Marbell, et al. ∙ 0 ∙ share

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VTA: An Open Hardware-Software Stack for Deep Learning

Hardware acceleration is an enabler for ubiquitous and efficient deep le...
07/11/2018 ∙ by Thierry Moreau, et al. ∙ 6 ∙ share

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Learning to Optimize Tensor Programs

We introduce a learning-based framework to optimize tensor programs for ...
05/21/2018 ∙ by Tianqi Chen, et al. ∙ 0 ∙ share

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TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

There is an increasing need to bring machine learning to a wide diversit...
02/12/2018 ∙ by Tianqi Chen, et al. ∙ 0 ∙ share

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TVM: End-to-End Optimization Stack for Deep Learning

Scalable frameworks, such as TensorFlow, MXNet, Caffe, and PyTorch drive...
02/12/2018 ∙ by Tianqi Chen, et al. ∙ 0 ∙ share

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Introducing ReQuEST: an Open Platform for Reproducible and Quality-Efficient Systems-ML Tournaments

Co-designing efficient machine learning based systems across the whole h...
01/19/2018 ∙ by Thierry Moreau, et al. ∙ 0 ∙ share

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MATIC: Adaptation and In-situ Canaries for Energy-Efficient Neural Network Acceleration

- The primary author has withdrawn this paper due to conflict of interes...
06/14/2017 ∙ by Sung Kim, et al. ∙ 0 ∙ share

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Exploring Computation-Communication Tradeoffs in Camera Systems

Cameras are the defacto sensor. The growing demand for real-time and low...
06/12/2017 ∙ by Amrita Mazumdar, et al. ∙ 0 ∙ share

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Thierry Moreau

Featured Co-authors

Carlos Guestrin

Michael Carbin

Tianqi Chen

Lara Dolecek

Luis Ceze

Arvind Krishnamurthy

Zachary Tatlock

Phillip Stanley-Marbell

Eva Darulova

Babak Falsafi

Ziheng Jiang

Relay: A High-Level Compiler for Deep Learning

Relay: A High-Level IR for Deep Learning

Automating Generation of Low Precision Deep Learning Operators

Exploiting Errors for Efficiency: A Survey from Circuits to Algorithms

VTA: An Open Hardware-Software Stack for Deep Learning

Learning to Optimize Tensor Programs

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

TVM: End-to-End Optimization Stack for Deep Learning

Introducing ReQuEST: an Open Platform for Reproducible and Quality-Efficient Systems-ML Tournaments

MATIC: Adaptation and In-situ Canaries for Energy-Efficient Neural Network Acceleration

Exploring Computation-Communication Tradeoffs in Camera Systems