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Relay: A High-Level Compiler for Deep Learning
Frameworks for writing, compiling, and optimizing deep learning (DL) mod...
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Relay: A High-Level IR for Deep Learning
Frameworks for writing, compiling, and optimizing deep learning (DL) mod...
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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...
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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...
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VTA: An Open Hardware-Software Stack for Deep Learning
Hardware acceleration is an enabler for ubiquitous and efficient deep le...
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Learning to Optimize Tensor Programs
We introduce a learning-based framework to optimize tensor programs for ...
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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...
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TVM: End-to-End Optimization Stack for Deep Learning
Scalable frameworks, such as TensorFlow, MXNet, Caffe, and PyTorch drive...
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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...
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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- The primary author has withdrawn this paper due to conflict of interes...
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Exploring Computation-Communication Tradeoffs in Camera Systems
Cameras are the defacto sensor. The growing demand for real-time and low...
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