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06/24/2023
H_2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models
Large Language Models (LLMs), despite their recent impressive accomplish...
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06/03/2023
On Optimal Caching and Model Multiplexing for Large Model Inference
Large Language Models (LLMs) and other large foundation models have achi...
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03/13/2023
FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU
The high computational and memory requirements of large language model (...
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07/09/2022
TensorIR: An Abstraction for Automatic Tensorized Program Optimization
Deploying deep learning models on various devices has become an importan...
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06/28/2022
NumS: Scalable Array Programming for the Cloud
Scientists increasingly rely on Python tools to perform scalable distrib...
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06/22/2022
GACT: Activation Compressed Training for General Architectures
Training large neural network (NN) models requires extensive memory reso...
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04/29/2021
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training
The increasing size of neural network models has been critical for impro...
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06/11/2020
Ansor : Generating High-Performance Tensor Programs for Deep Learning
High-performance tensor programs are crucial to guarantee efficient exec...
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07/03/2019
A Unified Optimization Approach for CNN Model Inference on Integrated GPUs
Modern deep learning applications urge to push the model inference takin...
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05/21/2018
Learning to Optimize Tensor Programs
We introduce a learning-based framework to optimize tensor programs for ...
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02/12/2018
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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01/13/2018
Size-to-depth: A New Perspective for Single Image Depth Estimation
In this paper we consider the problem of single monocular image depth es...
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12/02/2017
