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09/11/2023
Large Language Models for Compiler Optimization
We explore the novel application of Large Language Models to code optimi...
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03/02/2023
BenchDirect: A Directed Language Model for Compiler Benchmarks
The exponential increase of hardware-software complexity has made it imp...
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08/13/2022
BenchPress: A Deep Active Benchmark Generator
We develop BenchPress, the first ML benchmark generator for compilers th...
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11/23/2021
Caviar: An E-graph Based TRS for Automatic Code Optimization
Term Rewriting Systems (TRSs) are used in compilers to simplify and prov...
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10/30/2021
Sustainable AI: Environmental Implications, Challenges and Opportunities
This paper explores the environmental impact of the super-linear growth ...
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04/01/2021
Using Python for Model Inference in Deep Learning
Python has become the de-facto language for training deep neural network...
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11/11/2020
Understanding Training Efficiency of Deep Learning Recommendation Models at Scale
The use of GPUs has proliferated for machine learning workflows and is n...
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12/30/2019
RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing
Personalized recommendation systems leverage deep learning models and ac...
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10/02/2019
MLPerf Training Benchmark
Machine learning is experiencing an explosion of software and hardware s...
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08/13/2019
Exploiting Parallelism Opportunities with Deep Learning Frameworks
State-of-the-art machine learning frameworks support a wide variety of d...
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06/06/2019
The Architectural Implications of Facebook's DNN-based Personalized Recommendation
The widespread application of deep learning has changed the landscape of...
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03/29/2019
SysML: The New Frontier of Machine Learning Systems
Machine learning (ML) techniques are enjoying rapidly increasing adoptio...
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11/24/2018
Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications
The application of deep learning techniques resulted in remarkable impro...
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11/14/2018
