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Sustainable AI: Environmental Implications, Challenges and Opportunities
Conference on Machine Learning and Systems (MLSys), 2021
30 October 2021
Carole-Jean Wu
Ramya Raghavendra
Udit Gupta
Bilge Acun
Newsha Ardalani
Kiwan Maeng
Gloria Chang
Fiona Aga Behram
James Huang
Charles Bai
M. Gschwind
Anurag Gupta
Myle Ott
Anastasia Melnikov
Salvatore Candido
David Brooks
Geeta Chauhan
Benjamin C. Lee
Hsien-Hsin S. Lee
Bugra Akyildiz
Maximilian Balandat
Joe Spisak
R. Jain
Michael G. Rabbat
K. Hazelwood
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Papers citing
"Sustainable AI: Environmental Implications, Challenges and Opportunities"
50 / 192 papers shown
Title
Neuromorphic Intermediate Representation: A Unified Instruction Set for Interoperable Brain-Inspired Computing
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Steven Abreu
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AI-native Interconnect Framework for Integration of Large Language Model Technologies in 6G Systems
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Anytime-Competitive Reinforcement Learning with Policy Prior
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02 Nov 2023
PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices
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Autonomous Tree-search Ability of Large Language Models
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International Conference on Computational Linguistics (COLING), 2023
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Albert Gatt
Dong Nguyen
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10 Oct 2023
MAD Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems
International Symposium on Computer Architecture (ISCA), 2023
Samuel Hsia
Alicia Golden
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Zach DeVito
Gu-Yeon Wei
David Brooks
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04 Oct 2023
LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models
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Ruhan Wang
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OpenBA: An Open-sourced 15B Bilingual Asymmetric seq2seq Model Pre-trained from Scratch
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Zecheng Tang
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Towards Energy-Aware Federated Traffic Prediction for Cellular Networks
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Selim F. Yilmaz
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Large language models can accurately predict searcher preferences
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S. Spielman
Nick Craswell
Bhaskar Mitra
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XGen-7B Technical Report
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Tian Xie
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Silvio Savarese
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07 Sep 2023
Efficiency is Not Enough: A Critical Perspective of Environmentally Sustainable AI
Communications of the ACM (CACM), 2023
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Christian Igel
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405
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Energy Concerns with HPC Systems and Applications
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Youssef Mesri
167
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Maestro: Uncovering Low-Rank Structures via Trainable Decomposition
International Conference on Machine Learning (ICML), 2023
Samuel Horváth
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GRASP: A Rehearsal Policy for Efficient Online Continual Learning
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Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference
International Symposium on Computer Architecture (ISCA), 2023
Ranggi Hwang
Jianyu Wei
Shijie Cao
Changho Hwang
Xiaohu Tang
Ting Cao
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Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models
International Conference on Machine Learning (ICML), 2023
Bilgehan Sel
Ahmad S. Al-Tawaha
Vanshaj Khattar
R. Jia
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20 Aug 2023
InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models
ACM Conference on Recommender Systems (RecSys), 2023
Kabir Nagrecha
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P. Delgado
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E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
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Qifan Wang
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Zhiwen Cao
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VPVLM
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Batching for Green AI -- An Exploratory Study on Inference
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19 Jul 2023
Llama 2: Open Foundation and Fine-Tuned Chat Models
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On the Promise and Pitfalls of Optimizing Embodied Carbon
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Toward Sustainable HPC: Carbon Footprint Estimation and Environmental Implications of HPC Systems
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Towards Environmentally Equitable AI via Geographical Load Balancing
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196
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Vessim: A Testbed for Carbon-Aware Applications and Systems
Philipp Wiesner
Ilja Behnke
Paul Kilian
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282
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High-performance deep spiking neural networks with 0.3 spikes per neuron
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How to estimate carbon footprint when training deep learning models? A guide and review
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Evaluating the Social Impact of Generative AI Systems in Systems and Society
Irene Solaiman
Zeerak Talat
William Agnew
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Clover: Toward Sustainable AI with Carbon-Aware Machine Learning Inference Service
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252
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Luís Cruz
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SIESTA: Efficient Online Continual Learning with Sleep
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An Overview on Language Models: Recent Developments and Outlook
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208
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