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Accurate reporting of energy and carbon usage is essential for understanding the potential climate impacts of machine learning research.
Causes of climate change over the past 1000 years
Thomas J Crowley · 2000
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The relative importance of perceived ease of use in is adoption: A study of e-commerce adoption
David Gefen and Detmar W Straub · 2000
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Eco-labeling for energy efficiency and sustainability: a meta-evaluation of us programs
Abhijit Banerjee and Barry D Solomon · 2003
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Green defaults: Information presentation and pro-environmental behaviour
Daniel Pichert and Konstantinos V. Katsikopoulos · 2007
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Greenhouse gas equivalencies calculator, 2008
US Environmental Protection Agency · 2008
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Climate change and discounting the future: a guide for the perplexed
David Weisbach and Cass R Sunstein · 2008
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Irreversible climate change due to carbon dioxide emissions
Susan Solomon, Gian-Kasper Plattner, Reto Knutti, and Pierre Friedlingstein · 2009
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Towards energy-aware scheduling in data centers using machine learning
Josep Ll. Berral, Íñigo Goiri, Ramón Nou, Ferran Julià, Jordi Guitart, Ricard Gavaldà, and Jordi Torres · 2010
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Climate-neutral ecology conferences: just do it!
Oliver Bossdorf, Madalin Parepa, and Markus Fischer · 2010
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RAPL: memory power estimation and capping
Howard David, Eugene Gorbatov, Ulf R Hanebutte, Rahul Khanna, and Christian Le · 2010
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Accounting for climate change and the self-regulation of carbon disclosures
Jane Andrew and Corinne Cortese · 2011
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Standardized reporting of climate change information in australia
Julie Cotter, Muftah Najah, and Shihui Sophie Wang · 2011
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The social cost of carbon
Richard SJ Tol · 2011
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ImageNet Classification with Deep Convolutional Neural Networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton · 2012
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Environmental-aware virtual data center network
Kim Khoa Nguyen, Mohamed Cheriet, Mathieu Lemay, Victor Reijs, Andrew Mackarel, and Alin Pastrama · 2012
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Carbon accounting: a systematic literature review
Kristin Stechemesser and Edeltraud Guenther · 2012
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Comprehensive carbon stock and flow accounting: a national framework to support climate change mitigation policy
Judith I Ajani, Heather Keith, Margaret Blakers, Brendan G Mackey, and Helen P King · 2013
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The Arcade Learning Environment: An Evaluation Platform for General Agents
Marc G Bellemare, Yavar Naddaf, Joel Veness, and Michael Bowling · 2013
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Statistical modeling of power/energy of scientific kernels on a multi-gpu system
Sayan Ghosh, Sunita Chandrasekaran, and Barbara Chapman · 2013
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Google’s Green PPAs: What, How, and Why
Google · 2013
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Green computing: A life cycle perspective
Alex K Jones, Liang Liao, William O Collinge, Haifeng Xu, Laura A Schaefer, Amy E Landis, and Melissa M Bilec · 2013
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The future carbon footprint of the ict and e&m sectors
Jens Malmodin, Pernilla Bergmark, and Dag Lundén · 2013
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Playing Atari With Deep Reinforcement Learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller · 2013
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Unified performance and power modeling of scientific workloads
Shuaiwen Leon Song, Kevin Barker, and Darren Kerbyson · 2013
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The carbon footprint of conference papers
Diomidis Spinellis and Panos Louridas · 2013
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Social Cost of Carbon
U.S. Environment Protection Agency · 2013
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Annex 2 - metrics and methodology
V. Krey, O. Masera, G. Blanford, T. Bruckner, R. Cooke, K. Fisher-Vanden, H. Haberl, E. Hertwich, E. Kriegler, D. Mueller, S. Paltsev, L. Price, S. Schlömer, D. Ürge-Vorsatz, D. van Vuuren, and T. Zwickel · 2014
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Nudging energy efficiency behavior: The role of information labels
Richard G Newell and Juha Siikamäki · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Accounting for Carbon
Valentin Bellassen and Nicolas Stephan · 2015
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Data center energy consumption modeling: A survey
Miyuru Dayarathna, Yonggang Wen, and Rui Fan · 2015
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CO2 Emissions from Fuel Combustion
International Energy Agency · 2015
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Climate Change 2014: Mitigation of Climate Change: Working Group III Contribution to the IPCC Fifth Assessment Report
IPCC · 2015
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Why greatness cannot be planned: The myth of the objective
Kenneth O Stanley and Joel Lehman · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Comparative Carbon Footprint Assessment of the Manufacturing and Use Phases of Two Generations of AMD Accelerated Processing Units, 2015
Chandramouli Venkatesan · 2015
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OpenAI Gym, 2016
Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
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An analysis of deep neural network models for practical applications
Alfredo Canziani, Adam Paszke, and Eugenio Culurciello · 2016
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A validation of dram rapl power measurements
Spencer Desrochers, Chad Paradis, and Vincent M Weaver · 2016
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Achieving Our 100% Renewable Energy Purchasing Goal and Going Beyond
Google · 2016
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SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and< 0.5 MB model size
Forrest N Iandola, Song Han, Matthew W Moskewicz, Khalid Ashraf, William J Dally, and Kurt Keutzer · 2016
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How better accounting can more cheaply reduce carbon emissions
Jacob LaRiviere, Gavin Mccormick, and Sho Kawano · 2016
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Diagonalwise Refactorization: An Efficient Training Method for Depthwise Convolutions
Zheng Qin, Zhaoning Zhang, Dongsheng Li, Yiming Zhang, and Yuxing Peng · 2018
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Country-level social cost of carbon
Katharine Ricke, Laurent Drouet, Ken Caldeira, and Massimo Tavoni · 2018
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Mobilenetv2: Inverted residuals and linear bottlenecks
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
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Quality assessment of gpu power profiling mechanisms
Satyabrata Sen, Neena Imam, and Chung-Hsing Hsu · 2018
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AI Researchers Left Disappointed As NIPS Sells Out In Under 12 Minutes
Sam Shead · 2018
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Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
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Psutil package: a cross-platform library for retrieving information on running processes and system utilization, 2016
Giampaolo Rodola · 2016
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Ten years of Google Translate
Barak Turovsky · 2016
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Sergey Zagoruyko and Nikos Komodakis · 2016
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Convolutional sequence to sequence learning
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, and Yann N Dauphin · 2017
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Academic conferences urgently need environmental policies
Matthew H Holden, Nathalie Butt, Alienor Chauvenet, Michaela Plein, Martin Stringer, and Iadine Chadès · 2017
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Mobilenets: Efficient convolutional neural networks for mobile vision applications
Andrew G Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
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Frank Soboczenski, Michael D Himes, Molly D O’Beirne, Simone Zorzan, Atilim Gunes Baydin, Adam D Cobb, Yarin Gal, Daniel Angerhausen, Massimo Mascaro, Giada N Arney, et al · 2018
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Modeling the impact of media awareness programs on mitigation of carbon dioxide emitted from automobiles
Shyam Sundar, Ashish Kumar Mishra, and Ram Naresh · 2018
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Climate change and mandatory carbon reporting: Impacts on business process and performance
Samuel Tang and David Demeritt · 2018
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Shufflenet: An extremely efficient convolutional neural network for mobile devices
Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, and Jian Sun · 2018
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Hulk: An energy efficiency benchmark platform for responsible natural language processing
Xiyou Zhou, Zhiyu Chen, Xiaoyong Jin, and William Yang Wang · 2018
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Gossip-based actor-learner architectures for deep reinforcement learning
Mahmoud ("Mido") Assran, Joshua Romoff, Nicolas Ballas, Joelle Pineau, and Mike Rabbat · 2019
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Decovac: Design of experiments with controlled variability components
Thomas Boquet, Laure Delisle, Denis Kochetkov, Nathan Schucher, Parmida Atighehchian, Boris Oreshkin, and Julien Cornebise · 2019
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Hardnet: A low memory traffic network
Ping Chao, Chao-Yang Kao, Yu-Shan Ruan, Chien-Hsiang Huang, and Youn-Long Lin · 2019
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Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark
Cody Coleman, Daniel Kang, Deepak Narayanan, Luigi Nardi, Tian Zhao, Jian Zhang, Peter Bailis, Kunle Olukotun, Chris Ré, and Matei Zaharia · 2019
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GPU-Accelerated Atari Emulation for Reinforcement Learning, 2019
Steven Dalton, Iuri Frosio, and Michael Garland · 2019
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Rational mining limits bitcoin emissions
Nicolas Houy · 2019
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Accelerating Deep Learning by Focusing on the Biggest Losers
Angela H. Jiang, Daniel L. K. Wong, Giulio Zhou, David G. Andersen, Jeffrey Dean, Gregory R. Ganger, Gauri Joshi, Michael Kaminksy, Michael Kozuch, Zachary C. Lipton, and Padmanabhan Pillai · 2019
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Rapid and accurate energy models through calibration with ipmi and rapl
Richard Kavanagh and Karim Djemame · 2019
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Quantifying the carbon emissions of machine learning
Alexandre Lacoste, Alexandra Luccioni, Victor Schmidt, and Thomas Dandres · 2019
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Implausible projections overestimate near-term bitcoin co2 emissions
Eric Masanet, Arman Shehabi, Nuoa Lei, Harald Vranken, Jonathan Koomey, and Jens Malmodin · 2019
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Single Headed Attention RNN: Stop Thinking With Your Head
Stephen Merity · 2019
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Modeling energy consumption based on resource utilization
Lucas Venezian Povoa, Cesar Marcondes, and Hermes Senger · 2019
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State and trends of carbon pricing 2019, 2019
Celine Ramstein, Goran Dominioni, Sanaz Ettehad, Long Lam, Maurice Quant, Jialiang Zhang, Louis Mark, Sam Nierop, Tom Berg, Paige Leuschner, et al · 2019
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Tackling Climate Change with Machine Learning
David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Kording, Carla Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer Chayes, and Yoshua Bengio · 2019
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Roy Schwartz, Jesse Dodge, Noah A. Smith, and Oren Etzioni · 2019
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The ai index 2019 annual report
Yoav Shoham, Erik Brynjolfsson, Jack Clark, John Etchemendy, Barbara Grosz, Terah Lyons, James Manyika, Saurabh Mishra, and Juan Carlos Niebles · 2019
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The carbon footprint of bitcoin
Christian Stoll, Lena Klaaßen, and Ulrich Gallersdörfer · 2019
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Energy and Policy Considerations for Deep Learning in NLP
Emma Strubell, Ananya Ganesh, and Andrew McCallum · 2019
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Eliminating the Variability of Cross-Validation Results with LIBLINEAR due to Randomization and Parallelization
Vladimir Sukhoy and Alexander Stoytchev · 2019
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The bitter lesson
Richard Sutton · 2019
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Real-time carbon accounting method for the european electricity markets
Bo Tranberg, Olivier Corradi, Bruno Lajoie, Thomas Gibon, Iain Staffell, and Gorm Bruun Andresen · 2019
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Pay Less Attention with Lightweight and Dynamic Convolutions
Felix Wu, Angela Fan, Alexei Baevski, Yann Dauphin, and Michael Auli · 2019
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Is bitcoin the only problem? a scenario model for the power demand of blockchains
Michel Zade, Jonas Myklebost, Peter Tzscheutschler, and Ulrich Wagner · 2019
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Verified instruction-level energy consumption measurement for nvidia gpus
Yehia Arafa, Ammar ElWazir, Abdelrahman ElKanishy, Youssef Aly, Ayatelrahman Elsayed, Abdel-Hameed Badawy, Gopinath Chennupati, Stephan Eidenbenz, and Nandakishore Santhi · 2020
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{ELECTRA}: Pre-training text encoders as discriminators rather than generators
Kevin Clark, Minh-Thang Luong, Quoc V. Le, and Christopher D. Manning · 2020
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Utility is in the eye of the user: A critique of nlp leaderboards
Kawin Ethayarajh and Dan Jurafsky · 2020
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Mlperf inference benchmark
Vijay Janapa Reddi, Christine Cheng, David Kanter, Peter Mattson, Guenther Schmuelling, Carole-Jean Wu, Brian Anderson, Maximilien Breughe, Mark Charlebois, William Chou, et al · 2020
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