Carole-Jean Wu

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 128

Top Venues

Publications

Mostafa Elhoushi, Akshat Shrivastava, Diana Liskovich, Basil Hosmer, Bram Wasti, Liangzhen Lai, Anas Mahmoud, Bilge Acun, Saurabh Agarwal, Ahmed Roman, Ahmed A Aly, Beidi Chen, Carole-Jean Wu
LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding. CoRR (2024)
Gyudong Kim, Mehdi Ghasemi, Soroush Heidari, Seungryong Kim, Young Geun Kim, Sarma B. K. Vrudhula, Carole-Jean Wu
HeteroSwitch: Characterizing and Taming System-Induced Data Heterogeneity in Federated Learning. MLSys (2024)
Mubashara Akhtar, Omar Benjelloun, Costanza Conforti, Joan Giner-Miguelez, Nitisha Jain, Michael Kuchnik, Quentin Lhoest, Pierre Marcenac, Manil Maskey, Peter Mattson, Luis Oala, Pierre Ruyssen, Rajat Shinde, Elena Simperl, Goeffry Thomas, Slava Tykhonov, Joaquin Vanschoren, Steffen Vogler, Carole-Jean Wu
Croissant: A Metadata Format for ML-Ready Datasets. CoRR (2024)
Bilge Acun, Brent Morgan, Henry Richardson, Nat Steinsultz, Carole-Jean Wu
Unlocking the Potential of Renewable Energy Through Curtailment Prediction. CoRR (2024)
Mostafa Elhoushi, Akshat Shrivastava, Diana Liskovich, Basil Hosmer, Bram Wasti, Liangzhen Lai, Anas Mahmoud, Bilge Acun, Saurabh Agarwal, Ahmed Roman, Ahmed A Aly, Beidi Chen, Carole-Jean Wu
LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding. ACL (1) (2024)
Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, Victor Akinwande, Namir Al-Nuaimi, Najla Alfaraj, Elie Alhajjar, Lora Aroyo, Trupti Bavalatti, Borhane Blili-Hamelin, Kurt D. Bollacker, Rishi Bomassani, Marisa Ferrara Boston, Siméon Campos, Kal Chakra, Canyu Chen, Cody Coleman, Zacharie Delpierre Coudert, Leon Derczynski, Debojyoti Dutta, Ian Eisenberg, James Ezick, Heather Frase, Brian Fuller, Ram Gandikota, Agasthya Gangavarapu, Ananya Gangavarapu, James Gealy, Rajat Ghosh, James Goel, Usman Gohar, Subhra S. Goswami, Scott A. Hale, Wiebke Hutiri, Joseph Marvin Imperial, Surgan Jandial, Nick Judd, Felix Juefei-Xu, Foutse Khomh, Bhavya Kailkhura, Hannah Rose Kirk, Kevin Klyman, Chris Knotz, Michael Kuchnik, Shachi H. Kumar, Chris Lengerich, Bo Li, Zeyi Liao, Eileen Peters Long, Victor Lu, Yifan Mai, Priyanka Mary Mammen, Kelvin Manyeki, Sean McGregor, Virendra Mehta, Shafee Mohammed, Emanuel Moss, Lama Nachman, Dinesh Jinenhally Naganna, Amin Nikanjam, Besmira Nushi, Luis Oala, Iftach Orr, Alicia Parrish, Cigdem Patlak, William Pietri, Forough Poursabzi-Sangdeh, Eleonora Presani, Fabrizio Puletti, Paul Röttger, Saurav Sahay, Tim Santos, Nino Scherrer, Alice Schoenauer Sebag, Patrick Schramowski, Abolfazl Shahbazi, Vin Sharma, Xudong Shen, Vamsi Sistla, Leonard Tang, Davide Testuggine, Vithursan Thangarasa, Elizabeth Anne Watkins, Rebecca Weiss, Chris Welty, Tyler Wilbers, Adina Williams, Carole-Jean Wu, Poonam Yadav, Xianjun Yang, Yi Zeng, Wenhui Zhang, Fedor Zhdanov, Jiacheng Zhu, Percy Liang, Peter Mattson, Joaquin Vanschoren
Introducing v0.5 of the AI Safety Benchmark from MLCommons. CoRR (2024)
Carole-Jean Wu, Bilge Acun, Ramya Raghavendra, Kim M. Hazelwood
Beyond Efficiency: Scaling AI Sustainably. CoRR (2024)
Samuel Hsia, Alicia Golden, Bilge Acun, Newsha Ardalani, Zachary DeVito, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
MAD-Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems. ISCA (2024)
Mubashara Akhtar, Omar Benjelloun, Costanza Conforti, Pieter Gijsbers, Joan Giner-Miguelez, Nitisha Jain, Michael Kuchnik, Quentin Lhoest, Pierre Marcenac, Manil Maskey, Peter Mattson, Luis Oala, Pierre Ruyssen, Rajat Shinde, Elena Simperl, Goeffry Thomas, Slava Tykhonov, Joaquin Vanschoren, Jos van der Velde, Steffen Vogler, Carole-Jean Wu
Croissant: A Metadata Format for ML-Ready Datasets. DEEM@SIGMOD (2024)
Alicia Golden, Samuel Hsia, Fei Sun, Bilge Acun, Basil Hosmer, Yejin Lee, Zachary DeVito, Jeff Johnson, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
Generative AI Beyond LLMs: System Implications of Multi-Modal Generation. ISPASS (2024)
Alicia Golden, Samuel Hsia, Fei Sun, Bilge Acun, Basil Hosmer, Yejin Lee, Zachary DeVito, Jeff Johnson, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
Is Flash Attention Stable? CoRR (2024)
Gyudong Kim, Mehdi Ghasemi, Soroush Heidari, Seungryong Kim, Young Geun Kim, Sarma B. K. Vrudhula, Carole-Jean Wu
HeteroSwitch: Characterizing and Taming System-Induced Data Heterogeneity in Federated Learning. CoRR (2024)
Saurabh Agarwal, Bilge Acun, Basil Hosmer, Mostafa Elhoushi, Yejin Lee, Shivaram Venkataraman, Dimitris Papailiopoulos, Carole-Jean Wu
CHAI: Clustered Head Attention for Efficient LLM Inference. CoRR (2024)
Mark Zhao, Satadru Pan, Niket Agarwal, Zhaoduo Wen, David Xu, Anand Natarajan, Pavan Kumar, Shiva Shankar P., Ritesh Tijoriwala, Karan Asher, Hao Wu, Aarti Basant, Daniel Ford, Delia David, Nezih Yigitbasi, Pratap Singh, Carole-Jean Wu
Tectonic-Shift: A Composite Storage Fabric for Large-Scale ML Training. USENIX Annual Technical Conference (2023)
Ashkan Yousefpour, Shen Guo, Ashish Shenoy, Sayan Ghosh, Pierre Stock, Kiwan Maeng, Schalk-Willem Krüger, Michael Rabbat, Carole-Jean Wu, Ilya Mironov
Green Federated Learning. CoRR (2023)
Lingjiao Chen, Bilge Acun, Newsha Ardalani, Yifan Sun, Feiyang Kang, Hanrui Lyu, Yongchan Kwon, Ruoxi Jia, Carole-Jean Wu, Matei Zaharia, James Zou
Data Acquisition: A New Frontier in Data-centric AI. CoRR (2023)
Young Geun Kim, Udit Gupta, Andrew McCrabb, Yonglak Son, Valeria Bertacco, David Brooks, Carole-Jean Wu
GreenScale: Carbon-Aware Systems for Edge Computing. CoRR (2023)
Samuel Hsia, Udit Gupta, Bilge Acun, Newsha Ardalani, Pan Zhong, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
MP-Rec: Hardware-Software Co-design to Enable Multi-path Recommendation. ASPLOS (3) (2023)
Jhe-Yu Liou, Stephanie Forrest, Carole-Jean Wu
GEVO-ML: Optimizing Machine Learning Code with Evolutionary Computation. CoRR (2023)
Jiali Xing, Bilge Acun, Aditya Sundarrajan, David Brooks, Manoj Chakkaravarthy, Nikky Avila, Carole-Jean Wu, Benjamin C. Lee
Carbon Responder: Coordinating Demand Response for the Datacenter Fleet. CoRR (2023)
Carole-Jean Wu
Special Issue on Environmentally Sustainable Computing. IEEE Micro 43 (1) (2023)
Mariam Elgamal, Doug Carmean, Elnaz Ansari, Okay Zed, Ramesh Peri, Srilatha Manne, Udit Gupta, Gu-Yeon Wei, David Brooks, Gage Hills, Carole-Jean Wu
Design Space Exploration and Optimization for Carbon-Efficient Extended Reality Systems. CoRR (2023)
Udit Gupta, Mariam Elgamal, Gage Hills, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu
Footprint Tool: Designing Sustainable Computer Systems With an Architectural Carbon Modeling Tool. IEEE Micro 43 (4) (2023)
Alicia Golden, Samuel Hsia, Fei Sun, Bilge Acun, Basil Hosmer, Yejin Lee, Zachary DeVito, Jeff Johnson, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
Generative AI Beyond LLMs: System Implications of Multi-Modal Generation. CoRR (2023)
Bilge Acun, Benjamin Lee, Fiodar Kazhamiaka, Kiwan Maeng, Udit Gupta, Manoj Chakkaravarthy, David Brooks, Carole-Jean Wu
Carbon Explorer: A Holistic Framework for Designing Carbon Aware Datacenters. ASPLOS (2) (2023)
Samuel Hsia, Udit Gupta, Bilge Acun, Newsha Ardalani, Pan Zhong, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
MP-Rec: Hardware-Software Co-Design to Enable Multi-Path Recommendation. CoRR (2023)
Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Raje, Max Bartolo, Evan Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas W. Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Y. Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi
DataPerf: Benchmarks for Data-Centric AI Development. NeurIPS (2023)
Yu Yang, Aaditya K. Singh, Mostafa Elhoushi, Anas Mahmoud, Kushal Tirumala, Fabian Gloeckle, Baptiste Rozière, Carole-Jean Wu, Ari S. Morcos, Newsha Ardalani
Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data. CoRR (2023)
Sid Wang, John Nguyen, Ke Li, Carole-Jean Wu
READ: Recurrent Adaptation of Large Transformers. CoRR (2023)
Geet Sethi, Pallab Bhattacharya, Dhruv Choudhary, Carole-Jean Wu, Christos Kozyrakis
FlexShard: Flexible Sharding for Industry-Scale Sequence Recommendation Models. CoRR (2023)
Mariam Elgamal, Doug Carmean, Elnaz Ansari, Okay Zed, Ramesh Peri, Srilatha Manne, Udit Gupta, Gu-Yeon Wei, David Brooks, Gage Hills, Carole-Jean Wu
Carbon-Efficient Design Optimization for Computing Systems. HotCarbon (2023)
Mark Zhao, Dhruv Choudhary, Devashish Tyagi, Ajay Somani, Max Kaplan, Sung-Han Lin, Sarunya Pumma, Jongsoo Park, Aarti Basant, Niket Agarwal, Carole-Jean Wu, Christos Kozyrakis
RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure. MLSys (2023)
Haiyang Huang, Newsha Ardalani, Anna Sun, Liu Ke, Hsien-Hsin S. Lee, Anjali Sridhar, Shruti Bhosale, Carole-Jean Wu, Benjamin Lee
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference. CoRR (2023)
Meisam Hejazinia, Dzmitry Huba, Ilias Leontiadis, Kiwan Maeng, Mani Malek, Luca Melis, Ilya Mironov, Milad Nasr, Kaikai Wang, Carole-Jean Wu
Federated Ensemble Learning: Increasing the Capacity of Label Private Recommendation Systems. IEEE Data Eng. Bull. 46 (1) (2023)
Samuel Hsia, Alicia Golden, Bilge Acun, Newsha Ardalani, Zachary DeVito, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
MAD Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems. CoRR (2023)
Newsha Ardalani, Carole-Jean Wu, Zeliang Chen, Bhargav Bhushanam, Adnan Aziz
Understanding Scaling Laws for Recommendation Models. CoRR (2022)
Liu Ke, Udit Gupta, Mark Hempstead, Carole-Jean Wu, Hsien-Hsin S. Lee, Xuan Zhang
Hercules: Heterogeneity-Aware Inference Serving for At-Scale Personalized Recommendation. CoRR (2022)
Noveen Sachdeva, Mehak Preet Dhaliwal, Carole-Jean Wu, Julian J. McAuley
Infinite Recommendation Networks: A Data-Centric Approach. NeurIPS (2022)
Meisam Hejazinia, Dzmitry Huba, Ilias Leontiadis, Kiwan Maeng, Mani Malek, Luca Melis, Ilya Mironov, Milad Nasr, Kaikai Wang, Carole-Jean Wu
FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning. CoRR (2022)
Chun-Feng Wu, Carole-Jean Wu, Gu-Yeon Wei, David Brooks
A joint management middleware to improve training performance of deep recommendation systems with SSDs. DAC (2022)
Geet Sethi, Bilge Acun, Niket Agarwal, Christos Kozyrakis, Caroline Trippel, Carole-Jean Wu
RecShard: statistical feature-based memory optimization for industry-scale neural recommendation. ASPLOS (2022)
Dzmitry Huba, John Nguyen, Kshitiz Malik, Ruiyu Zhu, Mike Rabbat, Ashkan Yousefpour, Carole-Jean Wu, Hongyuan Zhan, Pavel Ustinov, Harish Srinivas, Kaikai Wang, Anthony Shoumikhin, Jesik Min, Mani Malek
PAPAYA: Practical, Private, and Scalable Federated Learning. MLSys (2022)
Kiwan Maeng, Haiyu Lu, Luca Melis, John Nguyen, Mike Rabbat, Carole-Jean Wu
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity. RecSys (2022)
Mehdi Ghasemi, Daler N. Rakhmatov, Carole-Jean Wu, Sarma B. K. Vrudhula
EdgeWise: Energy-efficient CNN Computation on Edge Devices under Stochastic Communication Delays. ACM Trans. Embed. Comput. Syst. 21 (5) (2022)
Noveen Sachdeva, Carole-Jean Wu, Julian J. McAuley
On Sampling Collaborative Filtering Datasets. WSDM (2022)
Noveen Sachdeva, Mehak Preet Dhaliwal, Carole-Jean Wu, Julian J. McAuley
Infinite Recommendation Networks: A Data-Centric Approach. CoRR (2022)
Mark Zhao, Niket Agarwal, Aarti Basant, Bugra Gedik, Satadru Pan, Mustafa Ozdal, Rakesh Komuravelli, Jerry Pan, Tianshu Bao, Haowei Lu, Sundaram Narayanan, Jack Langman, Kevin Wilfong, Harsha Rastogi, Carole-Jean Wu, Christos Kozyrakis, Parik Pol
Understanding data storage and ingestion for large-scale deep recommendation model training: industrial product. ISCA (2022)
Geet Sethi, Bilge Acun, Niket Agarwal, Christos Kozyrakis, Caroline Trippel, Carole-Jean Wu
RecShard: Statistical Feature-Based Memory Optimization for Industry-Scale Neural Recommendation. CoRR (2022)
Young Geun Kim, Carole-Jean Wu
FedGPO: Heterogeneity-Aware Global Parameter optimization for Efficient Federated Learning. IISWC (2022)
Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Juan Ciro, Lora Aroyo, Bilge Acun, Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Tariq Kane, Christine R. Kirkpatrick, Tzu-Sheng Kuo, Jonas Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi
DataPerf: Benchmarks for Data-Centric AI Development. CoRR (2022)
Young Geun Kim, Carole-Jean Wu
FedGPO: Heterogeneity-Aware Global Parameter Optimization for Efficient Federated Learning. CoRR (2022)
Jhe-Yu Liou, Muaaz Awan, Steven A. Hofmeyr, Stephanie Forrest, Carole-Jean Wu
Understanding the Power of Evolutionary Computation for GPU Code Optimization. IISWC (2022)
Bilge Acun, Benjamin Lee, Kiwan Maeng, Manoj Chakkaravarthy, Udit Gupta, David Brooks, Carole-Jean Wu
A Holistic Approach for Designing Carbon Aware Datacenters. CoRR (2022)
Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga Behram, Jinshi Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim M. Hazelwood
Sustainable AI: Environmental Implications, Challenges and Opportunities. MLSys (2022)
Udit Gupta, Young Geun Kim, Sylvia Lee, Jordan Tse, Hsien-Hsin S. Lee, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
Chasing Carbon: The Elusive Environmental Footprint of Computing. IEEE Micro 42 (4) (2022)
Mark Zhao, Dhruv Choudhary, Devashish Tyagi, Ajay Somani, Max Kaplan, Sung-Han Lin, Sarunya Pumma, Jongsoo Park, Aarti Basant, Niket Agarwal, Carole-Jean Wu, Christos Kozyrakis
RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure. CoRR (2022)
Liu Ke, Udit Gupta, Mark Hempstead, Carole-Jean Wu, Hsien-Hsin S. Lee, Xuan Zhang
Hercules: Heterogeneity-Aware Inference Serving for At-Scale Personalized Recommendation. HPCA (2022)
Kiwan Maeng, Haiyu Lu, Luca Melis, John Nguyen, Mike Rabbat, Carole-Jean Wu
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity. CoRR (2022)
Udit Gupta, Mariam Elgamal, Gage Hills, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu
ACT: designing sustainable computer systems with an architectural carbon modeling tool. ISCA (2022)
Noveen Sachdeva, Carole-Jean Wu, Julian J. McAuley
On Sampling Collaborative Filtering Datasets. CoRR (2022)
Jhe-Yu Liou, Muaaz Awan, Steven A. Hofmeyr, Stephanie Forrest, Carole-Jean Wu
Understanding the Power of Evolutionary Computation for GPU Code Optimization. CoRR (2022)
Wenjie Xiong, Liu Ke, Dimitrije Jankov, Michael Kounavis, Xiaochen Wang, Eric Northup, Jie Amy Yang, Bilge Acun, Carole-Jean Wu, Ping Tak Peter Tang, G. Edward Suh, Xuan Zhang, Hsien-Hsin S. Lee
SecNDP: Secure Near-Data Processing with Untrusted Memory. HPCA (2022)
Soroush Heidari, Mehdi Ghasemi, Young Geun Kim, Carole-Jean Wu, Sarma B. K. Vrudhula
CAMDNN: Content-Aware Mapping of a Network of Deep Neural Networks on Edge MPSoCs. IEEE Trans. Computers 71 (12) (2022)
Wenjie Xiong, Liu Ke, Dimitrije Jankov, Michael Kounavis, Xiaochen Wang, Eric Northup, Jie Amy Yang, Bilge Acun, Carole-Jean Wu, Ping Tak Peter Tang, G. Edward Suh, Xuan Zhang, Hsien-Hsin S. Lee
SecNDP: Secure Near-Data Processing with Untrusted Memory. IACR Cryptol. ePrint Arch. 2021 (2021)
Udit Gupta, Samuel Hsia, Jeff Jun Zhang, Mark Wilkening, Javin Pombra, Hsien-Hsin S. Lee, Gu-Yeon Wei, Carole-Jean Wu, David Brooks
RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance. CoRR (2021)
Mark Wilkening, Udit Gupta, Samuel Hsia, Caroline Trippel, Carole-Jean Wu, David Brooks, Gu-Yeon Wei
RecSSD: near data processing for solid state drive based recommendation inference. ASPLOS (2021)
Zhaoxia Deng, Jongsoo Park, Ping Tak Peter Tang, Haixin Liu, Jie Yang, Hector Yuen, Jianyu Huang, Daya Shanker Khudia, Xiaohan Wei, Ellie Wen, Dhruv Choudhary, Raghuraman Krishnamoorthi, Carole-Jean Wu, Nadathur Satish, Changkyu Kim, Maxim Naumov, Sam Naghshineh, Mikhail Smelyanskiy
Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale. IEEE Micro 41 (5) (2021)
Yu Emma Wang, Carole-Jean Wu, Xiaodong Wang, Kim M. Hazelwood, David Brooks
Exploiting Parallelism Opportunities with Deep Learning Frameworks. ACM Trans. Archit. Code Optim. 18 (1) (2021)
Chunxing Yin, Bilge Acun, Xing Liu, Carole-Jean Wu
TT-Rec: Tensor Train Compression for Deep Learning Recommendation Models. CoRR (2021)
Michael Lui, Yavuz Yetim, Özgür Özkan, Zhuoran Zhao, Shin-Yeh Tsai, Carole-Jean Wu, Mark Hempstead
Understanding Capacity-Driven Scale-Out Neural Recommendation Inference. ISPASS (2021)
Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga Behram, James Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim Hazelwood
Sustainable AI: Environmental Implications, Challenges and Opportunities. CoRR (2021)
Udit Gupta, Young Geun Kim, Sylvia Lee, Jordan Tse, Hsien-Hsin S. Lee, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
Chasing Carbon: The Elusive Environmental Footprint of Computing. HPCA (2021)
Mark Zhao, Niket Agarwal, Aarti Basant, Bugra Gedik, Satadru Pan, Mustafa Ozdal, Rakesh Komuravelli, Jerry Pan, Tianshu Bao, Haowei Lu, Sundaram Narayanan, Jack Langman, Kevin Wilfong, Harsha Rastogi, Carole-Jean Wu, Christos Kozyrakis, Parik Pol
Understanding and Co-designing the Data Ingestion Pipeline for Industry-Scale RecSys Training. CoRR (2021)
Mehdi Ghasemi, Soroush Heidari, Young Geun Kim, Aaron Lamb, Carole-Jean Wu, Sarma B. K. Vrudhula
Energy-Efficient Mapping for a Network of DNN Models at the Edge. SMARTCOMP (2021)
Vijay Janapa Reddi, Christine Cheng, David Kanter, Peter Mattson, Guenther Schmuelling, Carole-Jean Wu
The Vision Behind MLPerf: Understanding AI Inference Performance. IEEE Micro 41 (3) (2021)
Carole-Jean Wu, Srilatha Manne, Parthasarathy Ranganathan, Sarah Bird, Shane Greenstein
Socio-Technological Challenges and Opportunities: Paths Forward. CoRR (2021)
Mark Wilkening, Udit Gupta, Samuel Hsia, Caroline Trippel, Carole-Jean Wu, David Brooks, Gu-Yeon Wei
RecSSD: Near Data Processing for Solid State Drive Based Recommendation Inference. CoRR (2021)
Kiwan Maeng, Shivam Bharuka, Isabel Gao, Mark C. Jeffrey, Vikram Saraph, Bor-Yiing Su, Caroline Trippel, Jiyan Yang, Mike Rabbat, Brandon Lucia, Carole-Jean Wu
Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery. MLSys (2021)
Chunxing Yin, Bilge Acun, Carole-Jean Wu, Xing Liu
TT-Rec: Tensor Train Compression for Deep Learning Recommendation Models. MLSys (2021)
Udit Gupta, Samuel Hsia, Jeff Zhang, Mark Wilkening, Javin Pombra, Hsien-Hsin Sean Lee, Gu-Yeon Wei, Carole-Jean Wu, David Brooks
RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance. MICRO (2021)
Venkatesh Kodukula, Saad Katrawala, Britton Jones, Carole-Jean Wu, Robert LiKamWa
Dynamic Temperature Management of Near-Sensor Processing for Energy-Efficient High-Fidelity Imaging. Sensors 21 (3) (2021)
Noveen Sachdeva, Carole-Jean Wu, Julian J. McAuley
SVP-CF: Selection via Proxy for Collaborative Filtering Data. CoRR (2021)
Dzmitry Huba, John Nguyen, Kshitiz Malik, Ruiyu Zhu, Mike Rabbat, Ashkan Yousefpour, Carole-Jean Wu, Hongyuan Zhan, Pavel Ustinov, Harish Srinivas, Kaikai Wang, Anthony Shoumikhin, Jesik Min, Mani Malek
Papaya: Practical, Private, and Scalable Federated Learning. CoRR (2021)
Bilge Acun, Matthew Murphy, Xiaodong Wang, Jade Nie, Carole-Jean Wu, Kim M. Hazelwood
Understanding Training Efficiency of Deep Learning Recommendation Models at Scale. HPCA (2021)
Zhaoxia Deng, Jongsoo Park, Ping Tak Peter Tang, Haixin Liu, Jie Yang, Hector Yuen, Jianyu Huang, Daya Shanker Khudia, Xiaohan Wei, Ellie Wen, Dhruv Choudhary, Raghuraman Krishnamoorthi, Carole-Jean Wu, Nadathur Satish, Changkyu Kim, Maxim Naumov, Sam Naghshineh, Mikhail Smelyanskiy
Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale. CoRR (2021)
Young Geun Kim, Carole-Jean Wu
AutoFL: Enabling Heterogeneity-Aware Energy Efficient Federated Learning. CoRR (2021)
Young Geun Kim, Carole-Jean Wu
AutoFL: Enabling Heterogeneity-Aware Energy Efficient Federated Learning. MICRO (2021)
Young Geun Kim, Carole-Jean Wu
AutoScale: Energy Efficiency Optimization for Stochastic Edge Inference Using Reinforcement Learning. MICRO (2020)
Jhe-Yu Liou, Xiaodong Wang, Stephanie Forrest, Carole-Jean Wu
GEVO-ML: a proposal for optimizing ML code with evolutionary computation. GECCO Companion (2020)
Udit Gupta, Samuel Hsia, Vikram Saraph, Xiaodong Wang, Brandon Reagen, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu
DeepRecSys: A System for Optimizing End-To-End At-Scale Neural Recommendation Inference. ISCA (2020)
Jhe-Yu Liou, Xiaodong Wang, Stephanie Forrest, Carole-Jean Wu
GEVO: GPU Code Optimization Using Evolutionary Computation. ACM Trans. Archit. Code Optim. 17 (4) (2020)
Udit Gupta, Carole-Jean Wu, Xiaodong Wang, Maxim Naumov, Brandon Reagen, David Brooks, Bradford Cottel, Kim M. Hazelwood, Mark Hempstead, Bill Jia, Hsien-Hsin S. Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, Xuan Zhang
The Architectural Implications of Facebook's DNN-Based Personalized Recommendation. HPCA (2020)
Kiwan Maeng, Shivam Bharuka, Isabel Gao, Mark C. Jeffrey, Vikram Saraph, Bor-Yiing Su, Caroline Trippel, Jiyan Yang, Mike Rabbat, Brandon Lucia, Carole-Jean Wu
CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery. CoRR (2020)
Udit Gupta, Samuel Hsia, Vikram Saraph, Xiaodong Wang, Brandon Reagen, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu
DeepRecSys: A System for Optimizing End-To-End At-scale Neural Recommendation Inference. CoRR (2020)
Carole-Jean Wu, Robin Burke, Ed Chi, Joseph A. Konstan, Julian J. McAuley, Yves Raimond, Hao Zhang
Developing a Recommendation Benchmark for MLPerf Training and Inference. CoRR (2020)
Jhe-Yu Liou, Xiaodong Wang, Stephanie Forrest, Carole-Jean Wu
GEVO: GPU Code Optimization using Evolutionary Computation. CoRR (2020)
Young Geun Kim, Carole-Jean Wu
AutoScale: Optimizing Energy Efficiency of End-to-End Edge Inference under Stochastic Variance. CoRR (2020)
Michael Lui, Yavuz Yetim, Özgür Özkan, Zhuoran Zhao, Shin-Yeh Tsai, Carole-Jean Wu, Mark Hempstead
Understanding Capacity-Driven Scale-Out Neural Recommendation Inference. CoRR (2020)
Vijay Janapa Reddi, Christine Cheng, David Kanter, Peter Mattson, Guenther Schmuelling, Carole-Jean Wu, Brian Anderson, Maximilien Breughe, Mark Charlebois, William Chou, Ramesh Chukka, Cody Coleman, Sam Davis, Pan Deng, Greg Diamos, Jared Duke, Dave Fick, J. Scott Gardner, Itay Hubara, Sachin Idgunji, Thomas B. Jablin, Jeff Jiao, Tom St. John, Pankaj Kanwar, David Lee, Jeffery Liao, Anton Lokhmotov, Francisco Massa, Peng Meng, Paulius Micikevicius, Colin Osborne, Gennady Pekhimenko, Arun Tejusve Raghunath Rajan, Dilip Sequeira, Ashish Sirasao, Fei Sun, Hanlin Tang, Michael Thomson, Frank Wei, Ephrem Wu, Lingjie Xu, Koichi Yamada, Bing Yu, George Yuan, Aaron Zhong, Peizhao Zhang, Yuchen Zhou
MLPerf Inference Benchmark. ISCA (2020)
Samuel Hsia, Udit Gupta, Mark Wilkening, Carole-Jean Wu, Gu-Yeon Wei, David Brooks
Cross-Stack Workload Characterization of Deep Recommendation Systems. IISWC (2020)

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Carole-Jean Wu