Carole-Jean Wu is currently a Research Scientist and Technical Lead Manager at Meta AI / FAIR. She is a founding member and a Vice President of MLCommons – a non-profit organization that aims to accelerate machine learning innovations for the benefits of all. Dr. Wu also serves on the MLCommons Board as a Director, chaired the MLPerf Recommendation Benchmark Advisory Board, and co-chaired for MLPerf Inference. Prior to Meta/Facebook, She was an Associate Professor at ASU. 

Dr. Wu’s expertise sits at the intersection of computer architecture and machine learning. Her work spans across datacenter infrastructures and edge systems, such as developing energy- and memory-efficient systems and microarchitectures, optimizing systems for machine learning execution at-scale, and designing learning-based approaches for system design and optimization. She is passionate about pathfinding and tackling system challenges to enable efficient and responsible AI technologies. 

Dr. Wu's work has been recognized with several awards, including IEEE Micro Top Picks and ACM / IEEE Best Paper Awards. In addition, her work has been featured at the MLPerf Inference v0.5 Launch and Results, MaskRCNN2Go for MLPerf, and from Understanding Computing's Carbon Footprint to Designing Low-Carbon Computers of Tech @ Meta, and Bloomberg Green. 

Dr. Wu is the recipient of NSF CAREER Award, CRA-WP Anita Borg Early Career Award Distinction of Honorable Mention, IEEE Young Engineer of the Year Award, Science Foundation Arizona Bisgrove Early Career Scholarship, Facebook AI Infrastructure Mentorship Award, and HPCA and IISWC Hall of Fame. She was the Program Co-Chair of the Conference on Machine Learning and Systems (MLSys 2022), the Program Chair of the IEEE International Symposium on Workload Characterization (IISWC 2018), and the Editor for the IEEE MICRO Special Issue on Environmentally Sustainable Computing. She received her M.A. and Ph.D. degrees in Electrical Engineering from Princeton University and the B.Sc. degree in Electrical and Computer Engineering from Cornell University. 

[Google Scholar]  [dblp]

Research

My work sits in the intersection of computer architecture and machine learning with the following emphasis:

Check out my work on Socio-Technological Challenges and Opportunities: Paths Forward, Sustainable AI: Environmental Implications, Challenges and Opportunities, and thoughts on inclusive approaches to technological innovations: Think Globally, Design Deliberately: Taking an Inclusive Approach to Innovation.

Honors and Awards

2023 IEEE Micro Top Picks for ACT: Designing Sustainable Computer Systems with an Architectural Carbon Modeling Tool

2022 ACM Conference on Recommender Systems Best Paper Award Finalist for Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity

2022 IEEE Micro Top Picks for Chasing Carbon: The Elusive Environmental Footprint of Computing

2021 IEEE Micro Top Picks for The Vision Behind MLPerf: Understanding AI Inference Performance

2021 IEEE Micro Top Picks Honorable Mention for DeepRecSys: A System for Optimizing End-to-end At-scale Neural Recommendation Inference

2020 Distinction of Honorable Mention of the CRA Anita Borg Early Career Award

2019 Facebook AI Infrastructure Mentorship Award

2019 ACM/IEEE ICSE Genetic Improvement on Software Best Paper Award for Genetic Improvement for GPU Code

2018 IEEE ITHERM Best Paper Award for Designing a Temperature Model to Understand the Thermal Challenges of Portable Computing Platforms

2017 NSF CAREER Award

2017 IEEE Young Engineer of the Year Award

2015 IEEE Best of Computer Architecture Letters for Architectural Thermal Energy Harvesting Opportunities for Sustainable Computing

2013 SFAz Bisgrove CAREER Award

2011 Intel PhD Fellowship

2011 IEEE ISPASS Best Paper Nomination for Characterization and Dynamic Mitigation of Intra-Application Cache Interference

2009 Princeton Excellence in Leadership Award 

2006 Princeton PhD Fellowship

Pre-Prints

To appear at USENIX ATC 2023

Mark Zhao, Satadru Pan, Niket Agarwal, Zhaoduo Wen, David Xu, Anand Natarajan, Pavan Kumar, Shiva Shankar, Ritesh Tijoriwala, Karan Asher, Hao Wu, Aarti Basant, Daniel Ford, Delia David, Nezih Yigitbasi, Pratap Singh, Carole-Jean Wu, Christos Kozyrakis. 

To appear at MLSys-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.

Meisam Hejazinia, Dzmitry Huba, Ilias Leontiadis, Kiwan Maeng, Mani Malek, Luca Melis, Ilya Mironov, Milad Nasr, Kaikai Wang, Carole-Jean Wu.

Newsha Ardalani, Carole-Jean Wu, Zeliang Chen, Bhargav Bhushanam, Adnan Aziz.   

Geet Sethi, Pallab Bhattacharya, Dhruv Choudhary, Carole-Jean Wu, Christos Kozyrakis.

Haiyang Huang, Newsha Ardalani, Anna Sun, Liu Ke, Hsien-Hsin S. Lee, Anjali Sridhar, Shruti Bhosale, Carole-Jean Wu, Benjamin Lee.

Young Geun Kim, Udit Gupta, Andrew McCrabb, Yonglak Son, Valeria Bertacco, David Brooks, Carole-Jean Wu.

Mariam Elgamal, Doug Carmean, Elnaz Ansari, Okay Zed, Ramesh Peri, Srilatha Manne, Udit Gupta, Gu-Yeon Wei, David Brooks, Gage Hills, Carole-Jean Wu.

Ashkan Yousefpour, Shen Guo, Ashish Shenoy, Sayan Ghosh, Pierre Stock, Kiwan Maeng, Schalk-Willem Kruger, Mike Rabbat, Carole-Jean Wu, Ilya Mironov.

Sid Wang, John Nguyen, Ke Li, Carole-Jean Wu.

Selected Publications

[ASPLOS-2023] Carbon Explorer: A Holistic Approach for Designing Carbon Aware Datacenters

Bilge Acun, Benjamin C. Lee, Fiodar Kazhamiaka, Kiwan Maeng, Manoj Chakkaravarthy, Udit Gupta, David Brooks, Carole-Jean Wu. [code]

[ASPLOS-2023] MP-Rec: Hardware-Software Co-Design to Enable Multi-Path Recommendation 

Samuel Hsia, Udit Gupta, Bilge Acun, Newsha Ardalani, Pan Zhong, Gu-Yeon Wei, David Brooks, Carole-Jean Wu.

[NeurIPS-2022] Infinite Recommendation Networks: A Data-Centric Approach 

Noveen Sachdeva, Mehak Preet Dhaliwal, Carole-Jean Wu, Julian McAuley. [code: Infinite AE; Data-Distill

Kiwan Maeng, Haiyu Lu, Luca Melis, John Nguyen, Mike Rabbat, Carole-Jean Wu. [code]

Best Paper Award Finalist 

Udit Gupta, Mariam Elgamal, Gage Hills, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu. [code]

IEEE Micro Top Picks 

M. Zhao, N. Agarwal, A. Basant, B. Gedik, S. Pan, M. Ozdal, R. Komuravelli, J. Pan, T. Bao, H. Lu, S. Narayanan, J. Langman, K. Wilfong, H. Rastogi, C.-J. Wu, C. Kozyrakis, P. Pol. 

C.-J. Wu, R. Raghavendra, U. Gupta, B. Acun, N. Ardalani, K. Maeng, F. A. Behram, J. Huang, C. Bai, M. Gschwind, A. Gupta, M. Ott, A. Melnikov, S. Candido, D. Brooks, G. Chauhan, B. Lee, H.-S. S. Lee, B. Akyildiz, M. Balandat, J. Spisak, R. Jain, M. Rabbat, K. Hazelwood.

D. Huba, J. Nguyen, K. Malik, R. Zhu, M. Rabbat, A. Yousefpour, C.-J. Wu, G. Zhan, P. Ustinov, H. Srinivas, K. Wang, A. Shoumikhin, J. Min, M. Malek.

Geet Sethi, Bilge Acun, Niket Agarwal, Christos Kozyrakis, Caroline Trippel, Carole-Jean Wu.

Noveen Sachdeva, Carole-Jean Wu, and Julian McAuley. [code]

Young Geun Kim and Carole-Jean Wu.

U. Gupta, S. Hsia, J. Zhang, M. Wilkening, J. Pombra, H.-S. Lee, G. Wei, C.-J. Wu, and D. Brooks.

Chunxing Yin, Bilge Acun, Xing Liu, and Carole-Jean Wu. [code]

MLSys Outstanding Paper Award

K. Maeng, S. Bharuka, I. Gao, M. Jeffrey, V. Saraph, B.-Y. Su, C. Trippel, J. Yang, M. Rabbat, B. Lucia, and C.-J. Wu.

M. Wilkening, U. Gupta, S. Hsia, C. Trippel, C.-J. Wu, D. Brooks, G.-Y. Wei.

U. Gupta, Y. Kim, S. Lee, J. Tse, H.-H. Lee, G. Wei, D. Brooks, and C.-J. Wu.

IEEE Micro Top Picks 

Bilge Acun, Matthew Murphy, Xiaodong Wang, Jade Nie, Carole-Jean Wu, and Kim Hazelwood.

Young Geun Kim and Carole-Jean Wu.

U. Gupta, S. Hsia, V. Saraph, X. Wang, B. Reagen, G.-Y. Wei, H.-S. Lee, D. Brooks, and C.-J. Wu. [code]

IEEE Micro Top Picks Honorable Mention 

L. Ke, U. Gupta, B. Cho, D. Brooks, V. Chandra, U. Diril, A. Firoozshahian, K. Hazelwood, B. Jia, H.-S. Lee, M. Li, B. Maher, D. Mudigere, M. Naumov, M. Schatz, M. Smelyanskiy, X. Wang, B. Reagen, C.-J. Wu, M. Hempstead,  X. Zhang.

V. Reddi, C. Cheng, D. Kanter, P. Mattson, G. Schmuelling, C.-J. Wu, B. Anderson, M. Breughe, M. Charlebois, W. Chou, R. Chukka, C. Coleman, S. Davis, P. Deng, G. Diamos, J. Duke, D. Fick, J. Gardner, I. Hubara, S. Idgunji, T. Jablin, J. Jiao, T. St. John, P. Kanwar, D. Lee, J. Liao, A. Lokhmotov, F. Massa, P. Meng, P. Micikevicius, C. Osborne, G. Pekhimenko, A. Rajan, D. Sequeira, A. Sirasao, F. Sun, H. Tang, M. Thomson, F. Wei, E. Wu, L. Xu, K. Yamada, B. Yu, G. Yuan, A. Zhong, P. Zhang, Y. Zhou. [code]

IEEE Micro Top Picks -- The Vision Behind MLPerf: Understanding AI Inference Performance

P. Mattson, C. Cheng, C. Coleman, G. Diamos, P. Micikevicius, D. Patterson, H. Tang, G.-Y. Wei, P. Ballis, V. Bittorf, D. Brooks, D. Chen, D. Dutta, U. Gupta, K. Hazelwood, A. Hock, X. Huang, B. Jia, D. Kang, N. Kumar, J. Liao, G. Ma, D. Narayanan, T. Oguntebi, G. Pekhimenko, L. Pentecost, V. Reddi, T. Robie, T. St. John, C.-J. Wu, L. Xu, C. Young, M. Zaharia. [code]

U. Gupta, C.-J. Wu, X. Wang, M. Naumov, B. Reagen, D. Brooks, B. Cottel, K. Hazelwood, M. Hempstead, B. Jia, H.-H. Lee, A. Malevich, D. Mudigere, M. Smelyanskiy, L. Xiong, X. Zhang. 

Carole-Jean Wu, David Brooks, Kevin Chen, Douglas Chen, Sy Choudhury, Marat Dukhan, Kim Hazelwood, Eldad Isaac, Yangqing Jia, Bill Jia, Tommer Leyvand, Hao Lu, Yang Lu, Lin Qiao, Brandon Reagen, Joe Spisak, Fei Sun, Andrew Tulloch, Peter Vajda, Xiaodong Wang, Yanghan Wang, Bram Wasti, Yiming Wu, Ran Xian, Sungjoo Yoo, Peizhao Zhang.

Akhil Arunkumar, Evgeny Bolotin, David Nellans, and Carole-Jean Wu.

[HPCA-2018] LATTE-CC: Latency Tolerance Aware Adaptive Cache Compression Management for Energy Efficient GPUs 

Akhil Arunkumar, Shin-Ying Lee, Vignesh Soundararajan, and Carole-Jean Wu. [paper]

[ISCA-2017] MCM-GPU: Multi-Chip-Module GPUs for Continued Performance Scalability

Akhil Arunkumar, Evgeny Bolotin, Benjamin Cho, Ugljesa Milic, Eiman Ebrahimi, Oreste Villa, Aamer Jaleel, Carole-Jean Wu, and David Nellans. [paper]

[HPCA-2016] Improving Smartphone/Mobile User Experience by Balancing Performance and Energy with Probabilistic QoS Guarantee 

Benjamin Gaudette, Carole-Jean Wu, and Sarma Vrudhula. [paper]

[ISCA-2015] CAWA: Coordinated Warp Scheduling and Cache Prioritization for Critical Warp Acceleration for GPGPU Workloads

Shin-Ying Lee, Akhil Arunkumar, and Carole-Jean Wu. [paper]

[PACT-2014] CAWS: Criticality-Aware Warp Scheduling for GPGPU Workloads

Shin-Ying Lee and Carole-Jean Wu. [paper]

[MICRO-2011] PACMan: Prefetch-Aware Cache Management for High Performance Caching

Carole-Jean Wu, Aamer Jaleel, Will Hasenplaugh, Margaret Martonosi, Simon Steely Jr., and Joel Emer. [paper]

[MICRO-2011] SHiP: Signature-Based Hit Predictor for High Performance Caching

Carole-Jean Wu, Aamer Jaleel, Margaret Martonosi, Simon Steely Jr., and Joel Emer. [paper]

Industry Initiatives and Open Source Software

Fair and useful benchmarks for measuring training and inference performance of machine learning hardware, software, and services 

CVPR-LPCV [Slide Deck][Talk]

Embedded Vision Summit [Slide Deck][Talk]

CLEAR: Computing Landscapes for Environmental Accountability and Responsibility

PERSONAL: Personalized Recommendation Systems and Algorithms 

AutoScale: Energy Efficiency Optimization of Stochastic Edge Inference Using Reinforcement Learning

GEVO: Genetic Improvement of GPU Code

DORA: Optimizing Smartphone Energy Efficiency and Web Browser Performance under Interference

MobileBench: Performance, Energy Characterizations and Architectural Implications of an Emerging Mobile Platform Benchmark Suite

Mentorship of Student and Post-Doctoral Researchers at FAIR

Undergraduate/MS/PhD Advisees and Post-Doctoral Researchers

Outstanding Computer Engineering PhD Graduate Student Award

Received the Outstanding Computer Engineering MS Graduate Student Award

Professional Service

Journal Editor 

Executive Committee

Conference Steering Committee

Award Selection Committee

Technical Program Chair

Technical Program Committee 

Journal Editorial Board

CRA-Widening Participation (WP) Career Mentoring Workshop