Publications

• 2022
  • A Survey of Multi-Tenant Deep Learning Inference on GPU, in the workshop of Cloud Intelligence/AIOps, collocated at MLSys’22.
  • F. Yu, Z. Xu, T. Shen, D. Stamoulis, L. Shangguan, D. Wang, M. Zhang, X. Tong, R. Madhok, C. Zhao, X. Li, N. Karianakis, D. Lymberopoulos, C. Liu, A. Li, Y. Chen, and X. Chen. Rethinking Latency-aware DNN Design with GPU Tail Effect Analysis, (Poster) in the 17th European Conference on Computer Systems (EuroSys), 2022.
  • Soobee Lee, Minindu Weerakoon, Jonghyun Choi, Minjia Zhang, Di Wang, Myeongjae Jeon, Carousel Memory: Rethinking the Design of Episodic Memory for Continual Learning, in Proceedings of Design Automation Conference (DAC) https://arxiv.org/pdf/2110.07276.pdf, 2022.
  • F. Yu, Z. Xu, C. Liu, D. Stamoulis, D. Wang, Y. Wang, and X. Chen. AntiDoteX: Attention-based Dynamic Optimization for Neural Network Runtime Efficiency, in the Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2022.
  • F. Yu, D. Wang, Y. Chen, N. Karianakis, T. Shen, P. Yu, D. Lymberopoulos, S. Lu, W. Shi, X. Chen. SC-UDA: Style and Content Gap aware Unsupervised Domain Adaptation for Object Detection, in Proceedings of Winter Conference on Applications of Computer Vision (WACV), 2022.
• 2021
  • F. Yu, S. Bray, D. Wang, L. Shangguan, X. Tang, C. Liu and X. Chen. Automated Runtime-Aware Scheduling for Multi-Tenant DNN Inference on GPU, in Proceedings of the 40th IEEE International Conference on Computer Aided Design (ICCAD), 2021.
  • Fuxun Yu, Zhuwei Qin, Chenchen Liu, Di Wang, and Xiang Chen, REIN the RobuTS: Robust DNN-based Image Recognition in Autonomous Driving Systems, in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Vol 40, Issue 6, pages 1258-1271, June 2021.
  • F. Yu, W. Zhang, Z. Qin, Z. Xu, D. Wang, C. Liu, Z. Tian, and X. Chen, Fed^2: Feature Aligned Federated Learning, to appear in Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021.
• 2020
  • Fuxun Yu, Dimitrios Stamoulis, Di Wang, Dimitrios Lymberopoulos, Xiang Chen, Exploring the Design Space of Efficient Deep Neural Networks, in the 3rd Workshop on Computing Architecture for Edge Computing (ArchEdge), Collocated with the 5th ACM/IEEE Symposium on Edge Computing, Virtual, Nov. 2020.
  • Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu, Diana Marculescu, Single-Path Mobile AutoML: Efficient ConvNet Design and NAS Hyperparameter Optimization, in IEEE Journal of Selected Topics in Signal Processing, Vol 14, Issue 4, Page 609-622, May, 2020.
  • F. Yu, D. Wang, Y. Chen, N. Karianakis, P. Yu, D. Lymberopoulos, X. Chen, Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning, in the 2nd Vision for all Seasons (V4AS) Workshop, collocated with Computer Vision and Pattern Recognition (CVPR) Conference, June, 2020.
  • F. Yu, C. Liu, D. Wang, Y. Wang, and X. Chen. AntiDOte: Attention-based Dynamic Optimization for Neural Network Runtime Efficiency, in Proceedings of the 23rd Design Automation and Test in Europe Conference (DATE), Mar. 2020. (Best Paper Award Nomination)
  • F. Yu, Z. Qin, D. Wang, P. Xu, C. Liu, T. Zhi, and X. Chen. DC-CNN: Computational Flow Redefinition for Efficient CNN Inference through Model Structural Decoupling, in Proceedings of the 23rd Design Automation and Test in Europe Conference (DATE), Mar. 2020.
• 2019
  • Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu, Diana Marculescu, “Single-Path NAS: Designing Hardware-Efficient ConvNets in less than 4 Hours”, to appear in Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2019 (ECML PKDD’19) arXiv link: http://arxiv.org/abs/1904.02877; codebase: https://github.com/dstamoulis/single-path-nas
  • Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu and Diana Marculescu, “Single-Path NAS: Device-Aware Efficient ConvNet Design”, Joint Workshop on On-Device Machine Learning & Compact Deep Neural Network Representations (ODML-CDNNR), colocated with ICML, 2019. (Best Paper Award)
• 2018
  • Mengting Wan, Di Wang, Jie Liu, Paul Bennett, Julian McAuley, “Representing and Recommending Shopping Baskets with Complementarity, Compatibility, and Loyalty”, in Proc. of 2018 ACM Conference on Information and Knowledge Management (CIKM’18), Turin, Italy, Oct. 2018.
  • N. Nasiriani, G. Kesidis, D. Wang, Public Cloud Differential Pricing Design Under Provider and Tenants Joint Demand Response , in Proceedings of the Ninth ACM International Conference on Future Energy Systems (e-Energy), 2018.
  • A. Mamun, I. Narayanan, D. Wang, A. Sivasubramaniam, H. K. Fathy, A Stochastic Optimal Control Approach for Exploring Tradeoffs between Cost Savings and Battery Aging in Datacenters Demand Response, in IEEE Transactions on Control Systems Technology, 26(1):360-367, January 2018
  • Yuanyuan Shi, Bolun Xu, Di Wang, Baosen Zhang, Using Battery Storage for Peak Shaving and Frequency Regulation: Joint Optimization for Superlinear Gains, in IEEE PES Transactions on Power Systems, May, 2018.

• 2017

  • Iyswarya Narayanan, Di Wang, Abdullah-al Mamun, Anand Sivasubramaniam, Hosam Fathy, Sean James, Evaluating Energy Storage for a Multitude of Uses in the Datacenter, in the Proceedings of IEEE International Symposium on Workload Characterization (IISWC), 2017.
  • Neda Nasiriani, George Kesidis, Di Wang, Optimal Peak Shaving Using Batteries at Datacenters: Characterizing the Risks and Benefits, in Proceedings of the IEEE 25th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS) 2017 (Best Paper Award).
  • Iyswarya Narayanan, Bikash Sharma, Di Wang, Sriram Govindan, Laura Caulfield, Anand Sivasubramaniam, Aman Kansal, Jie Liu, Badriddine Khessib and Kushagra Vaid, Rain or Shine? – Making Sense of Cloudy Reliability Data, in Proceedings of the 37th IEEE International Conference on Distributed Computing (ICDCS), 2017.
  • Mengting Wan, Di Wang, Matt Goldman, Matt Taddy, Justin Rao, Jie Liu, Dimitrios Lymberopoulos, Julian McAuley, Modeling Consumer Preferences and Price Sensitivities from Large-Scale Grocery Shopping Transaction Logs, in Proceedings of World Wide Web Conference (WWW), 2017.
• 2016
  • Y. Shi, B. Xu, B. Zhang, D. Wang, Leveraging Energy Storage to Optimize Data Center Electricity Cost in Emerging Power Markets, in Proceedings of the 7th ACM International Conference on Future Energy Systems (e-Energy), 2016.
  • I. Narayanan, D. Wang, M. Jeon, B. Sharma, L. Caulfield, A. Sivasubramaniam, B. Cutler, J. Liu, B. Khessib, K. Vaid, SSD Failures in Datacenters: What, When and Why? , in Proceedings of the 9th ACM International Systems and Storage Conference (Systor), 2016. (Best Student Paper Award)

  • Yang Li, Di Wang, Saugata Ghose, Jie Liu, Sriram Govindan, Sean James, Eric Peterson, John Siegler, Rachata Ausavarungnirun, Onur Mutlu, SizeCap: Coordinating Energy Storage Sizing and Power Capping for Fuel Cell Powered Data Centers, in the 22nd Intl. Symp. on High Performance Computer Architecture (HPCA), 2016. Acceptance ratio: 53/240 (22%).

  • Iyswarya Narayanan, Di Wang, Myeongjae Jeon, Bikash Sharma, Laura Caulfield, Anand Sivasubramaniam, Ben Cutler, Jie Liu, Badriddine Khessib, Kushagra Vaid, SSD Failures in Datacenters: What, When and Why?, ACM SIGMETRICS/IFIP Performance (Poster), 2016.
  • Abdullah-al Mamun, Iyswarya Narayanan, Di Wang, Anand Sivasubramaniam, Hosam K. Fathy, Battery health-conscious online power management for demand response in datacenters with stochastic power demand, IEEE Control Systems Society Conference Management, 2016.
  • Li Zhao, Jacob Brouwer, Sean James, Eric Peterson, Di Wang, and Jie Liu, Fuel Cell Powered Data Centers: In-Rack DC Generation, The Electrochemistry Society Transactions, 71(1): 131-139, 2016.
  • Mark Gottscho, Mohammed Shoaib, Sriram Govindan, Bikash Sharma, Di Wang, and Puneet Gupta, Measuring the Impact of Memory Errors on Application Performance, IEEE Computer Architecture Letters, 2016.
  • A. Mamun, I. Narayanan, D. Wang, A. Sivasubramaniam, H. K. Fathy, Multi-objective Optimization of Demand Response in a Datacenter with Lithium-ion Battery Storage, Journal of Energy Storage, Vol. 7, pp. 258-269, 2016.
• 2015
  • D. Wang, Variability Aware Statistical Timing Modeling Using SPICE Simulations, Lambert Academic Publishing, ISBN 978-3-659-40553-2, 2015.
  • A. Mamun, D. Wang, I. Narayanan, A. Sivasubramaniam, H. Fathy, Physics-based simulation of the impact of demand response on lead-acid emergency power availability in a datacenter, Journal of Power Sources 275, 516-524, Feb, 2015.
  • A. Mamun, I. Narayanan, D. Wang, A. Sivasubramaniam, H. Fathy, Multi-objective Optimization to Minimize Battery Degradation and Electricity Cost for Demand Response in Datacenters, ASME Dynamic Systems and Control Conference, 2015.
• 2014 and Previous Years
  • Iyswarya Narayanan, Di Wang, Abdullah-Al Mamun, Anand Sivasubramaniam, and Hosam K. Fathy, Should We Dual-Purpose Energy Storage in Datacenters for Power Backup and Demand Response? in Workshop on Power-Aware Computing and Systems (HOTPOWER), 2014.
  • Di Wang, Sriram Govindan, Anand Sivasubramaniam, Aman Kansal, Jie Liu and Badriddine Khessib, Underprovisioning Backup Power Infrastructure for Datacenters, in Proceedings of Internatonal Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), Salt Lake City, UT. March 2014.
  • Di Wang, Chuangang Ren, Sriram Govindan, Anand Sivasubramaniam, Bhuvan Urgaonkar, Aman Kansal and Kushagra Vaid, ACE: Abstracting, Characterizing and Exploiting Datacenter Power Demands, In the Proceedings of the IEEE International Symposium on Workload Characterization (IISWC), (Best Paper Award), 2013.
  • Di Wang, Chuangang Ren, Anand Sivasubramaniam, Virtualizing Power Distribution in Datacenters, In the Proceedings of the 40th ACM/IEEE International Symposium on Computer Architecture (ISCA), 2013.
  • Di Wang, Chuangang Ren, Sriram Govindan, Anand Sivasubramaniam, Bhuvan Urgaonkar, Aman Kansal and Kushagra Vaid, ACE: Abstracting, Characterizing and Exploiting Peaks and Valleys in Datacenter Power Consumption, In Proceedings of the ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS, poster),2013.
  • Di Wang, Anand Sivasubramaniam, and Bhuvan Urgaonkar, A Case for Heterogeneous Flash in the Datacenter, In the Workshop on Data Center Performance (DCPerf), colocated with ICDCS, 2013 (Invited Paper).
  • Sriram Govindan, Di Wang, Anand Sivasubramaniam, and Bhuvan Urgaonkar, Aggressive Datacenter Power Provisioning with Batteries, ACM Transactions on Computer Systems (TOCS), 31(1), Feb. 2013. Featured in CACM News
  • Chuangang Ren, Di Wang, Bhuvan Urgaonkar, and Anand Sivasubramaniam, Carbon-Aware Energy Capacity Planning for Datacenters, Proceedings of IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS), 2012, Best Paper Award
  • Di Wang, Chuangang Ren, Anand Sivasubramaniam, Bhuvan Urgaonkar, and Hosam K. Fathy, Energy Storage in Datacenters: What, Where and How Much?, Proceedings of the ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS 2012) Nominated for Best Paper Award.
  • Sriram Govindan, Di Wang, Anand Sivasubramaniam, and Bhuvan Urgaonkar, Leveraging Stored Energy for Handling Power Emergencies in Aggressively Provisioned Datacenters, In the Proceedings of Architectural Support for Programming Languages and Operating Systems (ASPLOS 2012), Pick of the Month of IEEE Sustainable Computing Register, October 2012 .
  • Sriram Govindan, Di Wang, Lydia Chen, Anand Sivasubramaniam, and Bhuvan Urgaonkar, Towards Realizing a Low Cost and Highly Available Datacenter Power Infrastructure, Proceedings of the Fourth Workshop on Power-Aware Computing and Systems (HOTPOWER 2011), co-located with SOSP 2011, Cascais, Portugal, October 2011.
  • Vyas Venkataraman, Di Wang, Wei Qin, Mrinal Bose and Jayanta Bhadra, Simulation of a heterogeneous system at multiple levels of abstraction using Rendezvous based modeling, 10th International Workshop on Microprocessor Test and Verification (MTV’09), Austin, Texas, USA, Dec. 2009.
  • Di Wang, Vyas Venkataraman, Zhen Wang, Wei Qin, Hangsheng Wang, Mrinal Bose, and Jayanta Bhadra, Accelerating Multi-party Scheduling for Transaction-level Modeling, ACM/IEEE Great Lakes Symposium on VLSI (GLSVLSI’09), Boston, USA, May, 2009.
  • Vyas Venkataraman, Di Wang, Atabak Mahram, Wei Qin, Mrinal Bose, and Jayanta Bhadra, Synthesis Oriented Scheduling of Multiparty Rendezvous in Transaction Level Models, IEEE CS Annual Symposium on VLSI (ISVLSI’09), Florida, USA, May, 2009.
  • Kelvin Swartz and Di Wang, Design and Simulation of a High Performance Emergency Data Delivery Protocol, IEEE CS International Conference on Networking and Services (ICNS’07), Athens, Greece, June, 2007.