Venue of ACM SIGMETRICS 2023


Orlando, Florida, USA
June 19-22, 2023


Day 1: June 19, 2023 (Monday) - Workshops / Tutorials

Detailed schedule: Please refer to the individual workshop pages for respective schedules.

Workshop 1: MAthematical performance Modeling and Analysis (MAMA)

8:25 am - 11:30 am EST (June 19, 2023)

Workshop 2: Teaching Performance Analysis of Computer Systems (TeaPACS)

9:15 am - 11:30 am EST (June 19, 2023)

Workshop 3: Causal Inference for Engineers

8:00 am - 11:30 am EST (June 19, 2023)

Workshop 4: Learning-augmented Algorithms: Theory and Applications

8:00 am - 11:30 am EST (June 19, 2023)

Tutorial 1 / Workshop 5

8:00 am - 10:00 am EST (June 19, 2023)

10:00 am - 11:00 am EST (June 19, 2023)

Tutorial 2: A Modern Approach to Product-forms and Reversibility for the Quantitative Analysis of Computer Systems

9:00 am - 11:00 am EST (June 19, 2023)

FCRC Plenary Talk

11:30 am - 12:30 pm EST (June 19, 2023)

Workshop 1: MAthematical performance Modeling and Analysis (MAMA)

1:30 pm - 6:00 pm EST (June 19, 2023)

Workshop 2: Teaching Performance Analysis of Computer Systems (TeaPACS)

1:30 pm - 6:00 pm EST (June 19, 2023)

Workshop 3: Causal Inference for Engineers

1:30 pm - 6:00 pm EST (June 19, 2023)

Workshop 6: Measurements for Self-Driving Networks

1:30 pm - 6:00 pm EST (June 19, 2023)

Workshop 5: Quantum Systems and Computation Part II

1:30 pm - 6:00 pm EST (June 19, 2023)

Tutorial 3

2:00 pm - 3:30 pm EST (June 19, 2023)

4:00 pm - 5:30 pm EST (June 19, 2023)

Business Meeting (open to all)

6:00 - pm - 6:45 pm EST (June 19, 2023)

Women and Non-Binary Networking Dinner: Joint Event with e-Energy (tentative)

7:00 - pm - 8:00 pm EST (June 19, 2023)

Day 2: June 20, 2023 (Tuesday) - Main Conference

Opening Session

8:45 am - 9:15 am EST (June 20, 2023)

Achievement Award Talk: Laurent Massoulié

9:15 am - 10:15 am EST (June 20, 2023)
Fast Distributed Optimization with Asynchrony and Time Delays
  • Abstract: The training of models over distributed data calls for distributed optimization schemes. This has motivated research on distributed convex optimization, leading to the identification of lower bounds on convergence speed, and distributed optimization algorithms with convergence speed potentially matching these lower bounds, for a variety of settings. In this talk we focus on the important setting of asynchronous operation, for which we propose optimization algorithms with optimal speed. We next consider systems with heterogeneous communication and computation delays, for which we propose fast asynchronous algorithms adapted to these heterogeneous delays.
  • Bio: Laurent Massoulié is research director at Inria, head of the Microsoft Research – Inria Joint Centre, and professor at the Applied Maths Centre of Ecole Polytechnique. His research interests are in machine learning, probabilistic modelling and algorithms for networks. He has held research scientist positions at: France Telecom, Microsoft Research, Thomson-Technicolor, where he headed the Paris Research Lab. He obtained best paper awards at IEEE INFOCOM 1999, ACM SIGMETRICS 2005, ACM CoNEXT 2007, NeurIPS 2018, NeurIPS 2021, was elected "Technicolor Fellow" in 2011, received the "Grand Prix Scientifique" of the Del Duca Foundation delivered by the French Academy of Science in 2017, and is a Fellow of the “Prairie” Institute.

Rising Star Research Award Talk: Weina Wang

10:15 am - 11:15 am EST (June 20, 2023)
Large Stochastic Systems: Many to One and One to Many
  • Abstract: Large-scale systems, such as large computing systems, communication systems, online delivery platforms, and online social networks, are prevalent in our society today. To understand these systems and design decision-making algorithms for them, large stochastic systems provide a fundamental mathematical framework. In this talk, we delve into two distinct and complementary perspectives for studying large stochastic systems with many components. The first perspective, which we refer to as the "many-to-one" perspective, appears widely in existing literature on mean-field analysis. This perspective offers an intuitive way of constructing a single-component system, whose equilibrium provides an approximation for the stationary behavior of the original many-component problem. This many-to-one perspective often provides insights into analyzing the system under specific algorithms. I will then focus on a new perspective/framework that we devise, which we call the “one-to-many” framework, primarily targeted at algorithm design rather than analysis. Under this framework, we first develop an algorithm for a single-component problem, and then convert it into an algorithm for the original many-component problem. I will demonstrate this framework in a server-utilization maximization problem and the restless bandit problem.
  • Bio: Weina Wang is an Assistant Professor in the Computer Science Department at Carnegie Mellon University. Her research lies in the broad area of applied probability and stochastic systems, with applications in large computing systems, random graph alignment, and privacy-preserving data analytics. She was a joint postdoctoral research associate in the Coordinated Science Lab at the University of Illinois at Urbana-Champaign, and in the School of ECEE at Arizona State University, from 2016 to 2018. She received her Ph.D. degree in Electrical Engineering from Arizona State University in 2016, and her Bachelor’s degree from the Department of Electronic Engineering at Tsinghua University in 2009. Her dissertation received the Dean’s Dissertation Award in the Ira A. Fulton Schools of Engineering at Arizona State University in 2016. She received the Kenneth C. Sevcik Outstanding Student Paper Award at ACM SIGMETRICS 2016, the Best Paper Award at ACM MobiHoc 2022, and an NSF CAREER award in 2022.

FCRC Plenary Talk

11:30 am - 12:30 pm EST (June 20, 2023)

Session 1A: Cloud and Datacenter 1 (Disaggregation and Emerging Infrastructure)

2:00 pm - 3:20 pm EST (June 20, 2023)
Session Chair: Anshul Gandhi

  • Memtrade: Marketplace for Disaggregated Memory on Clouds by Hasan Al Maruf (University of Michigan), Yuhong Zhong (Columbia University), Hongyi Wang (Columbia University), Mosharaf Chowdhury (University of Michigan), Asaf Cidon (Columbia University), and Carl Waldspurger (Carl Waldspurger Consulting)
  • Mars: Near-Optimal Throughput with Shallow Buffers in Reconfigurable Datacenter Networks by Vamsi Addanki (TU Berlin), Chen Avin (Ben Gurion University of the Negev), and Stefan Schmid (TU Berlin)
  • DaeMon: Architectural Support for Efficient Data Movement in Fully Disaggregated Systems by Christina Giannoula (National Technical University of Athens), Kailong Huang (University of Toronto), Jonathan Tang (University of Toronto), Nectarios Koziris (National Technical University of Athens, Greece), Georgios Goumas (National Technical University of Athens), Zeshan Chishti (Intel Corporation), and Nandita Vijaykumar (University of Toronto)
  • Duo: A High-Throughput Reconfigurable Datacenter Network Using Local Routing and Control by Johannes Zerwas (Technische Universität München), Csaba Györgyi (ELTE Eötvös Loránd University, Budapest, Hungary), Andreas Blenk (Siemens AG), Stefan Schmid (TU Berlin), and Chen Avin (Ben Gurion University of the Negev)

Session 1B: Online Optimization 1

2:00 pm - 3:00 pm EST (June 20, 2023)
Session Chair: Lili Su

  • Online Fair Allocation with Perishable Resources by Sean R. Sinclair (Cornell University), Chamsi Hssaine (Amazon), and Siddhartha Banerjee (Cornell University)
  • Dynamic Bin Packing with Predictions by Mozhengfu Liu (Nanyang Technological University), and Xueyan Tang (Nanyang Technological University)
  • The Online Knapsack Problem with Departures by Bo Sun (The Chinese University of Hong Kong), Lin Yang (The Chinese University of Hong Kong), Mohammad Hajiesmaili (University of Massachusetts Amherst), Adam Wierman (California Institute of Technology), John C. S. Lui (The Chinese University of Hong Kong), Don Towsley (University of Massachusetts - Amherst), and Danny H. K. Tsang (The Hong Kong University of Science and Technology)

FCRC Plenary Panel

4:15 pm - 5:15 pm EST (June 20, 2023)

Reception and SRC Poster Session

6:00 pm - 7:45 pm EST (June 20, 2023)

Day 3: June 21, 2023 (Wednesday) - Main Conference

Session 2A: Cloud & Datacenter 2 (Efficient IO)

9:00 am - 10:00 am EST (June 21, 2023)
Session Chair: Shaolei Ren

  • Towards Accelerating Data Intensive Application's Shuffle Process Using SmartNICs by Jiaxin Lin (The University of Texas at Austin), Tao Ji (UT Austin), Xiangpeng Hao (UW Madison), Hokeun Cha (UW Madison), Yanfang Le (AMD), Xiangyao Yu (University of Wisconsin - Madison), and Aditya Akella (UT Austin)
  • DiffForward: On Balancing Forwarding Traffic for Modern Cloud Block Services via Differentiated Forwarding by Wenzhe Zhu (University of Science and Technology of China), Yongkun Li (University of Science and Technology of China), Erci Xu (PDL), Fei Li (Alibaba Group), Yinlong Xu (University of Science and Technology of China), and John C. S. Lui (The Chinese University of Hong Kong)
  • SplitRPC: A {Control + Data} Path Splitting RPC Stack for ML Inference Serving by Adithya Kumar (The Pennsylvania State University), Anand Sivasubramaniam (The Pennsylvania State University), and Timothy Zhu (The Pennsylvania State University)

Session 2B: Stochastic Scheduling

9:00 am - 10:00 am EST (June 21, 2023)
Session Chair: Celine Comte

  • Power-of-d Choices Load Balancing in the Sub-Halfin Whitt Regime by Sushil Varma (Georgia Institute of Technology), Francisco Castro (University of California, Los Angeles), and Siva Theja Maguluri (Georgia Tech)
  • On the stochastic and asymptotic improvement of First-Come First-Served and Nudge scheduling by Benny Van Houdt (University of Antwerp)
  • Optimal Scheduling in the Multiserver-job Model under Heavy Traffic by Isaac Grosof (Carnegie Mellon University), Ziv Scully (Carnegie Mellon University), Alan Scheller-Wolf (Carnegie Mellon University), and Mor Harchol-Balter (Carnegie Mellon University)

Session 3A: Cloud & Datacenter 3 (Performance and Resource Management)

10:00 am - 11:00 am EST (June 21, 2023)
Session Chair: Daniel Ratton Figueiredo

  • Go-to-Controller is Better: Efficient and Optimal LPM Caching with Splicing by Itamar Gozlan (Ben-Gurion University of the Negev, Israel), Chen Avin (Ben-Gurion University of the Negev, Israel), Gil Einziger (Ben-Gurion University of the Negev, Israel), and Gabriel Scalosub (Ben-Gurion University of the Negev, Israel)
  • Noise in the Clouds: Influence of Network Performance Variability on Application Scalability by Daniele De Sensi (ETH Zurich), Tiziano De Matteis (ETH Zurich), Konstantin Taranov (ETH Zurich), Salvatore Di Girolamo (ETH Zurich), Tobias Rahn (ETH Zurich), and Torsten Hoefler (ETH Zurich)
  • SMASH: Flexible, Fast, and Resource-efficient Placement and Lookup of Distributed Storage by Yi Liu (University of California Santa Cruz), Shouqian Shi (University of California Santa Cruz), Minghao Xie (University of California Santa Cruz), Heiner Litz (University of California, Santa Cruz), and Chen Qian (University of California Santa Cruz)

Session 3B: Online Optimization 2

10:00 am - 11:00 am EST (June 21, 2023)
Session Chair: Mohammad Hajiesmaili

  • (Private) Kernelized Bandits with Distributed Biased Feedback by Fengjiao Li (Virginia Tech), Xingyu Zhou (Wayne State University), and Bo Ji (Virginia Tech)
  • Online Resource Allocation under Horizon Uncertainty by Santiago Balseiro (Columbia University), Christian Kroer (Columbia University), and Rachitesh Kumar (Columbia University)
  • Streaming Algorithms for Constrained Submodular Maximization by Shuang Cui (University of Science and Technology of China), Kai Han (Soochow University), Jing Tang (The Hong Kong University of Science and Technology), He Huang (Soochow University), Xueying Li (Alibaba Group), and Zhiyu Li (Alibaba Group)

FCRC Plenary Talk

11:30 am - 12:30 pm EST (June 21, 2023)

Session 4A: ML for Systems

2:00 pm - 3:20 pm EST (June 21, 2023)
Session Chair: Adwait Jog

  • PEACH: Proactive and Environment Aware Channel State Information Prediction with Depth Images by Serkut Ayvaşık (Technical University of Munich), Fidan Mehmeti (Technical University of Munich), Edwin Babaians (Technical University of Munich), and Wolfgang Kellerer (Technical University of Munich)
  • FuncPipe: A Pipelined Serverless Framework for Fast and Cost-efficient Training of Deep Learning Models by Yunzhuo Liu (Shanghai Jiao Tong University), Bo Jiang (Shanghai Jiao Tong University), Tian Guo (Worcester Polytechnic Institute), Zimeng Huang (Shanghai Jiao Tong University), Wenhao Ma (Shanghai Jiao Tong University), Xinbing Wang (Shanghai Jiao Tong University), and Chenghu Zhou (Chinese Academy of Sciences)
  • Characterizing the Performance of Accelerated Edge Devices for Training Deep Learning Models by Prashanthi S.K (Indian Institute of Science), Sai Anuroop Kesanapalli (Indian Institute of Science), and Yogesh Simmhan (Indian Institute of Science)
  • Malcolm: Multi-agent Learning for Cooperative Load Management at Rack Scale by Hossein Abbasi Abyaneh (University of Waterloo), Maizi Liao (University of Waterloo), and Seyed Majid Zahedi (University of Waterloo)

Session 4B: Online Optimization 3

2:00 pm - 3:20 pm EST (June 21, 2023)
Session Chair: Danilo Ardagna

  • Robust Multi-Agent Bandits Over Undirected Graphs by Daniel Vial (University of Texas at Austin), Sanjay Shakkottai (University of Texas, Austin), and R Srikant (UIUC)
  • Optimistic No-regret Algorithms for Discrete Caching by Naram Mhaisen (Delft University of Technology), Abhishek Sinha (Tata Institute of Fundamental Research), Georgios Paschos (Amazon), and Georgios Iosifidis (Delft University of Technology)
  • Smoothed Online Optimization with Unreliable Predictions by Daan Rutten (Georgia Institute of Technology), Nicolas Christianson (California Institute of Technology), Debankur Mukherjee (Georgia Institute of Technology), and Adam Wierman (California Institute of Technology)
  • Online Adversarial Stabilization of Unknown Networked Systems by Jing Yu (California Institute of Technology), Dimitar Ho (California Institute of Technology), and Adam Wierman (California Institute of Technology)

Session 5A: Game theory, Pricing & Mean-field Analysis

4:00 pm - 5:20 pm EST (June 21, 2023)
Session Chair: Benny Van Houdt

  • Gacha Game Analysis and Design by Canhui Chen (Tsinghua University) and Zhixuan Fang (Tsinghua Univerisity)
  • Mean-field Analysis for Load Balancing on Spatial Graphs by Daan Rutten (Georgia Institute of Technology) and Debankur Mukherjee (Georgia Institute of Technology)
  • Bias and Refinement of Multiscale Mean Field Models by Sebastian Allmeier (INRIA) and Nicolas Gast (INRIA)
  • Enabling Long-term Fairness in Dynamic Resource Allocation by Tareq Si Salem (Inria, Université Côte d'Azur), Georgios Iosifidis (Delft University of Technology), and Giovanni Neglia (Inria, Université Côte d'Azur)

Session 5B: Network Measurement 1

4:00 pm - 5:20 pm EST (June 21, 2023)
Session Chair: Florin Ciucu

  • A Comparative Analysis of Ookla Speedtest and Measurement Labs Network Diagnostic Test (NDT7) by Kyle MacMillan (University of Chicago), Tarun Mangla (University of Chicago), James Saxon (University of Chicago), Nicole P. Marwell (University of Chicago), and Nick Feamster (University of Chicago)
  • Each at its own pace: Third-party Dependency and Centralization Around the World by Rashna Kumar (Northwestern University), Sana Asif (Northwestern University), Elise Lee (Northwestern University), and Fabi'an E. Bustamante (Northwestern University)
  • Detecting and Measuring Aggressive Location Harvesting in Mobile Apps via Data-flow Path Embedding by Haoran Lu (Indiana University Bloomington), Qingchuan Zhao (City University of Hong Kong), Yongliang Chen (City University of Hong Kong), Xiaojing Liao (Indiana University Bloomington), and Zhiqiang Lin (Ohio State University)
  • Fiat Lux: Illuminating IPv6 Apportionment with Different Datasets by Amanda Hsu (Georgia Institute of Technology), Frank Li (Georgia Institute of Technology), and Paul Pearce (Georgia Institute of Technology)


6:30 pm - 8:30 pm EST (June 21, 2023)

Day 4: June 22, 2023 (Thursday) - Main Conference

Session 6A: Reinforcement Learning

9:00 am - 10:00 am EST (June 22, 2023)
Session Chair: Qiaomin Xie

  • Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes by Dongyan (Lucy) Huo (Cornell University), and Yudong Chen, Qiaomin Xie (University of Wisconsin-Madison)
  • Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning by Yizhou Zhang (Tsinghua University), Guannan Qu (Carnegie Mellon University), Pan Xu (Duke University), Yiheng Lin (California Institute of Technology), Zaiwei Chen (California Institute of Technology), and Adam Wierman (California Institute of Technology)
  • Overcoming the Long Horizon Barrier for Sample-Efficient Reinforcement Learning with Latent Low-Rank Structure by Tyler Sam (Cornell University), Yudong Chen (University of Wisconsin-Madison), and Christina Lee Yu (Cornell University)

Session 6B: Network Measurement 2

9:00 am - 10:00 am EST (June 22, 2023)
Session Chair: Eytan Modiano

  • Network Monitoring on Multi-Pipe Switches by Marco Chiesa (KTH Royal Institute of Technology) and Fábio L. Verdi (LERIS - UFSCar)
  • Real-time Spread Burst Detection in Data Streaming by Haibo Wang (University of Florida), Dimitrios Melissourgos (University of Florida), Chaoyi Ma (University of Florida), and Shigang Chen (University of Florida)
  • JS Capsules: A Framework for Capturing Fine-grained JavaScript Memory Measurements for the Mobile Web by Usama Naseer (Brown University) and Theophilus A. Benson (Brown University and Carnegie Mellon University)

Session 7A: Emerging Architectures

10:00 am - 11:00 am EST (June 22, 2023)
Session Chair: Tian Guo

  • SLITS: Sparsity-Lightened Intelligent Thread Scheduling by Wangkai Jin (Succincter) and Xiangjun Peng (Succincter)
  • Asynchronous Automata Processing on GPUs by Hongyuan Liu (William & Mary / The Hong Kong University of Science and Technology (Guangzhou)), Sreepathi Pai (University of Rochester), and Adwait Jog (William & Mary / University of Virginia)
  • Detecting and Measuring Security Risks of Hosting-Based Dangling Domains by Mingming Zhang (Tsinghua University), Xiang Li (Tsinghua University), Baojun Liu (Tsinghua University), JianYu Lu (Qi An Xin Group Corp.), Yiming Zhang (Tsinghua University), Jianjun Chen (Tsinghua University), Haixin Duan (Institute for Network Science and Cyberspace, Tsinghua University; Qi An Xin Group Corp.), Shuang Hao (University of Texas at Dallas), and Xiaofeng Zheng (Institute for Network Sciences and Cyberspace, Tsinghua University; QiAnXin Technology Research Institute & Legendsec Information Technology (Beijing) Inc.)

Session 7B: Queueing Theory

10:00 am - 11:00 am EST (June 22, 2023)
Session Chair: Weina Wang

  • The M/M/k with deterministic setup times by Jalani K. Williams (Carnegie Mellon University), Mor Harchol-Balter (Carnegie Mellon University), and Weina Wang (Carnegie Mellon University)
  • Joint Learning and Control in Stochastic Queueing Networks with Unknown Utilities by Xinzhe Fu (MIT) and Eytan Modiano (MIT)
  • Constant Regret Primal-Dual Policy for Multi-way Dynamic Matching by Yehua Wei (Duke University), Jiaming Xu (Duke University), and Sophie H. Yu (Duke University)

FCRC Plenary Talk

11:30 am - 12:30 pm EST (June 22, 2023)

SRC Session A: Undergraduate Posters

2:00 pm - 3:00 pm EST (June 22, 2023)
Session Chair: Y. C. Tay

  • Zephyr: An Economically Feasible, Zero-Knowledge Light Client for Enhanced Blockchain by Xiangan He (Boston College)
  • An Energy-efficient Wireless Sensor Network Applied to Greenhouse Cultivation by Beatriz Souza, Marcio Miranda (advisor), and Luiz Maltar (advisor) (Universidade Federal Rural do Rio de Janeiro)
  • Best Practices for Exoskeleton Evaluation Using DeepLabCut by Nishat Ahmed, Amaan Rahman, and Lucia Rhode (The Cooper Union for the Advancement of Science and Art)
  • An End-to-End Benchmarking Tool for Analyzing the Hardware-Software Implications of Multi-modal DNNs by Tianhao Huang, Mo Niu, and Xiaozhi Zhu (Shanghai Jiao Tong University)

SRC Session B: Graduate Posters

2:00 pm - 3:30 pm EST (June 22, 2023)
Session Chair: Sara Alouf

  • Learning the Optimal Representation Dimension for Restricted Boltzmann Machines by Amanda Camacho Novaes de Oliveira (Universidade Federal do Rio de Janeiro (UFRJ))
  • Graph Learning based Performance Analysis for Queueing Networks by Zifeng Niu (Imperial College London)
  • The RESET Technique for Multiserver-Job Analysis by Isaac Grosof (Carnegie Mellon University)
  • PEMA+: A Comprehensive Resource Manager for Microservices by Md Rajib Hossen (The University of Texas at Arlington)
  • Distributed Experimental Design Networks by Yuanyuan Li (Northeastern University)

Session 8A: Security & Privacy

4:00 pm - 5:20 pm EST (June 22, 2023)
Session Chair: Lishan Yang

  • Batching of Tasks by Users of Pseudonymous Forums: Anonymity Compromise and Protection by Alexander Goldberg (Carnegie Mellon University), Giulia Fanti (Carnegie Mellon University), and Nihar Shah (Carnegie Mellon University)
  • Characterizing Cryptocurrency-themed Malicious Browser Extensions by Kailong Wang (National University of Singapore), Yuxi Ling (National University of Singapore), Yanjun Zhang (Deakin University), Zhou Yu (Beijing University of Posts and Telecommunications), Haoyu Wang (Huazhong University of Science and Technology), Guangdong Bai (University of Queensland), Beng Chin Ooi (National University of Singapore), and Jin Song Dong (National University of Singapore)
  • Strategic Latency Reduction in Blockchain Peer-to-Peer Networks by Weizhao Tang (CMU), Lucianna Kiffer (ETH Zurich), Giulia Fanti (CMU), and Ari Juels (Jacobs Institute, Cornell Tech)

Session 8B: Wireless Networks

4:00 pm - 5:20 pm EST (June 22, 2023)
Session Chair: Daniel Ratton Figueiredo

  • Switching in the Rain: Predictive Wireless x-haul Network Reconfiguration by Igor Kadota (Columbia University), Dror Jacoby (Tel Aviv University), Hagit Messer (Tel Aviv University), Gil Zussman (Columbia University), and Jonatan Ostrometzky (Tel Aviv University)
  • A First Look at Wi-Fi 6 in Action: Throughput, Latency, Energy Efficiency, and Security by Ruofeng Liu (Bosch Research) and Nakjung Choi (Ph.D., Network Systems and Security Research, Nokia Bell Labs)
  • CoBF: Coordinated Beamforming in Dense mmWave Networks by Ding Zhang (George Mason University), Panneer Selvam Santhalingam (George Mason University), Parth Pathak (George Mason University), and Zizhan Zheng (Tulane University)
  • Leveraging the Properties of mmWave Signals for 3D Finger Motion Tracking for Interactive IoT Applications by Yilin Liu (Penn State University), Shijia Zhang (Penn State University), Mahanth Gowda (Penn State University), and Srihari Nelakuditi (University of South Carolina)