USENIX ATC '22 Poster Session

USENIX ATC '22 Poster Session and Reception

The following posters will be presented during the Poster Session and Reception on Tuesday, July 12, 2022, from 6:30 pm–8:00 pm.

Modulo: Finding Convergence Failure Bugs in Distributed Systems with Divergence Resync Models
Beom Heyn Kim, Samsung Research, University of Toronto; Taesoo Kim, Samsung Research, Georgia Institute of Technology; David Lie, University of Toronto

Campo: Cost-Aware Performance Optimization for Mixed-Precision Neural Network Training
Xin He, CSEE, Hunan University & Xidian University; Jianhua Sun and Hao Chen, CSEE, Hunan University; Dong Li, University of California, Merced

Privbox: Faster System Calls Through Sandboxed Privileged Execution
Dmitry Kuznetsov and Adam Morrison, Tel Aviv University

CBMM: Financial Advice for Kernel Memory Managers
Mark Mansi, Bijan Tabatabai, and Michael M. Swift, University of Wisconsin - Madison

Investigating Managed Language Runtime Performance: Why JavaScript and Python are 8x and 29x slower than C++, yet Java and Go can be Faster?
David Lion, University of Toronto and YScope Inc.; Adrian Chiu and Michael Stumm, University of Toronto; Ding Yuan, University of Toronto and YScope Inc.

CoVA: Exploiting Compressed-Domain Analysis to Accelerate Video Analytics
Jinwoo Hwang, Minsu Kim, Daeun Kim, Seungho Nam, Yoonsung Kim, and Dohee Kim, KAIST; Hardik Sharma, Google; Jongse Park, KAIST

Cachew: Machine Learning Input Data Processing as a Service
Dan Graur, Damien Aymon, Dan Kluser, and Tanguy Albrici, ETH Zurich; Chandramohan A. Thekkath, Google; Ana Klimovic, ETH Zurich

Automatic Recovery of Fine-grained Compiler Artifacts at the Binary Level
Yufei Du, University of North Carolina at Chapel Hill; Ryan Court and Kevin Snow, Zeropoint Dynamics; Fabian Monrose, University of North Carolina at Chapel Hill

CRISP: Critical Path Analysis of Large-Scale Microservice Architectures
Zhizhou Zhang, UC Santa Barbara; Murali Krishna Ramanathan, Prithvi Raj, and Abhishek Parwal, Uber Technologies Inc.; Timothy Sherwood, UC Santa Barbara; Milind Chabbi, Uber Technologies Inc.

Co-opting Linux Processes for High-Performance Network Simulation
Rob Jansen, U.S. Naval Research Laboratory; Jim Newsome, Tor Project; Ryan Wails, Georgetown University, U.S. Naval Research Laboratory

Serving Heterogeneous Machine Learning Models on Multi-GPU Servers with Spatio-Temporal Sharing
Seungbeom Choi, Sunho Lee, Yeonjae Kim, Jongse Park, Youngjin Kwon, and Jaehyuk Huh, KAIST

IPLFS: Log-Structured File System without Garbage Collection
Juwon Kim, Minsu Jang, Muhammad Danish Tehseen, Joontaek Oh, and YouJip Won, KAIST

Speculative Recovery: Cheap, Highly Available Fault Tolerance with Disaggregated Storage
Nanqinqin Li, Anja Kalaba, Michael J. Freedman, Wyatt Lloyd, and Amit Levy, Princeton University

Vinter: Automatic Non-Volatile Memory Crash Consistency Testing for Full Systems
Samuel Kalbfleisch, Lukas Werling, and Frank Bellosa, Karlsruhe Institute of Technology

Whale: Efficient Giant Model Training over Heterogeneous GPUs
Xianyan Jia, Le Jiang, Ang Wang, and Wencong Xiao, Alibaba Group; Ziji Shi, National University of Singapore & Alibaba Group; Jie Zhang, Xinyuan Li, Langshi Chen, Yong Li, Zhen Zheng, Xiaoyong Liu, and Wei Lin, Alibaba Group

Faster Software Packet Processing on FPGA NICs with eBPF Program Warping
Marco Bonola, CNIT/Axbryd; Giacomo Belocchi, Angelo Tulumello, and Marco Spaziani Brunella, Axbryd/University of Rome "Tor Vergata"; Giuseppe Siracusano, NEC Laboratories Europe; Giuseppe Bianchi, University of Rome "Tor Vergata"/CNIT; Roberto Bifulco, NEC Laboratories Europe

Zero-Change Object Transmission for Distributed Big Data Analytics
Mingyu Wu, Shuaiwei Wang, Haibo Chen, and Binyu Zang, Shanghai Jiao Tong University

RRC: Responsive Replicated Containers
Diyu Zhou, UCLA and EPFL; Yuval Tamir, UCLA

JITServer: Disaggregated Caching JIT Compiler for the JVM in the Cloud
Alexey Khrabrov, University of Toronto; Marius Pirvu and Vijay Sundaresan, IBM; Eyal de Lara, Univerity of Toronto

Primo: Practical Learning-Augmented Systems with Interpretable Models
Qinghao Hu, Nanyang Technological University; Harsha Nori, Microsoft; Peng Sun, SenseTime; Yonggang Wen and Tianwei Zhang, Nanyang Technological University

Sift: Using Refinement-guided Automation to Verify Complex Distributed Systems
Haojun Ma, Hammad Ahmad, Aman Goel, Eli Goldweber, Jean-Baptiste Jeannin, Manos Kapritsos, and Baris Kasikci, University of Michigan

Memory Harvesting in Multi-GPU Systems with Hierarchical Unified Virtual Memory
Sangjin Choi and Taeksoo Kim, KAIST; Jinwoo Jeong, Ajou University; Rachata Ausavarungnirun, King Mongkut's University of Technology North Bangkok; Myeongjae Jeon, UNIST; Youngjin Kwon, KAIST; Jeongseob Ahn, Ajou University

PRIDWEN: Universally Hardening SGX Programs via Load-Time Synthesis
Fan Sang, Georgia Institute of Technology; Ming-Wei Shih, Microsoft; Sangho Lee, Microsoft Research; Xiaokuan Zhang, Georgia Institute of Technology; Michael Steiner, Intel; Mona Vij, Intel Labs; Taesoo Kim, Georgia Institute of Technology

Riker: Always-Correct and Fast Incremental Builds from Simple Specifications
Charlie Curtsinger, Grinnell College; Daniel W. Barowy, Williams College