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IPDPS 2024 Conference Posters

In the last stage of review of the paper submissions to the main conference, the program committee identified full paper submissions to be recommended for consideration as a short paper and designated here as Conference Poster-accept Papers.

The 24 conference posters listed below* will be presented by the authors during the Conference Poster Session to be held on Wednesday 29 May from 4:10 – 5:30 pm. The posters will also be available for viewing during the three days of the main conference, and 2-page short papers describing the work will be published as part of the IPDPSW volume of the proceedings.

They represent what may be considered preliminary works of interest to the community, and this will make their authors’ contributions available to IPDPS 2024 attendees.

  • A Deep Dive into Task-Based Parallelism in Python
    William Ruys, Hochan Lee, Bozhi You, Shreya Talati, Jaeyoung Park, James Almgren-Bell, Yineng Yan, Milinda Fernando, George Biros, Mattan Erez (The University of Texas at Austin); Martin Burtscher (Texas State University); Christopher Rossbach, Keshav Pingali, Milos Gligoric (The University of Texas at Austin)
  • A New Exact State Reconstruction Strategy for Conjugate Gradient Methods with Arbitrary Preconditioners
    Viktoria Mayer, Wilfried Gansterer (University of Vienna)
  • A Stochastic Composite Model to Understand the Impact of Rare, Colossal Interference in HPC Systems
    Muna Tageldin, Majeed Hayat (Marquette University); Jered Dominguez-Trujillo (Los Alamos National Laboratory); Patrick Bridges (University of New Mexico)
  • Accelerating Native Transaction Processing in LSM-Based Persistent Key-Value Stores
    Jin Xue, Zili Shao (The Chinese University of Hong Kong)
  • AdCoalescer: An Adaptive Coalescer to Reduce the Inter-Module Traffic in MCM-GPUs
    Xu Zhang, Guangda Zhang , Lu Wang, Xia Zhao (Academy of Military Sciences, Beijing)
  • An SR-IOV SSD Optimized for QoS-Sensitive IaaS Cloud Storage
    Xiang Chen (DapuStor); Ru Ying, Haocong Ma, Yao Wang, Xianjun Meng, Guangjun Xie (Baidu (China) Co., Ltd); Yonghui Zhan, Fenyong Yuan, Ying Yang, Tao Lu, Jinqiang Wang, Yunxin Huang, Yafei Yang (DapuStor); You Zhou, Fei Wu (Huazhong University of Science and Technology)
  • Asynchrony and Failure Masking via Pseudo-Local Process Recovery in MPI Applications
    Matthew Whitlock, Hemanth Kolla (Sandia National Laboratories); Aurelien Bouteiller (University of Tennessee Knoxville); Jackson Mayo, Nicolas Morales, Keita Teranishi (Sandia National Laboratories); George Bosilca (University of Tennessee Knoxville)
  • EDDIS: Accelerating Distributed Data-Parallel DNN Training for Heterogeneous GPU Cluster
    Shinyoung Ahn, Hooyoung Ahn (ETRI); Hyeonseong Choi (DeepInspection); Jaehyun Lee (VAIV Company Inc.)
  • Efficient Multi-Processor Scheduling in Increasingly Realistic Models
    Pal Andras Papp, Georg Anegg, Aikaterini Karanasiou, Albert-Jan N. Yzelman (Huawei Zurich Research Center)
  • Energy-Aware Decentralized Learning with Intermittent Model Training
    Martijn de Vos, Akash Dhasade (École polytechnique fédérale de Lausanne); Paolo Dini (Centre Tecnològic de Telecomunicacions de Catalunya); Elia Guerra (Independent researcher); Anne-Marie Kermarrec (École polytechnique fédérale de Lausanne); Marco Miozzo (Centre Tecnològic de Telecomunicacions de Catalunya); Rafael Pires, Rishi Sharma (École polytechnique fédérale de Lausanne)
  • Enhancing Energy Efficiency with Multi-Site Scheduling Strategies
    Alok Kamatar, Valerie Hayot-Sasson, Yadu Babuji, Andre Bauer (University of Chicago); Gourav Rattihalli, Ninad Hogade, Dejan Milojicic (HPE); Kyle Chard, Ian Foster (University of Chicago)
  • Evaluation of Programming Models and Performance for Stencil Computation on GPGPUs
    Baodi Shan, Mauricio Araya-Polo (Total Energies EP Research and Technology USA, LLC)
  • Exploiting Tensor Cores in Sparse Matrix-Multivector Multiplication via Block-Sparsity-Aware Clustering
    Eunji Lee, Yoonsang Han, Gordon Euhyun Moon (Sogang University)
  • FedClust: Optimizing Federated Learning on Non-IID Data through Weight-Driven Client Clustering
    Md Sirajul Islam, Simin Javaherian (University of Louisiana at Lafayette); Fei Xu (East China Normal University); Xu Yuan, Li Chen, Nian-feng Tzeng (University of Louisiana at Lafayette)
  • FedSZ: Leveraging Error-Bounded Lossy Compression for Federated Learning Communications
    Grant Wilkins (Argonne National Laboratory and University of Cambridge); Sheng Di (Argonne National Laboratory); Jon Calhoun (Clemson University); Zilinghan Li (University of Cambridge); Kibaek Kim, Robert Underwood (Argonne National Laboratory); Richard Mortier (University of Cambridge); Franck Cappello (Argonne National Laboratory)
  • Integration Framework for Online Thread Throttling with Thread and Page Mapping on NUMA Systems
    Janaina Schwarzrock (Universidade Federal do Rio Grande do Sul and Universidade Federal do Rio Grande do Norte); Arthur F. Lorenzon (Universidade Federal do Rio Grande do Sul); Samuel Xavier de Souza (Universidade Federal do Rio Grande do Norte); Antonio Carlos S. Beck (Universidade Federal do Rio Grande do Sul)
  • MDLoader: A Hybrid Model-driven Data Loader for Distributed Deep Neural Networks Training
    Jonghyun Bae (Lawrence Berkeley National Laboratory); Jong Youl Choi, Massimiliano Lupo Pasini, Kshitij Mehta (Oak Ridge National Laboratory); Khaled Ibrahim (Lawrence Berkeley National Laboratory)
  • Proactive, Accuracy-aware Straggler Mitigation in Machine Learning Clusters
    Suraiya Tairin, Haiying Shen (University of Virginia); Anand Iyer (Georgia Institute of Technology)
  • Scalable Node Embedding Algorithms using Distributed Sparse Matrix Operations
    Isuru Ranawaka, Ariful Azad (Indiana University)
  • Scheduling and Allocation of Disaggregated Memory Resources in HPC Systems
    Jie Li (Texas Tech University); George Michelogiannakis, Brandon Cook, John Shalf (Berkeley Lab); Yong Chen (Texas Tech University);
  • Shared-Memory Parallel Dynamic Louvain Algorithm for Community Detection
    Subhajit Sahu, Kishore Kothapalli (International Institute of Information Technology Hyderabad, India); Dip Sankar Banerjee (Indian Institute of Technology Jodhpur, India)
  • System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models
    Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Reza Yazdani Aminabadi,  Shuwaen leon Song, Samyam Rajbhandari, Yuxiong He  (Microsoft Inc)
  • Toward Self-Adjusting k-ary Search Tree Networks
    Evgeniy Feder (ITMO University); Anton Paramonov (EPFL); Pavel Mavrin (Neapolis University Pafos); Iosif Salem, Stefan Schmid (TU Berlin); Vitaly Aksenov (City, University of London)
  • Understanding and Adapting to Multi-transport protocols in Datacenter Networks
    Dinghuang Hu, Dezun Dong (National University of Defense Technology, Changsha)

*Updated Posting 15 May 2024
Authors who have corrections should send email to giving full details.

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IPDPS 2023 Report

37th IEEE International Parallel
& Distributed Processing Symposium
May 15-19, 2023

Hilton St. Petersburg
Bayfront Hotel
St. Petersburg, Florida USA