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Workshop Support



IPDPS 2023 Call for Papers

37th IEEE International Parallel &
Distributed Processing Symposium


  • Authors must register their paper and submit an abstract by Thursday, September 29, 2022.
  • Authors must then submit full versions of registered papers by Thursday, October 6, 2022.
  • All deadlines are end of day ANYWHERE ON EARTH.
  • Before submitting, review the information under WHAT/WHERE TO SUBMIT below.

Authors are invited to submit manuscripts that present novel and impactful research in all areas of parallel and distributed processing. Works focusing on emerging technologies, interdisciplinary work spanning multiple IPDPS focus areas, and novel open-source artifacts are especially welcome. Topics of interest include but are not limited to the following topic areas:

Parallel and Distributed Algorithms for Computational Science: This track focuses on parallel and distributed (to include cloud, edge, and fog computing) algorithms arising in the context of execution of computational science methods. Examples of computations forming these workloads include structured and unstructured grids, dense and sparse linear algebra computations, spectral methods, and n-body computations. Also included in this track are algorithmic and theory contributions that are workload agnostic but specific to tightly coupled systems, such as those supporting communication, synchronization, and power management.

Parallel and Distributed Algorithms for Data Science: This track focuses on parallel and distributed (to include cloud, edge, and fog computing) algorithms arising in the context of execution of data science methods, including machine learning, data mining, graph computations, clustering, visualization, and other forms of data analytic methods. Also included in this track are algorithmic and theory contributions that are workload agnostic but specific to loosely coupled systems, such as those for management of distributed resources, and those related to distributed data and transactions as well as mobility.

Experiments: This track focuses on experiments and practice in parallel and distributed computing. Topics can include: design and experimental evaluation of applications of parallel and distributed computing in simulation and analysis; experiments on the use of novel commercial or research architectures, accelerators, quantum and neuromorphic architectures, and other non-traditional systems; performance modeling and analysis of parallel and distributed systems; innovations made in support of large-scale infrastructures and facilities; and methods for and experiences allocating and managing system and facility resources.

Programming Models, Compilers, and Runtime Systems: This track ranges from the design of programming models and paradigms to language and compilers supporting these models and paradigms, to runtime and middleware solutions. Software that is close to the application (as opposed to the bare hardware) but not specific to an application is included – examples includes frameworks targeting cloud and distributed systems; application frameworks for fault tolerance and resilience; software supporting data management, scalable data analytics and similar workloads, and runtime systems for future novel computing platforms including quantum, neuromorphic, and bio-inspired computing.

System Software: This track focuses on software that is close to the bare hardware. Topics include storage and I/O systems; system software for resource management, job scheduling, and energy-efficiency; system software support for accelerators and heterogeneous HPC computing systems; interactions between the OS and the hardware with other software layers; system software support for fault tolerance and resilience; containers and virtual machines; specialized operating systems and related support for high performance computing; and system software for future novel computing platforms including quantum, neuromorphic, and bio-inspired computing.

Architecture: This topics focuses on studies related to both existing and emerging architectures, including architectures for instruction-level and thread-level parallelism; manycore, multicores, accelerators, domain-specific and special-purpose architectures, reconfigurable architectures; memory technologies and hierarchies; volatile and non-volatile emerging memory technologies, solid-state devices; exascale system designs; data center and warehouse-scale architectures; novel big data architectures; network and interconnect architectures; emerging technologies for interconnects; parallel I/O and storage systems; power-efficient and green computing systems; resilience, security, and dependable architectures; performance modeling and evaluation; emerging trends for computing, machine learning, approximate computing, quantum computing, neuromorphic, analog, and bio-inspired computing.

Multidisciplinary: The focus of this track is on papers that cross the boundaries of the tracks listed above and/or address the application of parallel and distributed computing concepts and solutions to other areas of science and engineering. Contributions should either target two or more core areas of parallel and distributed computing or advance the use of parallel and distributed computing in other areas of science and engineering (to include translational research).

Best Paper Award

The program committee will select a small set of top-quality papers as best paper finalists, and one paper as the winner, for recognition with the Best Paper Award.

Best Open-Source Contribution Award

This year, the IPDPS technical program committee particularly welcomes submissions with open-source tool and dataset artifacts, relevant to the parallel and distributed computing community, as one of their technical contributions. The authors of accepted papers will be encouraged to identify if they wish their submissions to be considered for the best open-source contribution award. Such papers will be evaluated by a dedicated open-source tool and dataset artifacts committee. A small set of such papers will be identified as the best open-source contribution paper finalists as appropriate and applicable based on the quality of the contribution. One paper may be selected as the winner among the finalists, for recognition with the Best Open-Source Contribution Award, depending upon the contribution level and the recommendation from the committee. The two award categories are not exclusive (a paper can be nominated for both the best paper award and best open-source contribution award).


Abstracts of at most 500 words must be submitted by September 29, 2022. Manuscripts must be submitted by October 6, 2022; submitted manuscripts may not exceed ten (10) single-spaced double-column pages using 10-point size font on 8.5x11 inch pages (IEEE conference style), including figures, tables, and references. The submitted manuscripts should not include author names and affiliations, as a double-blind review process will be followed.

The IEEE conference style templates for MS Word and LaTeX provided by IEEE eXpress Conference Publishing are available for download. See the latest versions here.

Files should be submitted by following the instructions at the IPDPS 2023 Submission Site (powered by Linklings). Click here to submit abstract and register your paper by September 29th.


All submitted manuscripts will be reviewed by the Program Committee under a double-blind review process. Submissions will be judged on correctness, originality, technical strength, significance, potential impact, quality of presentation, and interest and relevance to the conference scope. Submitted manuscripts should NOT have appeared in or be under consideration for another conference, workshop, or journal.

A high-quality submission should articulate its contributions in multiple aspects:

  • Motivation. Clearly state the objective of the paper and provide strong support to motivate the specific problem the submission is solving.
  • Limitations of state-of-art approaches. Unambiguously discuss and distinguish from the most relevant and most recent prior works.
  • Key insights and contributions. Clearly articulate the major insights that enable the described approach or make it effective. Clearly specify the novelty of these insights and how they advance state-of-the-art. Provide a list of key contributions including flagship theoretical or experimental results and improvement over the prior art, as applicable.
  • Methodology. Clearly specify the key theoretical or experimental methodological details, as applicable. Support the chosen methodological choices (e.g., cite that most relevant and most recent prior works have evaluated their ideas using similar methodology). If new methodology is adopted or theoretical assumptions different from prior art are made, a detailed justification should be provided.
  • Limitations of the proposed approach. As applicable, articulate all the major limitations of the proposed approach and identify conclusions that are sensitive to specific assumptions made in the paper.

The Program Committee will be encouraged to assess the submissions in the above aspects. Therefore, the authors should consider making these aspects clear and easily identifiable, as much as possible, when articulating their contributions. We hope this will help improve both the review-quality (author experience) and reviewing-experience.

Authors will have the opportunity to respond to the reviewers’ questions and provide clarifications before the first-round decisions are made. Note that not all submissions may be invited to submit response/rebuttal. The submissions which are not invited to submit response/rebuttal will be notified with an early-reject decision by December 1, 2022.

Questions may be sent to Abstracts are due September 29, 2022, and full manuscripts must be received by October 6, 2022. This is a final, hard deadline. To ensure fairness, no extensions will be given.

Preliminary decisions will be sent by December 19, 2022, with a decision of either “accept”, “revise”, or “reject”. Authors of papers in the “revise” decision will have the opportunity to submit a new version addressing reviewers’ comments. Such a revised submission will be due on January 19, 2023 and will need to include a cover letter explaining the changes.

The ensuing review process for such submission will result in decisions of either “accept” or “reject”, the latter for the cases where the reviewers assess that the issues they raised were not satisfactorily and sufficiently addressed. Notification of final decisions will be mailed by January 31, 2023, and camera-ready papers will be due February 23, 2023.

ArXiv Submission Policy

Having an arXiv paper does not prohibit authors from submitting a paper to IPDPS 2023. arXiv papers are not peer-reviewed and not considered as formal publications, hence do not count as prior work. Authors are not expected to compare against arXiv papers that have not formally appeared in previous conference or journal proceedings. If a submitted paper is already on arXiv, please continue to follow the double-blind submission guidelines. Authors are encouraged to use preventive measures to reduce the chances of accidental breach of anonymity (e.g., use a different title in the submission, not upload/revise the arXiv version during the review period after the submission deadline).

Inclusive Description of Research Contributions

Please consider making your research contribution description inclusive in nature. For example, consider using gender-neutral pronouns, consider using examples that are ethnicity/culture-rich, consider engaging users from diverse backgrounds if your research involves a survey, etc. Best efforts should be made to make the paper accessible to visually impaired or color-blind readers.


  • Abstract submissions
    Thursday, September 29, 2022
  • Full manuscript submissions (double-blind)
    Thursday, October 6, 2022 - FIRM DEADLINE
  • Author response/rebuttal to reviews
    Thu, 1 Dec - Mon, 5 Dec 2022
  • 1st round decisions
    Monday, 19 December 2022
  • Revised submissions due
    Thursday, 19 January 2023
  • Final decisions
    Tuesday, 31 January 2023


Gagan Agrawal, Augusta University, USA
Devesh Tiwari, Northeastern University, USA


Parallel and Distributed Algorithms for Computational Science:
Anne Benoit (ENS Lyon, France)
Erik Saule (Univ of North Carolina, Charlotte, USA)

Parallel and Distributed Algorithms for Data Science:
Tekin Bicer (Argonne National Lab, USA)
Konstantin (Costas) Busch (Augusta University, USA)

Ann Gentile (Sandia National Lab, USA)
Ignacio Laguna (Lawrence Livermore National Lab, USA)

Programming Models, Compilers, and Runtime Systems:
Bin Ren (College of William & Mary, USA)
P. (Saday) Sadayappan (University of Utah, USA)

System Software:
Xubin He (Temple University, USA)
Jon Weissman (University of Minnesota, USA)

Michela Becchi (North Carolina State University, USA)
Osman Unsal (Barcelona Supercomputing Center, Spain)

Amanda Randles (Duke University, USA)
Valerie Taylor (Argonne National Lab, USA)


(Updated 27 Oct 2022*)

Parallel and Distributed Algorithms for Computational Science
Seher Acer (Google, USA)
Metin Aktulga (Michigan State University, USA)
Grey Ballard (Wake Forest University, USA)
Olivier Beaumont (Inria, University of Bordeaux, France)
Michael Bender (Stony Brook University, New York, USA)
Raphael Bleuse (University of Luxembourg, Luxembourg)
Quan Chen (Shanghai Jiao Tong University, Alibaba Cloud, China)
Jee Choi (University of Oregon, USA)
Daniel Cordeiro (University of São Paulo, Brazil)
Georges Da Costa (IRIT - Universite Paul Sabatier Toulouse III/ University of Toulouse, France)
Anthony Danalis (The University of Tennessee, Knozville, USA)
Karen Devine (Sandia National Laboratories, USA)
Lionel Eyraud-Dubois (Inria, University of Bordeaux, France)
Martin Farach-Colton (Rutgers University, USA)
Pieter Ghysels (Berkeley Lab, USA)
Alfredo Goldman (University of São Paulo, Brazil)
Thomas Herault (University of Tennessee, USA)
Sascha Hunold (Vienna University of Technologia, Austria)
George Karypis (University of Minnesota, USA)
Kamer Kaya (Sabanci University, Turkey)
Vitus J. Leung (Sandia National Laboratories, USA)
Mingmin Li (City University of Hong Kong, China)
Weifeng Liu (China University of Petroleum, Beijing, China)
Hatem Ltaief (King Abdullah University of Science and Technology, Saudi Arabia)
Fredrik Manne (University of Bergen, Norway)
Tim Mattson (Intel, USA)
Alba Melo (University of Brasilia, Brazil)
Kengo Nakajima (University of Tokyo, RIKEN, Japan)
Cynthia Phillips (Sandia National Laboratories, USA)
Loic Pottier (University of Southern California, USA)
Veronika Rehn-Sonigo (University of Bourgogne Franche-Comte, FEMTO-ST institute, France)
Krzysztof Rzadca (University of Warsaw, Google, Polan)
Peter Sanders (Karlsruhe Institute of Technology, Germany)
Olaf Schenk (University of Lugano, Switzerland)
Oded Schwartz (Hebrew University of Jerusalem, Israel)
Oliver Sinnen (University of Auckland, New Zealand)
Edgar Solomonik (University of Illinois, USA)
Hongyang Sun (The University of Kansas, USA)
Hari Sundar (The University of Utah, USA)
Bora Ucar (CNRS and LIP, ENS Lyon, France)
Frederic Vivien (Inria and LIP, ENS Lyon, France)

Parallel and Distributed Algorithms for Data Science:
James Aspnes (Yale University, USA)
Ariful Azad (Indiana University, USA)
Prasanna Balaprakash (Argonne National Laboratory, USA)
Dip Sankar Banerjee (Indian Institute of Technology Jodhpur, India)
George Biros (University of Texas and Oden Institute, USA)
Rezaul Chowdhury (Stony Brook University, USA)
Guojing Cong (Oak Ridge National Laboratory, USA)
Gianluca De Marco (University of Salerno, Italy)
Funda Ergun (Indiana University, USA)
Antonio Fernandez Anta (IMDEA Networks Institute, Spain)
Pierre Fraigniaud (CNRS, Université de Paris, France)
Ana Gainaru (Oak Ridge National Laboratory, USA)
Pawel Garncarek (Augusta University, USA)
Leszek Gąsieniec (University of Liverpool, United Kingdom)
Chryssis Georgiou (University of Cyprus, Cyprus)
Wojciech Golab (University of Waterloo, Canada)
Oded Green (NVIDIA and Georgia Institute of Technology, USA)
John A. Gunnels (NVIDIA, USA)
Mahantesh Halappanavar (Pacific Northwest National Laboratory, USA)
Ali Jannesari (Iowa State University, USA)
Klaus Jansen (University of Kiel, Germany)
Christos Kaklamanis (University of Patras, Greece)
Oguz Kaya (Université Paris-Saclay, France)
Udayan Khurana (IBM Research, USA)
Mariam Kiran (Lawrence Berkeley National Laboratory, USA)
Penporn Koanantakool (Google, USA)
Dariusz R. Kowalski (Augusta University, USA)
Sanmukh Kuppannagari (Case Western Reserve University, USA)
Dong Li (University of California Merced, USA)
Wei-keng Liao (Northwestern University, USA)
Zhengchun Liu (Argonne National Laboratory and University of Chicago, USA)
Marios Mavronicolas (University of Cyprus, Cyprus)
Friedhelm Meyer auf der Heide (Paderborn University, Germany)
Henning Meyerhenke (Humboldt University of Berlin, Germany)
Roberto Palmieri (Lehigh University, USA)
Gopal Pandurangan (University of Houston, USA)
Miroslav Popovic (University of Novi Sad, Serbia and Montenegro)
Pavan Poudel (ATGWORK, USA)
Radu Prodan (University of Klagenfurt, Austria)
Peter Robinson (Augusta University, USA)
Yogish Sabharwal (IBM India Research Lab, India)
Piyush Sao (Oak Ridge National Laboratory and Georgia Institute of Technology, USA)
Gokarna Sharma (Kent State University, USA)
Michael Spear (Lehigh University, USA)
Srikanta Tirthapura (Apple, USA)
Lewis Tseng (Boston College, USA)
Ramachandran Vaidyanathan (Louisiana State University, USA)
Abhinav Vishnu (AMD, USA)
Rio Yokota (Tokyo Institute of Technology, Japan)
Shinjae Yoo (Brookhaven National Laboratory, USA)
Yang You (National University of Singapore, Singapore)
Maxwell Young (Mississippi State University, USA)
Qin Zhang (Indiana University Bloomington, USA)

David Abramson (University of Queensland, Australia)
Hartwig Anzt (Karlsruhe Institute of Technology; University of Tennessee, Knoxville, )
Abhinav Bhatele (University of Maryland, College Park., USA)
Amanda J. Bienz (University of New Mexico, USA)
Jim Brandt (Sandia National Laboratories, USA)
Philip Carns (Argonne National Laboratory (ANL), USA)
Marc Casas Guix (Barcelona Supercomputing Center (BSC), Polytechnic University of Catalonia, Spain)
Zhongliang Chen (AMD, USA)
Florina M. Ciorba (University of Basel, Switzerland)
Jonathan Cook (New Mexico State University, USA)
Ryusuke Egawa (Tokyo Denki University, Tohoku University, Japan)
Basilio B. Fraguela (Universidade Da Coruña, Spain)
Richard Gerber (Lawrence Berkeley National Laboratory, USA)
Kevin Huck (University of Oregon, USA)
Nikhil Jain (NVIDIA Corporation, USA)
Saurabh Jha (IBM, USA)
Karen L. Karavanic (Portland State University, USA)
Naoya Maruyama (NVIDIA Corporation, USA)
Verónica G. Melesse Vergara (Oak Ridge National Laboratory (ORNL), USA)
Diana Moise (Hewlett Packard Enterprise (HPE), USA)
Hai Ah Nam (Lawrence Berkeley National Laboratory (LBNL), USA)
Konstantinos Parasyris (Lawrence Livermore National Laboratory, USA)
Tapasya Patki (Lawrence Livermore National Laboratory, USA)
Olga Pearce (Lawrence Livermore National Laboratory, Texas A&M University, USA)
Srinivasan Ramesh (NVIDIA Corporation, USA)
Kento Sato (RIKEN, Japan)
Galen Shipman (Los Alamos National Laboratory, USA)
Didem  Unat (Koç University, Istanbul, Turkey)
Craig Vineyard (Sandia National Laboratories, USA)
Richard Vuduc (Georgia Institute of Technology, USA)
Mohamed Wahib (RIKEN Center for Computational Science; AIST , Japan)
Michele Weiland (University of Edinburgh, Scotland)
Andrew Younge (Sandia National Laboratories, USA)

Programming Models, Compilers, and Runtime Systems:
Riyadh Baghdadi (New York University Abu Dhabi, UAE)
Wenlei Bao (Apple, USA)
Swarnendu Biswas (Indian Institute of Technology Kanpur, India)
George Bosilca (University of Tennessee Knowville, USA)
Franck Cappello (Argonne National Laboratory, USA)
Bradford Chamberlain (Hewlett Packard Enterprise/University of Washington, USA)
Yue Cheng (University of Virginia, USA)
Albert Cohen (Google, France)
Roshan Dathathri (Katana Graph, USA)
Michael Garland (NVIDIA Research, USA)
Ganesh Gopalakrishnan (University of Utah, USA)
Hui Guan (University of Massachusetts Amherst, USA)
Mary Hall (University of Utah, USA)
Mert Hidayetoğlu (University of Illinois at Urbana-Champaign, USA)
Gokcen Kestor (Pacific Northwest National Laboratory, USA)
Fredrik Kjolstad (Stanford University, USA)
Martin Kong (Ohio State University, USA)
I-Ting Angelina Lee (Washington University in St. Louis, USA)
Jaejin Lee (Seoul National University, South Korea)
Ang Li (Pacific Northwest National Laboratory, USA)
Jiajia Li (North Carolina State University, USA)
Jonathan Lifflander (Sandia National Laboratories, USA)
Tongping Liu (University of Massachusetts Amherst, USA)
Xu Liu (North Carolina State University, USA)
Hui Lu (SUNY Binghamton, USA)
Wenjing Ma (Institute of Software/Chinese Academy of Sciences, China)
Frank Mueller (North Carolina State University, USA)
Stefan Muller (Illinois Institute of Technology, USA)
Dimitrios Nikolopoulos (Virginia Tech, USA)
John Owens (University of California Davis, USA)
Prashant Pandey (University of Utah, USA)
Ivy Peng (Lawrence Livermore National Laboratory, USA)
Sivasankaran Rajamanickam (Sandia National Laboratories, USA)
Fabrice Rastello (Inria Grenoble, France)
Jie Ren (College of William & Mary, USA)
Probir Roy (University of Michigan-Dearborn, USA)
Bo Sang (Ant Group, USA)
Aamir Shafi (Ohio State University, USA)
Pengfei Su (University of California Merced, USA)
Hari Subramoni (Ohio State University, USA)
Aravind Sukumaran-Rajam (Meta Platforms, USA)
Zehra Sura (Bloomberg, USA)
Douglas Thain (University of Notre Dame, USA)
Zheng Wang (University of Leeds, UK)
Bing Xie (Oak Ridge National Laboratory, USA)
Jingling Xue (UNSW Sydney, Australia)
Rohit Zambre (NVIDIA, USA)
Minjia Zhang (Microsoft Research, USA)
Xuechen Zhang (Washington State University, USA)
Yunming Zhang (Google, USA)
Zheng Zhang (Rutgers University, USA)
Zhijia Zhao (University of California Riverside, USA)

System Software:
Ali Anwar (University of Minnesota, USA)
Ron Brightwell (Sandia National Laboratories, USA)
Suren Byna (Lawrence Berkeley National Laboratory (LBNL), USA)
Henri Casanova (University of Hawaii at Manoa, USA)
Yong Chen (Texas Tech University, USA)
Chao Chen (Amazon Science, USA)
Terry Cojean (Karlsruhe Institute of Technology, Germany)
James Dinan (NVIDIA Corporation, USA)
Jens Domke (RIKEN Center for Computational Science, Japan)
Christian Engelmann (Oak Ridge National Laboratory (ORNL), USA)
Trilce Estrada (University of New Mexico, USA)
Mathieu Faverge (Bordeaux INP, French Institute for Research in Computer Science and Automation (INRIA) France
Christian Fensch (ARM Norway, Norway)
Kurt Ferreira (Sandia National Laboratories, USA)
Song Fu (University of North Texas, USA)
Thierry Gautier (INRIA, ENS-Lyon, France)
Qian Gong (Oak Ridge National Laboratory (ORNL), USA)
Madhusudhan Govindaraju (SUNY Binghamton, USA)
Sumanth Gudaparthi (AMD Research, USA)
Abdou Guermouche (University of Bordeaux (IMB), French Institute for Research in Computer Science and Automation (INRIA), France)
Kyle Hale (Illinois Institute of Technology, USA)
Yu Hua (Huazhong University of Science and Technology, China)
Shadi Ibrahim (French Institute for Research in Computer Science and Automation (INRIA), France)
Kamil Iskra (Argonne National Laboratory (ANL), USA)
Youngjae Kim (Sogang University, South Korea, South Korea)
Volodymyr Kindratenko (University of Illinois, Nat. Center for Supercomputing Applications (NCSA), USA)      
Scott Klasky (Oak Ridge National Laboratory (ORNL), USA)
Zhiling Lan (Illinois Institute of Technology, USA)
Michael Lang (Los Alamos National Laboratory, USA)
Alexander Margolin (Hebrew University of Jerusalem, Israel)
Esteban Meneses (Costa Rica Institute of Technology, Costa Rica National High Technology Center, Costa Rica)
Ningfang Mi (Northeastern University, USA)
Sarah M. Neuwirth (Goethe University Frankfurt, Jülich Supercomputing Centre, Germany)
Bogdan Nicolae (Argonne National Laboratory (ANL), USA)
Guillaume Pallez (National Institute for Research in Computer Science and Automation (Inria); University of Bordeaux, France)
Sangmi Pallickara (Colorado State University, USA)
Dhabaleswar K. (DK) Panda (Ohio State University, USA)
Yu Pei (University of Tennessee, USA)
Ioan Raicu (Illinois Institute of Technology, Argonne National Laboratory (ANL), USA)
Thomas Ropars (Grenoble Alpes University, France)
Dario Suarez-Gracia (University of Zaragoza, Spain, Spain)
Nathan Tallent (Pacific Northwest National Laboratory (PNNL), USA)
Alexandru Uta (Leiden University, Amazon AWS, Netherlands)
Sathish Vadhiyar (IISC Bangalore, India)
Ana Lucia Varbanescu (University of Twente, University of Amsterdam, Netherlands)
Vanamala Venkataswamy (University of Virginia, USA)
En Wang (Jilin University, China)
Justin Wozniak (Argonne National Laboratory; University of Chicago, USA)
Shu Yin (Shanghai Tech University, State Key Lab of High Performance Computing, China)
Qing Zheng (Los Alamos National Laboratory, New Mexico Consortium, USA)
Mai Zheng (Iowa State University, USA)

Mohammad Alian (University of Kansas, USA)
Amro Awad (NCSU, USA)
Jason Bakos (University of South Carolina, USA)
Suren Byna (Lawrence Berkeley National Laboratory (LBNL), USA)
Simone Campanoni (Northwestern University, USA)
Roger D. Chamberlain (Washington University, USA)
Adrian Cristal (Barcelona Supercomputing Center, Spain)
Pascal Felber (University of Neuchatel, Switzerland)
Rong Ge (Clemson University, USA)
Roberto Gioiosa (Pacific Northwest National Laboratory (PNNL), USA)
Dimitris Gizopoulos (National and Kapodistrian University of Athens, Greece)
Hyeran Jeon (University of California, Merced, USA)
Arpit Joshi (Intel, USA)
Ulya Karpuzcu (University of Minnesota, USA)
Youngsok Kim (Yonsei University, South Korea)
Gwangsun Kim (POSTECH, Korea)
Robin Knauerhase (AMD Research, USA)
Pradeep Kumar (William & Mary, USA)
Seyong Lee (Oak Ridge National Laboratory (ORNL), USA)
Mikel Lujan (University of Manchester, United Kingdom)
Hiroki Matsutani (Keio University, Japan)
George Michelogiannakis (Lawrence Berkeley National Laboratory (LBNL), Stanford University, USA)
Onur Mutlu (ETH Zürich, Switzerland)
Hiroki Nakahara (Tokyo Institute of Technology, Japan)
Umit Ogras (University of Wisconsin-Madison, USA)
Ozcan Ozturk (Bilkent University, Turkey, Turkey)
Elaheh Sadredini (University of California, Riverside, USA)
Yukinori Sato (Toyohashi University of Technology, Japan)
Ioannis Sourdis (Chalmers University of Technology, Sweden)
Antonino Tumeo (Pacific Northwest National Laboratory (PNNL), USA)
Carlos Villavieja (Google, USA)
Rujia Wang (Illinois Institute of Technology, USA)
Bo Wu (Colorado School of Mines, USA)
Gulay Yalcin (Abdullah Gul University, Turkey)
Hao Zheng (University of Central Florida, USA)

Singharoy Abhishek (USA)
Mark Adams (Lawrence Berkeley National Laboratory (LBNL), USA)
Sanjukta Bhowmick (University of North Texas, USA
Kevin A. Brown (Argonne National Laboratory (ANL), USA)
Ali R. Butt (Virginia Tech, USA)
Silvina Caino-Lores (University of Tennessee, USA)
Jon Calhoun (Clemson University, USA)
Kirk Cameron (Virginia Tech, USA)
Kyle Chard (University of Chicago, Argonne National Laboratory (ANL), USA)
Zizhong Chen (University of California, Riverside, USA)
Jee Choi (University of Oregon, USA)
Vincenzo De Maio (Vienna University of Technology, Austria) 
Lucia Drummond (Fluminense Federal University, Brazil) 
Thomas Dufaud (University of Versailles, France) 
Lin Gan (Tsinghua University, China; National Supercomputing Center in Wuxi, China)
Sayan Ghosh (Pacific Northwest National Laboratory (PNNL), USA) 
Alex Gittens (Rensselaer Polytechnic Institute (RPI), USA)
Ganesh Gopalakrishnan (University of Utah, USA)
Hanqi Guo (The Ohio State University, USA)
Martin C. Herbordt (Boston University, USA)
Judith C. Hill (Lawrence Livermore National Laboratory, USA)
Peng Jiang (University of Iowa, USA)
Ananth Kalyanaraman (Washington State University, USA)
Masaaki Kondo (Keio University, Tokyo; RIKEN, USA)
Yang Liu (Lawrence Berkeley National Laboratory (LBNL), USA)
Ulrike Meier Yang (Lawrence Livermore National Laboratory, USA)
Bronson Messer (Oak Ridge National Laboratory (ORNL); University of Tennessee, USA)
Josh Milthorpe (Oak Ridge National Laboratory (ORNL); Australian National University, USA)
Diana Moise (Hewlett Packard Enterprise (HPE), Switzerland)
Jesmin Jahan Tithi (Intel Corporation, USA)
Weile Wei (Louisiana State University, LSU, USA)
Huiyang Zhou (North Carolina State University, USA)  
Yuhao Zhu (University of Rochester, USA)
Jaroslaw Zola (University at Buffalo, USA)

PC Chairs Team:
Abdullak Al-Mamun (University of Nevada Reno / Augusta University, USA)
Rohan Basu Roy (Northeastern University, USA)
Mehmet Belviranli (Colorado School of Mines, USA)
Dong Dai (UNC Charlotte, USA)
Giulia Guidi (Cornell University, USA)
Peng Jiang (University of Iowa , USA)
Raghavendra Kanakagiri (UIUC, USA)
Sidharth Kumar (University of Alabama, USA)
Guanpeng Li (University of Iowa, USA)
Hang Liu (Stevens Institute of Technology, USA)
Sreepathi Pai (University of Rochester, USA)
Tirthak Patel (Northeastern/ Rice University, USA)
Dingwen Tao (Indiana University, USA)
Haoyuan Xing (Google, USA)
Lishan Yang (George Mason University, USA)

(*Requests for corrections or changes should be sent to

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IPDPS 2022 Report

36th IEEE International Parallel & Distributed Processing Symposium
May 30 – June 3, 2022
(Lyon, France)