A Dynamic Scheduling Strategy of ADMM Sub-problem Optimization Algorithm Based on Hierarchical Structure

The Alternating Direction Method of Multiplier (ADMM) is a simple algorithm to resolve decomposable convex optimization problems, especially effective in solving large-scale problems. However, this algorithm suffers from the straggler problem its updates

  • PDF / 54,094,295 Bytes
  • 757 Pages / 439.37 x 666.142 pts Page_size
  • 110 Downloads / 232 Views

DOWNLOAD

REPORT


Meikang Qiu (Ed.)

Algorithms and Architectures for Parallel Processing 20th International Conference, ICA3PP 2020 New York City, NY, USA, October 2–4, 2020 Proceedings, Part I

Lecture Notes in Computer Science Founding Editors Gerhard Goos Karlsruhe Institute of Technology, Karlsruhe, Germany Juris Hartmanis Cornell University, Ithaca, NY, USA

Editorial Board Members Elisa Bertino Purdue University, West Lafayette, IN, USA Wen Gao Peking University, Beijing, China Bernhard Steffen TU Dortmund University, Dortmund, Germany Gerhard Woeginger RWTH Aachen, Aachen, Germany Moti Yung Columbia University, New York, NY, USA

12452

More information about this series at http://www.springer.com/series/7407

Meikang Qiu (Ed.)

Algorithms and Architectures for Parallel Processing 20th International Conference, ICA3PP 2020 New York City, NY, USA, October 2–4, 2020 Proceedings, Part I

123

Editor Meikang Qiu Columbia University New York, NY, USA

ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Computer Science ISBN 978-3-030-60244-4 ISBN 978-3-030-60245-1 (eBook) https://doi.org/10.1007/978-3-030-60245-1 LNCS Sublibrary: SL1 – Theoretical Computer Science and General Issues © Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

This three-volume set contains the papers presented at the 20th International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP 2020), held during October 2–4, 2020, in New York, USA. There were 495 submissions. Each submission was reviewed by at least 3 reviewers, and on the average 3.5 Program Committee members. The committee decided to accept 147 papers. We will separate the proceeding into three v