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37th IEEE International Parallel & Distributed Processing Symposium

37th IEEE International Parallel & Distributed Processing Symposium

St. Petersburg , United States

Submission Deadline: Thursday 29 Sep 2022

Conference Dates: May 15, 2023 - May 19, 2023

Research
Impact Score 4.50

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Ranking & Metrics Impact Score is a novel metric devised to rank conferences based on the number of contributing the best scientists in addition to the h-index estimated from the scientific papers published by the best scientists. See more details on our methodology page.

Research Impact Score: 4.50
Contributing Best Scientists: 175
H5-index:
Papers published by Best Scientists 253
Research Ranking (Computer Science) 102

Conference Call for Papers

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).

Overview

Top Research Topics at International Parallel and Distributed Processing Symposium?

  • Distributed computing (32.00%)
  • Parallel computing (30.87%)
  • Computer network (13.13%)

The main points discussed in the conference deals with Distributed computing, Parallel computing, Computer network, Scalability and Scheduling (computing). The works on Distributed computing deal in particular with Message passing. Topics like Parallel algorithm, Speedup, Concurrent computing, Parallel processing (DSP implementation) and Multi-core processor are tackled as part of the discussions on Parallel computing.

While it focused on Parallel algorithm, it was also able to explore topics like Algorithm design and Theoretical computer science. Network topology, Server, Network packet, Quality of service and Routing protocol are among the concentrations of Computer network that garnered much attention in it. The work tackled in International Parallel and Distributed Processing Symposium goes beyond the discipline of Scheduling (computing) as it also encompasses Schedule.

More specifically, the research on Dynamic priority scheduling in it is related to Rate-monotonic scheduling. The majority of Fair-share scheduling studies in it are focused on the subject of Two-level scheduling. The Grid computing study which was featured in the conference aims to expound on the research in Grid.

What are the most cited papers published at the conference?

  • TEEN: a routing protocol for enhanced efficiency in wireless sensor networks (1924 citations)
  • APTEEN: a hybrid protocol for efficient routing and comprehensive information retrieval in wireless (1109 citations)
  • An adaptive energy-efficient and low-latency MAC for data gathering in wireless sensor networks (923 citations)

Research areas of the most cited articles at International Parallel and Distributed Processing Symposium:

The conference publications explore disciplines such as Parallel computing, Distributed computing, Computer network, Scheduling (computing) and Scalability. The most cited articles explore research in Resource allocation and overlapping concepts in Load balancing (computing) to expand the discourse in Distributed computing. The most cited articles explore research in Computer network alongside concepts in Wireless ad hoc network and other areas of study in Mobile ad hoc network.

What topics the last edition of the conference is best known for?

  • Operating system
  • Computer network
  • Artificial intelligence

The previous edition focused in particular on these issues:

The conference aims to foster the development of research in Parallel computing, Distributed computing, Scalability, Graph and Software. Sparse matrix and Data structure are some topics wherein Parallel computing research discussed in the event have an impact. The studies on Distributed computing discussed can also contribute to research in the domains of Scheduling (computing) and Cloud computing.

International Parallel and Distributed Processing Symposium focuses on Scheduling (computing) as well as the interrelated topic of Workload. International Parallel and Distributed Processing Symposium explores issues in Graph which can be linked to other research areas like Distributed algorithm and Graph (abstract data type).

The most cited articles from the last conference are:

  • MD-GAN: Multi-Discriminator Generative Adversarial Networks for Distributed Datasets (54 citations)
  • DLHub: Model and Data Serving for Science (40 citations)
  • A Modular Benchmarking Infrastructure for High-Performance and Reproducible Deep Learning (39 citations)

Papers citation over time

A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Research.com

The top authors publishing at International Parallel and Distributed Processing Symposium (based on the number of publications) are:

  • Jack Dongarra (41 papers) published 4 papers at the last edition the same number as at the previous edition,
  • Marco D. Santambrogio (28 papers) published 3 papers at the last edition, 4 less than at the previous edition,
  • Dhabaleswar K. Panda (25 papers) published 3 papers at the last edition, 1 more than at the previous edition,
  • Martin Schulz (25 papers) published 1 paper at the last edition the same number as at the previous edition,
  • Yves Robert (24 papers) published 1 paper at the last edition, 1 less than at the previous edition.

The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.

Research.com

Only papers with recognized affiliations are considered

The top affiliations publishing at International Parallel and Distributed Processing Symposium (based on the number of publications) are:

  • IBM (148 papers) published 8 papers at the last edition, 3 less than at the previous edition,
  • Georgia Institute of Technology (93 papers) published 8 papers at the last edition, 5 less than at the previous edition,
  • Lawrence Livermore National Laboratory (84 papers) published 8 papers at the last edition, 5 less than at the previous edition,
  • Argonne National Laboratory (82 papers) published 10 papers at the last edition, 1 less than at the previous edition,
  • Ohio State University (81 papers) published 8 papers at the last edition, 3 more than at the previous edition.

The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.

Research.com

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

Research.com

During the most recent 2019 edition, 3.41% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 23.14% were posted by at least one author from the top 10 institutions publishing at the conference. Another 8.24% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 14.90% of all publications and 53.73% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.

Research.com

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

Research.com

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

Research.com

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Research.com

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Previous Editions

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