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Scope and Interests

The technological trends in HPC system evolution indicates an increasing burden placed on application developers due to the management of the unprecedented complexity levels of hardware and its associated performance characteristics. Many existing scientific applications codes are unlikely to perform well on future systems without major modifications or even complete rewrites. In the future, it will be necessary to utilize, in concert, many characteristics such as multiple levels of parallelism, many lightweight cores, complex memory hierarchies, novel I/O technology, power capping, system-wide temporal/spatial performance heterogeneity and reliability concerns. The parallel and distributed computing (PDC) community has developed new programming models, algorithms, libraries and tools to meet these challenges in order to accommodate productive code development and effective system use. However, the scientific application community still needs to identify the benefit through practical evaluations.

Thus, the focus of this workshop is on methodologies and experiences used in scientific and engineering applications and algorithms to achieve sustainable code development for better productivity, application performance and reliability. In particular, we will focus on the following topics in parallel and distributed scientific and engineering applications, and not limited to:

  • Big scientific data
  • Performance modeling and simulation for the execution of scalable scientific applications on new heterogeneous architectures
  • Graph analytics with their (scientific) applications
  • Code modernization methodologies and experiences for adapting the changes in future computing systems
  • Languages for scientific computing on hybrid systems (e.g. Python, MPI+X where X is OpenMP, OpenCL, CUDA etc.)
  • Tools and techniques for improving the performance, reliability and resilience of scientific applications
  • Use cases of enterprise distributed computing technology (such as MapReduce, Data Analytics and Machine-learning tools) in scientific and engineering applications
  • Scalable parallel and distributed algorithms supporting science and engineering applications
  • Performance portability across heterogeneous architecture


The conference proceedings will be published by IEEE Computer Society. Selected papers from the proceedings will be invited for publication in journal special issues.

Important Dates

Paper submission due: February 5, 2022
Author Notification: March 04, 2022
Final camera-ready paper: March 15, 2022
Workshop Date: June 03, 2022

Paper Submission Guidelines

All papers must be submitted electronically and in PDF format. The material presented should be original and not published or under submission elsewhere. Authors should submit either full papers of up to 10 pages, or short papers of up to 4 pages, following strictly the IEEE Computer Society Proceedings Manuscript style, using two-column, single-space format, with 10-point font size. Figures and references must be included in the page limit. Oversized papers will be automatically rejected by the PC chairs. At least one of the authors of each accepted paper must register early to attend the conference, in order for the paper to appear in the conference proceedings.

PDSEC-2022 paper submission link:

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