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UrgentHPC 2020 : Second international workshop on HPC for Urgent Decision making

Event Date: Nov 13, 2020 - Nov 13, 2020
Submission Deadline: Aug 28, 2020
Notification of Acceptance: Sep 20, 2020
Camera Ready Version Due : Sep 30, 2020


Leveraging HPC for urgent decision making requires expertise in a wide range of areas, from dealing with real-time data, to experience in generating results within a specific time frame (real-time constraints), and generating visualisations enabling front-line decision makers to make correct choices first time, every time. It isn’t just technical challenges, but also policy issues that also need to be considered such as utilising our HPC machines in a more interactive manner to enable the urgent exploration of numerous disaster responses.

This workshop will bring together stakeholders, researchers and practitioners from across the HPC community to identify and tackle issues involved in using HPC for urgent decision making. Success stories, case-studies and challenges will be shared, with the goal of further building up a community around leveraging HPC as an important tool in urgently responding to disasters and societal challenges.

Call For Paper

We invite you to submit both full and hot-topic research papers detailing original work in the area of using HPC for making urgent decisions. Topics of interest for workshop submissions include (but are not limited to):

  • Example use-cases and case-studies that use HPC for urgent decision making
  • Techniques for integrating HPC workflows with real-time data
  • Approaches to verify and validate unreliable real-time data, for instance from sensors, IoT and satellites
  • System design for data reduction and pre-processing at source, for instance using edge computing and heterogeneous resources such as FPGAs
  • The use of data formats and conversion techniques to support the handling of data from numerous and diverse sources
  • Algorithmic techniques to guarantee result generation in specific time frames, such as result refinement which generates more accurate results as time progresses
  • Studies of leveraging HPC for workloads with real-time time constraints
  • Changes to existing HPC technologies and policies that are required to support using HPC interactively
  • The ability for HPC codes to adapt their resource requirements dynamically, for instance via elastic compute
  • Visualisation and presentation techniques to support rapid and accurate urgent decision making by the end user
  • Reduction and feature extraction of results to highlight critical issues of interest
  • Complimenting results with provenance data for additional context and certainty
  • Data analysis techniques for making urgent decisions in response to disasters

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