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Special issue XSEDE16 & PEARC17 – Practice and experience in advanced research computing
Author(s) -
Dahan Maytal,
Navrátil Paul
Publication year - 2019
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5325
Subject(s) - cyberinfrastructure , geospatial analysis , computer science , workflow , service (business) , data science , government (linguistics) , world wide web , linguistics , philosophy , cartography , economy , database , economics , geography
The conference on Practice and Experience in Advanced Research Computing (PEARC) provides a forum for discussing challenges, opportunities, and solutions among the broad range of participants in the research computing community. This community-driven effort builds on successes of the past and aims to grow and be more inclusive by involving additional local, regional, national, and international cyberinfrastructure and research computing partners spanning academia, government, and industry. The PEARC conference series is working to integrate and meet the collective interests of our growing community. PEARC originated from the XSEDE conference series, which showcased the discoveries, innovations, challenges, and achievements of those who use and support NSF Extreme Science and Engineering Discovery Environment (XSEDE) resources and services, as well as other digital resources and services throughout the world. The following papers represent the best papers from the transitionary conferences of this research community: XSEDE16, the final XSEDE conference, and PEARC17, the inaugural PEARC conference. These papers capture both important research contributions to the advanced computing community and best practices for advanced computing systems and remote user interfaces. These three papers cover a diverse set of topics: the impact of science gateways, innovative hardware impacting cyberinfrastructure, and improving computational frameworks with workflows, machine learning, and visualizations. The paper by Hu et al1 discusses how geospatial data have exploded to massive volume and diversity and subsequently cause serious usability issues for researchers in various scientific areas. This paper describes TopoLens, a cyberGIS community data service framework to facilitate geospatial big data access, processing, and sharing based on a hybrid supercomputer architecture. TopoLens delivers community data services developed for easy and efficient access to high-resolution topographic data. It supports on-demand data and map services, powered by hybrid cyberinfrastructure with cloud and HPC support, to efficiently produce datasets that are customized based on a user's request. The usability of TopoLens has been acknowledged in the topographic user community evaluation. The paper by Hancock et al2 dives into Jetstream, the NSF's first distributed production cloud resource. Jetstream offers a unique capability within the XSEDE-supported US national cyberinfrastructure, delivering interactive virtual machines (VMs) via the atmosphere interface. As a multi-region deployment that operates as an integrated system, Jetstream is proving effective in supporting modes and disciplines of research traditionally underrepresented on larger XSEDE-supported clusters and supercomputers. Jetstream has been used to perform research and education in biology, biochemistry, atmospheric science, earth science, and computer science. Lastly, the paper written by Li and Song3 discusses the challenges of large-scale simulations generating huge amounts of data with potentially critical information that is saved in intermediate files and is not instantly visible until advanced data analytics techniques are applied after reading all simulation. In this paper, the authors build a new computational framework to couple scientific simulations with multi-step machine learning processes and in situ data visualizations. This computational framework is built upon different software components and provides plug-in data analysis and visualization functions over complex scientific workflows. With this advanced framework, users can monitor and get real-time notifications of special patterns or anomalies from ongoing extreme-scale turbulent flow simulations. These three papers demonstrate the wide range of topics addressed by the PEARC community, which spans academic researchers, resource providers, industry partners, and other affiliates. The work done by this community and the insights shared at the annual PEARC conference are intended for broad application for those active in advanced computing research and practice. If you are already part of the PEARC community, we look forward to seeing you soon; if you have not yet attended a PEARC conference, we hope these papers will provide motivation and justification to invest your time and travel to join us. The editors would like to acknowledge the hard work of the program committees, both for XSEDE16 and for PEARC17, whose combined efforts resulted in this special issue. Sincerely, Paul Navrátil Maytal Dahan Technical Program Chair Technical Program Chair XSEDE16 PEARC17