[hpc-announce] PEARC 2020 Call for papers!!!!!

[Stewart, Craig Alan]

Dear Colleagues,

 

You are invited to submit papers for the PEARC20 Conference – Catch the wave that will be held in Portland, July 26–30, 2020. Presentations may address any topic related to advanced research computing, but topics consistent with one or more of the four technical tracks listede below are of particular interest. 

 

Key dates are: 
Submission – January 22nd, 2020
Reviewer feedback – March 4th, 2020
Camera-ready submission – May 4th, 2020
Conference – 26-30 July 2020, Portland, OR, USA
 

 

Technical Tracks for PEARC20

Advanced research computing environments – systems and system software: Practice and experience relating to the system (computing hardware, storage hardware, visualization hardware, and network hardware) and system software that drives the “hardware” side of cyberinfrastructure and research computing environments. Examples of relevant topics: GPUs, CPUs, and FPGAs as computational environments; experience with advanced storage systems; hardware and systems for data-centric computing; networking challenges; design and use of visualization environments; funding and operating of advanced research computing facilities (including considerations of cost of locally-sited hardware vs remote hardware such as cloud facilities), systems procurement, systems administration, cybersecurity, practice and experience in facilitating the acquisition, operation, and use of advanced hardware, software, networks and services to securely and sustainably advance research, scholarship, and creativity; performance comparisons and performance aspects of cloud environments.

Application software, support, and outcomes: From research computing experts that enable discoveries and outcomes. In many cases application advances and support are somewhat interchangeable – a more intuitive application interface may reduce (or perhaps eliminate) some needs for support. Etc. Outcomes – discoveries, new scholarly insights, and new artistic creations – are the reason that we all do what we do. Examples of relevant topics: support for researchers and other end-users; building and sustaining partnerships among providers of advanced research computing; cost-effective use of cloud and shared HPC resources; peta- and exascale computation; data and extreme data challenges; development and implementation of computational methods and software to enable the application of advanced research computing to any field of research or scholarship; analysis and understanding of research data using statistics, databases, visualization, virtual reality, etc.; science gateways; workflow systems; description of novel results or breakthroughs achieved in any field of research or scholarship for which the use of advanced research computing; use of advanced research computing to advance science, engineering, medicine, manufacturing, scholarship, public services, the arts, etc., by developing and leveraging advanced hardware, software, tools, networks, and services; issues of supporting local systems, remote systems, and cloud environments go in this track. For example, this could include ways research computing experts have supported research, as well as examples of computing research and data-enabled research made possible through research computing infrastructure, software, and support.

People involved in research computing – workforce development, diversity, and professionalization: Practice and experience in developing and sustaining advanced research computing as a profession, and developing a highly proficient workforce that realizes the full potential of people in all demographic groups. Examples of relevant topics: training in advanced research computing; curriculum development for STEM, computer science, data science, and computational sciences; learning technologies; work with underserved communities, career and workplace improvement; professional development in relevant soft and technical skills, defining research computing, and data career tracks.

Trending now – machine learning and artificial intelligence: Practice and experience related to the use of machine learning and artificial intelligence to advance science, engineering, medicine, manufacturing, scholarship, public services, the arts, etc. Examples of relevant topics: development of algorithms and software for machine learning, neural nets, deep learning, and artificial intelligence; applications of such algorithms and software; design or use of specialized purpose hardware or software designed to enable such applications in the context of advanced research computing facilities.

 

See https://pearc.hosting2.acm.org/pearc20/program/call-for-participation/ for details.

 

Sincerely,

 

Craig A. Stewart & Sean Cleveland

PEARC 20 Technical Program Co-Chairs