[NEST Users] ISAV'21: In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization

Dear all, for our in situ workshop at this year’s Supercomputing (https://vis.lbl.gov/events/ISAV2021/) we are still looking for submissions. So, if you are doing work on visualizing or analysing the results of a NEST simulation while it is running, you might consider submitting, quickly. The deadline will be extended to August 27. Please, find the CfP below. Cheers, Tom Vierjahn -- Tom Vierjahn Professor of Computer Science Dept. Business Studies and Information Technology Westphalian University of Applied Sciences Bocholt, Germany -- ISAV 2021: In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization # Workshop Theme The considerable interest in the HPC community regarding in situ analysis and visualization is due to several factors. First is an I/O cost savings, where data is analyzed/visualized while being generated, without first storing to a file system. Second is the potential for increased accuracy, where fine temporal sampling of transient analysis might expose some complex behavior missed in coarse temporal sampling. Third is the ability to use all available resources, CPUs and accelerators, in the computation of analysis products. The workshop brings together researchers, developers and practitioners from industry, academia, and government laboratories developing, applying, and deploying in situ methods in extreme-scale, high performance computing. The goal is to present research findings, lessons learned, and insights related to developing and applying in situ methods and infrastructure across a range of science and engineering applications in HPC environments; to discuss topics like opportunities presented by new architectures, existing infrastructure needs, requirements, and gaps, and experiences to foster and enable in situ analysis and visualization; to serve as a “center of gravity” for researchers, practitioners, and users/consumers of in situ methods and infrastructure in the HPC space. # Participation/Call for Papers We invite two types of submissions to ISAV 2021: (1) short, 4-page (+references) papers that present research results, that identify opportunities or challenges, and that present case studies/best practices for in situ methods/infrastructure in the areas of data management, analysis and visualization; (2) lightning presentation submissions, consisting of a 1- or 2-page (+references) submission, for a brief oral presentation at the workshop. Short papers will appear in the workshop proceedings and authors will be invited to give an oral presentation of 15 to 20 minutes; lightning round submissions invited to present at the workshop will have author names and titles included as part of the proceedings. Submissions of both types are welcome that fall within one or more areas of interest. Areas of interest for ISAV include, but are not limited to: - In situ infrastructures: Novel designs for systems and libraries; Opportunities; Gaps - System resources, hardware, and emerging architectures: Enabling Hardware; Hardware and architectures that provide opportunities for In situ processing, such as burst buffers, staging computations on I/O nodes, sharing cores within a node for both simulation and in situ processing; Efficient use of heterogeneous architectures. - Methods/algorithms: Best practices; Analysis: Feature detection, statistical methods, temporal methods, geometric and topological methods; Visualization: information visualization, scientific visualization, time-varying methods; Data reduction/compression. - Case Studies and Data Sources: Examples/case studies of solving a specific science challenge with in situ methods/infrastructure; In situ methods/systems applied to data from simulations and/or experiments/observations. - Simulation and Workflows: Integration, data modeling, software-engineering; Resilience: error detection, fault recovery; Workflows for supporting complex in situ processing pipelines. - Requirements and Usability: Reproducibility, provenance and metadata; Using in situ to enable rapid and flexible post-processing; Simplified access to extreme heterogeneous resources.