News Archive - March 2023

OSC: Finding Solutions for Long-term Research Data Storage Needs

March 20, 2023 | HPCwire

Case Western Reserve University is one of the most research-intensive higher education institutions in the state of Ohio. Ranked R1 by the Carnegie Classification of Institutions of Higher Education, during fiscal year 2021 it attracted more than $390 million in competitive sponsored research projects.

OSC’s automated tape library system performs daily backups to store massive amounts of information in a durable, accessible format for long-term reliability.

The C-FEWS framework: Supporting studies of climate-induced extremes on food, energy, and water systems at the regional scale

March 16, 2023 | Frontiers in Environmental Science

Climate change continues to challenge food, energy, and water systems (FEWS) across the globe and will figure prominently in shaping future decisions on how best to manage this nexus. In turn, traditionally engineered and natural infrastructures jointly support and hence determine FEWS performance, their vulnerabilities, and their resilience in light of extreme climate events. We present here a research framework to advance the modeling, data integration, and assessment capabilities that support hypothesis-driven research on FEWS dynamics cast at the macro-regional scale.

GlobusWorld 2023 Program Announced

March 13, 2023 | For Immediate Release

Chicago, IL - March 14, 2023 - Globus, the leading research data management service, today announced the lineup of speakers for GlobusWorld 2023, being held April 25-27, 2023 in Chicago, IL, and online. Now in its 21st year, GlobusWorld brings together over 200 researchers, systems administrators, developers and IT leaders from top computing centers, labs and universities around the world.

Edge-Based, Machine-Learning-Enabled Materials Exploration Pipeline

March 10, 2023 | Argonne National Lab - Photon Sciences

New Argonne machine learning models will open the possibility for real-time experiment feedback critical to understanding materials.

Researchers from Argonne and SLAC have demonstrated the ability to use beamline data from live experiments to train machine learning (ML) models on remote supercomputers and deploy the results on edge devices at beamlines, enabling near-real-time data processing.