A new study published late last year in the Monthly Notices of the Royal Astronomical Society used supercomputer simulations to explore molecular gas within and surrounding the intracluster medium, or the space between galaxies in a galaxy cluster.
A research team from SDSC and institutes in Sweden and France have published a study on the OLIG2 inhibitor as a way to improve prognoses for brain cancer patients.
The American Association for Thoracic Surgery (AATS) has adopted an open-source, cloud-based platform led out of the San Diego Supercomputer Center (SDSC) that addresses widely recognized challenges with historical platforms throughout the cardiothoracic surgical community.
Scientists at the Southwest Research Institute (SwRI) used SDSC’s Comet supercomputer to help model the formation of terrestrial planets such as Mercury, Venus, and Mars in a quest to explore if there are Earth-like planets outside our solar system.
Building upon decades of research on how to make boron carbide even more efficient, an engineering team at the University of Florida (UF) has been conducting simulations using SDSC's Comet supercomputer to better understand the nanoscale level of this important material.
The amount of carbon in the Earth’s terrestrial ecosystems is likely to decline by about 10 percent through the year 2100, according to USGS researchers who used SDSC's 'Comet' supercomputer to conduct simulations.
SDSC and the Wisconsin IceCube Particle Astrophysics Center (WIPAC) successfully completed a computational experiment as part of a multi-institution collaboration that marshalled all globally available for sale GPUs (graphics processing units) across Amazon Web Services, Microsoft, and Google.
San Diego-based Predictive Science, Inc. this week released their first forecast for the 2019-2020 influenza season, which typically runs from November through March.
Researchers at the San Diego Supercomputer Center at UC San Diego have launched an open-source software called SeedMeLab, which provides a host of features for researchers across all disciplines to manage and disseminate their data.
MIT’s Computer Science & Artificial Intelligence Laboratory (CSAIL) and the Center for Applied Internet Data Analysis (CAIDA) at SDSC have developed a new machine learning system to identify "serial hijackers" of internet IP addresses.