Revisiting the CANcer Distributed Learning Environment (CANDLE) Project
The CANcer Distributed Learning Environment (CANDLE) project provides deep-learning computing methodologies for accelerating cancer research.
The CANcer Distributed Learning Environment (CANDLE) project provides deep-learning computing methodologies for accelerating cancer research.
Machine learning technologies are creating inspiring new opportunity vistas for scientific discovery and research at the exascale.
Application developers can get expert answers through Zoom-based calls to coding questions pertaining to OpenMP offloading.
As principal investigator of the ECP SOLLVE project, Sunita Chandrasekaran emphasizes the development of sustainable software.
Sunita Chandrasekaran of Brookhaven National Laboratory is the new principal investigator of the SOLLVE project, which is advancing OpenMPI.
The winner and two of three finalists of the SC20 Gordon Bell Special Award for COVID-19 competition leveraged the scalable workflow technologies brou
The Exascale Computing Project's software engineers and computer scientists are building a pyramid—a software stack—that will support exascale's full processing power.
A collaborative team is working to get NWChem ready to run on exascale machines and to provide a starting point for future code development.
An article on phys.org by Ariana Tantillo of Brookhaven National Laboratory (BNL) describes team activities during the recent OpenMP hackathon at BNL.
The Computational Science Initiative at Brookhaven National Laboratory will host its 3rd GPU Hackathon, a free event, on September 23–27.
New ExaLearn Co-Design Center to be led by Brookhaven National Laboratory's Francis (Frank) Alexander. The Exascale Computing Project has initiated its sixth Co-Design Center, ExaLearn, to be led by Principal