The European programming framework EPEEC has announced an important milestone with the publication of the EPEEC Programming Guidelines for Parallel Applications
AMD in collaboration with Lawrence Livermore National Laboratory (LLNL) and HPE, has announced that El Capitan, the upcoming exascale class supercomputer at LLNL, will deliver more than 2 exaflops of double-precision performance.
The OpenMP Architecture Review Board (ARB) has released Technical Report 7, the final preview and public comment draft for the future OpenMP API, version 5.0
The main aim of this workshop is to present and debate advanced topics, open questions, current and future developments, and challenging applications related to advanced high-performance distributed computing and data systems, encompassing implementations ranging from traditional clusters to warehouse-scale data centres, and with architectures including hybrid, multicore, distributed, and cloud models.
Robert Roe reports on the potentially far-reaching benefits of exascale computing for European research
Elsevier and ExactCure recently announced a collaboration to develop and offer to hospitals – without charge – drug-specific exposure models for 20 already approved medicines that are being tested as potential treatments for Covid-19.
With the world’s focus on the COVID-19 pandemic, LIMS providers are working to develop solutions tailored to assist in the testing and management of virus samples.
Researchers at Harvard Medical School (HMS) have released an open source drug discovery platform, VirtualFlow, that harnesses supercomputing power to screen potentially billions of small organic compound structures in parallel, in the hunt for promising new drug molecules.
When designing a component or system, where do you start? In days gone by, designers would literally go back to the drawing board, using their experience and expertise to develop a new concept.
Effective utilisation of computing tools is critical to both AI and HPC research, with recent projects in both fields highlighting the scientific benefit of carefully managing resources.
Advances in computer vision combined with AI computing are helping pathologists to more accurately identify subtypes of cancer - leading to better treatments for patients, explains Dan Ruderman.
