February 7, 2017
For more than a decade the swelling output from life sciences experimental instruments has been overwhelming research computing infrastructures intended to supp Read more…
September 8, 2016
Modeling protein interactions with drugs has long been computationally challenging. One obstacle is these interactions often take relatively long to occur and conventional molecular dynamics simulation is insufficient. This week a group of researchers, using several EXSEDE supercomputers, report a hybrid in silico-experimental approach that shows promise as a drug design tool for use with G protein-coupled receptors (GPCRs) Read more…
November 18, 2013
According to Dr. Klaus Schulten from the University of Illinois, the molecular dynamics and visualization programs NAMD and VMD, which serve over 300,000 regist Read more…
January 14, 2010
NVIDIA has announced the Tesla Bio Workbench, a new program designed to bring together the computational components needed to run GPU-accelerated bioscience applications. The rationale is the same one NVIDIA's been touting ever since it got into the high performance computing business: take advantage of the superior performance of the GPU in order to lower the entry point for HPC. Read more…
Whether an organization chooses a cloud for general business needs or a highly tailored workload, the spectrum of offerings and configurations can be overwhelming. To help you navigate the various cloud options available today, we're breaking down your options, exploring pros and cons, and sharing ways to keep your options open and your business agile as you execute your cloud strategy.
Researchers in academic labs and commercial R&D groups continue to need more compute capacity, which means leveraging the latest innovations in HPC technologies as well as an assortment of resources to meet the unique needs of different workloads. Increasingly, systems based on Arm processors are stepping into that role, offering low power consumption and strategic advantages for HPC workloads.
Whether it's for fraud detection, personalized medicine, manufacturing, smart cities, autonomous vehicles and many other areas, advanced-scale computing has exploded beyond the realm of academia and government and into the private sector. And with data-intensive workloads on the rise, commercial users are turning to HPC-based infrastructure to run the AI, ML and cognitive computing applications that their organizations depend on.
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