February 1, 2012
Despite high-hopes, community support, and a lot of good science, the Magellan cloud computing project has ended after a two-year run. Like the famous explorer, the current-day Magellan also navigated uncharted waters and documented the journey for the benefit of future generations. The results of the two-year study are now available in the form of an extensive 169-page report. Read more…
June 22, 2010
Since its launch in 2009, the Magellan cloud computing testbed has produced some results of interest to the scientific computing community in its effort to evalue the cost-effectiveness and energy-efficiency, not to mention performance for clouds in scientific applications. Kathy Yelick, NERSC Director discusses some key findings. Read more…
October 13, 2009
Like many organizations that rely on industrial-strength datacenters, the US Department of Energy (DOE) would like to know if cloud computing can make its life easier. To answer that question, the DOE is launching a $32 million program to study how scientific codes can make use of cloud technology. 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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