June 2, 2011
The notion of "personal genomics" has generated a great deal of buzz over the last several years but according to one researcher, many of the promises that lie at the "plateau of productivity" for this technology are tied to some significant computational-side complexities. Read more…
May 31, 2011
Projects like the Sloan Digital Sky Survey have provided a wealth of cosmological data for scientists to explore in detail. However, making use of those terabytes -- and generating far more data in the process of simulating and analyzing new concepts -- is highlighting the bottlenecks for scientific computing at massive scale. Read more…
October 27, 2010
Languages like R and MATLAB, which were once unofficially reserved for technical computing domains are slowly finding their way into enterprises due to the rise in demand for large-scale data analytics. This demand is coupled with recent announcements about cloud-based ways to use these languages, opening new doors to access and use. 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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