October 2, 2012
The “big data” revolution is upon us, fed by the need in both the public and private sectors to quickly analyze large datasets for important patterns and trends. With big data analysis, ecommerce vendors can target customers more precisely, financial analysts can quickly spot changing market conditions, manufacturers can tune logistics planning, and the list goes on. They all need powerful, easy to use analysis tools to maintain a competitive edge. Read more…
July 2, 2012
By enabling extremely fast and scalable data access even under large and growing workloads, in-memory data grids (IMDGs) have proven their value in storing fast-changing application data, such as financial trading data, shopping data, and much more. As organizations work to efficiently access their critical business data across multiple sites or scale their processing into the cloud, the need rapidly has grown to quickly and seamlessly migrate data where it is needed. The use of IMDGs creates an exciting opportunity for organizations to employ powerful global strategies for data sharing. Federating IMDGs across multiple sites enables seamless, transparent access to data from any site and provides an ideal solution to the challenge of global data integration. Read more…
June 4, 2012
A hallmark of the Information Age is the incredible amount of business data that companies have to store and analyze, so-called “big data.” The ability to efficiently search data for important patterns can provide an essential business edge. Using an in-memory data grid with built-in analytics can provide near real-time analysis to keep you ahead of the competition. 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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