As you’ve increasingly seen in news headlines, secure access to shared data is not only an issue for Federal and local government agencies and the Intelligence Community – it has also become an issue for business enterprises needing to protect their intellectual property and other sensitive business data while engaging on a global scale with their partners and contractors.
This article series is the first to explore the Seagate ClusterStor™ Secure Data Appliance, which is designed to address government and business enterprise need for collaborative and secure information sharing within a Multilevel Security (MLS) framework at Big Data and HPC Scale. Compared to prior methods, this provides vast cost savings in reduced capital equipment and networks as well as reduced operational complexity, floor space, weight, power, and cooling while satisfying today’s requirements for performance, collaborative secure data sharing, and availability.
Virtualization allows workloads to be compartmentalized in their own VM in order to take full advantage of the underlying parallelism of today’s multicore, heterogeneous HPC systems without compromising security. This approach is particularly beneficial for organizations centralizing multiple groups on to a shared cluster or for teams with security issues – for example, a life sciences environment where access to genomic data needs to be restricted to specific researchers.
“NCSA has worked with more than one-third of the Fortune50, in sectors including manufacturing, oil and gas, finance, retail/wholesale, bio/medical, life sciences, astronomy, agriculture, technology, and more. NCSA’s Private Sector Program currently boasts 26 partners. PSP’s core mission is to help its partner community gain a competitive edge through expert use of modern, high-performance digital and human resources.”
“With the marriage of POWER8 and NVIDIA GPUs connected via NVLink, these systems are going to be simply unbeatable when it comes to handling some of the most demanding computing tasks for enterprises and popular consumer Web services. One example: harvesting insights in real time from massive amounts of medical data. Also, IBM is working to accelerate a range of its enterprise data analytics applications with GPUs, allowing customers to take advantage of these high-performance POWER-GPU systems.”