This technology guide will help government thought leaders in how best to use data analytics to manage and derive value from an increased dependence on data. “This guide provides an in-depth overview of the use of data analytics technology in the public sector. Focus is given to how data analytics is being used in the government setting with a number of high-profile use case examples, how the Internet-of-Things is taking a firm hold in helping government agencies collect and find insights in a broadening number of data sources, how government sponsored healthcare and life sciences are expanding, as well as how cyber security and data analytics are helping to secure government applications.”
MySQL is a widely used, open source relational database management system (RDBMS) which is an excellent solution for many applications, including web-scale applications. To learn more about accelerating MySQL for demanding OLAP and OLTP use cases with Apache Ignite download this guide.
In this document, our focus is on “industrializing” big data infrastructure—bringing operational maturity to the Hadoop data ecosystem, making it easier and cost-effective to deploy at enterprise scale, and moving companies from the proof of concept stage into production-ready deployments. Download this Guide to Big Data on an Industrial Scale to learn more.
Object stores represent a simpler, more scalable solution and one that is easily accessed over standard web-based protocols. To learn more about Object Stores download this guide.
For this report, DDN performed a number of experimental benchmarks to attain optimal IO rates for Paradigm Echos application workloads. It present results from IO intensive Echos micro-benchmarks to illustrate the DDN GRIDScaler performance benefits and provide some detail to aid optimal job packing in 40G Ethernet clusters. To find out the results download this guide.
A parallel file system offers several advantages over a single direct attached file system. By using fast, scalable, external disk systems with massively parallel access to data, researchers can perform analysis against much larger datasets than they can by batching large datasets through memory. To Learn More about the Parallel File Systems download this guide
As exponential data growth reshapes the industry, engineering, and scientific discovery, success has come to depend on the ability to analyze and extract insight from incredibly large data sets. Exascale computing will allow us to process data, run systems, and solve problems at a totally new scale and this will become vitally important as problems grow ever larger, ever more difficult. Our unmatched ability to bring new technology to the mainstream will provide systems that are markedly more affordable, usable, and efficient at handling growing workloads. To learn more download this white paper.
Using commodity hardware and the “plug-and-play” NumaConnect interconnect, Numascale delivers true shared memory programming and simpler administration at standard HPC cluster price points. Download this white paper to learn more.
When the National Center for Supercomputing Applications (NCSA) was created at the University of Illinois 27 years ago, it had a unique proposition—its computing, data and networking resources were designed for industry as well as academia. Over the years, NCSA’s efforts to serve industry have grown and matured. Download this white paper to learn more
The Central Processing Unit (CPU) has been at the heart of High Performance Computing (HPC) for decades. However, in recent years, advances in parallel processing technology mean the landscape has changed dramatically. To learn more download this white paper.