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Accelerating the speed and accessibility of artificial intelligence technologies

As AI technologies become even faster and more accessible, the computing community will be positioned to help organizations achieve the desired levels of efficiency that are critically needed in order to resolve the world’s most complex problems, and increase safety, productivity, and prosperity. Learn more about AI Technologies … download this white paper.

Accelerate MySQL for Demanding OLAP and OLTP Use Cases with Apache Ignite

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.

insideBIGDATA Guide to Use of Big Data on an Industrial Scale

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.

insideBIGDATA Guide to Artificial Intelligence & Deep Learning

In this guide we explain the difference between AI, machine learning and deep learning, and includes highlights of the insideBIGDATA audience survey. To learn more about AI and deep learning download this guide.

insideHPC Special Report: A Trusted Approach for High Performance Networking

The high performance networking interconnect landscape is in transition. InfiniBand and Intel Omni-Path will compete for the performance crown, while Ethernet will remain the ubiquitous standard for commercially oriented systems.

Nine Critical Features for Object Stores

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.

Paradigm and DDN: Achieving the Ultimate Efficiency for Seismic Data Analysis

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.

Parallel File System Delivers Better Strategies, Faster

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

In Memory Data Grids

This white paper provides an overview of in-memory computing technology with a focus on in-memory data grids. It discusses the advantages and uses of in-memory data grids and introduces the GridGain In-Memory Data Fabric. Download this guide to learn more.

insideHPC Research Report on In-Memory Computing

To achieve high performance, modern computer systems rely on two basic methodologies to scale resources. A scale-up design that allows multiple cores to share a large global pool of memory and a scale-out design design that distributes data sets across the memory on separate host systems in a computing cluster. To learn more about In-Memory computing download this guide from IHPC and SGI.