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The Convergence of Big Data and HPC

In this special guest feature, Barry Bolding, Senior VP and Chief Strategy Officer at Cray Inc., discusses a highly germaine topic for many enterprises today: the intersection of big data and high performance computing.

Reader Survey: Are AI/Machine Learning/Deep Learning in Your Future?

Please participate in our new audience survey on AI/machine learning/deep learning and give us your opinions about whether your company has any plans to become an AI Enterprise?

Water Industry Gets Smart on Big Data

The water and wastewater industry is in transition to a digital revolution that has the potential to transform the industry from the use of data-driven technologies, with utility sector spending dwarfing the industrial market. This is according to a new report by Global Water Intelligence (GWI) that provides a detailed guide to the opportunities in this smart market.

The Rise of Deep Learning for Healthcare and Life Sciences

The insideBIGDATA Guide to Healthcare & Life Sciences is a useful new resource directed toward enterprise thought leaders who wish to gain strategic insights into this exciting new area of technology. This segment focuses on the rise of deep learning.

UCHealth Improves Surgeons’ Utilization of Operating Rooms with Machine Learning Technology

UCHealth announced its inpatient operating room (OR) utilization at University of Colorado Hospital has seen a 16 percent increase for the blocks exchanged through mobile block swaps, in just three months with the launch of smart block scheduling based on predictive analytics.

Driving High Frequency Trading and Compliance with In Memory Computing

In the video presentation below, courtesy of our friends over at GridGain, Eric Karpman shares how some of the world’s largest financial institutions use in-memory computing to address the challenges of high frequency trading.

New SGI Scale-out Solution for SAP HANA Does Real-Time Applications

Today SGI announced that enterprises can now leverage the Intel-based SGI UV 300H server in a multi-node cluster (scale out) to run SAP Business Warehouse (SAP BW) on SAP HANA or new SAP BW/4HANA. Unique to SGI, the cluster nodes can later be reconfigured as single-node systems with 1 to 32TB of shared memory (scale up) to run SAP S/4HANA and other real-time applications. “For large enterprises that plan to migrate to SAP S/4HANA but wish to begin their journey to SAP HANA with SAP BW, our new SGI cluster offering is unquestionably the optimal solution,” said Jorge Titinger, president and CEO, SGI. “The scalability of the SGI UV 300H architecture coupled with our expertise in mission-critical environments provides an ideal path to real-time business with SAP HANA.”

Video: Why use Tables and Graphs for Knowledge Discovery System?

In this video from the 2016 HPC User Forum in Austin, John Feo from PNNL presents: Why use Tables and Graphs for Knowledge Discovery System? “GEMS software provides a scalable solution for graph queries over increasingly large data sets. As computing tools and expertise used in conducting scientific research continue to expand, so have the enormity and diversity of the data being collected. Developed at Pacific Northwest National Laboratory, the Graph Engine for Multithreaded Systems, or GEMS, is a multilayer software system for semantic graph databases. In their work, scientists from PNNL and NVIDIA Research examined how GEMS answered queries on science metadata and compared its scaling performance against generated benchmark data sets. They showed that GEMS could answer queries over science metadata in seconds and scaled well to larger quantities of data.”

insideBIGDATA Guide to Healthcare & Life Sciences

The insideBIGDATA Guide to Healthcare & Life Sciences is a useful new resource directed toward enterprise thought leaders who wish to gain strategic insights into this exciting new area of technology. The guide provides an overview of the utilization of big data technologies as an emerging discipline in healthcare and life sciences. It explores the characteristics of this business strategy and the benefits of leveraging big data technologies within these sectors. It also touches on the challenges and future directions of big data and analytics in the healthcare and life sciences industries.

Finding and Treating Sufferers of Rare Diseases: Big Data Techniques at Work

In this special guest feature, Dr. Ritu Chadha, IEEE Senior member, Executive Director at Vencore Labs, explains one commercial application of machine learning and information theoretics, among other techniques, to big data to reduce human suffering.