Sign up for our newsletter and get the latest big data news and analysis.

Case Study: More Efficient Numerical Simulation in Astrophysics

Novosibirsk State University is one of the major research and educational centers in Russia and one of the largest universities in Siberia. When researchers at the University were looking to develop and optimize a software tool for numerical simulation of magnetohydrodynamics (MHD) problems with hydrogen ionization —part of an astrophysical objects simulation (AstroPhi) project—they needed to optimize the tool’s performance on Intel® Xeon Phi™ processor-based hardware.

Go for Big Data

Many of the hottest modern infrastructure projects are powered by the Go programming language, including Kubernetes, Docker, Consul, etcd, and many more. Go is turning into a go to language for devops, web servers, and microservices. One route to providing robust, performant, and scalable data processing within Go is to utilize the Intel® Data Analytics Acceleration Library (Intel® DAAL) within Go programs.

OpenVX – The Standard for Computer Vision

OpenVX is an API enabling software developers to add hardware accelerated computer vision capabilities to their programs. Coupled with the current upswing in the use of deep learning technologies, computer vision applications with OpenVX are becoming very important. OpenVX is an integral part of Intel Computer Vision SDK. This comprehensive toolkit is for developing and deploying vision-oriented solutions on platforms from Intel, including autonomous vehicles, digital surveillance cameras, robotics, and mixed-reality headsets.

BlueData, Intel Compare Bare-Metal & Containers for Big Data Workloads

Has your business ever tried to decide between a bare-metal environment or a container-based environment for dealing with Big Data needs? BlueData and Intel collaborated to discuss this very issue in a benchmark study of the performance of Big Data workloads.

7 Steps From Raw Data to Insight

Data scientists generally ascribe to the “machine learning process” which is seen as a roadmap to follow when working on a data science project. The infographic at the end of this article provides a detailed work flow that it is general enough to encompass pretty much any data science project.

Bringing Artificial Intelligence to Life

Artificial Intelligence (AI) may seem like a vision for a distant future, but in truth, AI is all around us as machines are increasingly learning to sense, learn, reason, act and adapt in the real world. This is transforming industries and changing our lives in amazing new ways, by amplifying human capabilities, automating tedious or dangerous tasks, and solving some of our most challenging societal problems. In this article, we’ll discuss the path to AI with Intel technologies.

Intel Case Study: Speeding Up a Big Data Platform

In this technology cast study, we’ll examine MeritData, Inc., a leading big data analysis technology and service provider in China. The company’s product is called Tempo, a big data platform that has been widely used by well-known power, manufacturing, financial, and global enterprises and by cloud service providers. MeritData helps its customers explore and exploit data value―and ultimately creates value through data processing, data mining, and data visualization solutions. This is achieved through the fusion of high-performance computing (HPC) technology, leading data analysis algorithms, high-dimensional visualization, and creative data visualization language.

ZTE Wireless Institute Achieves Performance Breakthrough for Deep Learning with Intel FPGAs

Intel and ZTE, a leading technology telecommunications equipment and systems company, have worked together to reach a new benchmark in deep learning and convolutional neural networks (CNN). The technology is what many companies in Internet search and AI are trying to advance, and includes picture search and matching, as one example.

Kx Streaming Analytics Demo Easily Crunches 1.2 Billion NYC Taxi Data Points Using Standard Intel Xeon Phi

In this contributed article, tech writer Sean Thielen describes how Kx crunches a 1.2 billion record database of New York City taxi cab ride data to demonstrate what the Intel Xeon Phi processor could mean to distributed big data processing.

FPGAs Speed Machine Learning at SC16 Intel Discovery Zone

In this video from SC16, Intel demonstrates how Altera FPGAs can accelerate Machine Learning applications with greater power efficiency. “The demo was put together using OpenCL design tools and then compiled to FPGA. From an end-user perspective, they tied it together using Intel MKL-DNN with CAFFE on top of that. This week, Intel announced the DLIA Deep Learning Inference Accelerator that brings the whole solution together in a box.”