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Take our AI & HPC Survey to Win an Amazon Echo Show Device

AI and Machine Learning have been called the Next Big Thing in High Performance Computing, but what kinds of results are your peers already getting right now? There is one way to find out–by taking our HPC & AI Survey. “We invite you to take our insideHPC Survey on the intersection HPC & AI. In return, we’ll send you a free report with the results and enter your name in a drawing to win one of two Echo Show devices with Alexa technology. The Echo Show is a voice-activated smart screen device that Amazon unveiled back in 2017.”

How Deep Learning is Causing a ‘Seismic Shift’ in the Retail Industry

 These days, taking big data further and integrating machine and deep learning means having a competitive edge in the retail industry. Analytics — and their analysis — have always been a cornerstone of retail success. And now, deep learning techniques are going to push the data boom to the next level. A new insideHPC special report, courtesy of Dell EMC and NVIDIA, explores how the retail industry is being transformed by machine and deep learning.

Bright Computing Release 8.1 adds new features for Deep Learning, Kubernetes, and Ceph

Today Bright Computing released version 8.1 of the Bright product portfolio with new capabilities for cluster workload accounting, cloud bursting, OpenStack private clouds, deep learning, AMD accelerators, Kubernetes, Ceph, and a new lightweight daemon for monitoring VMs and non-Bright clustered nodes. “The response to our last major release, 8.0, has been tremendous,” said Martijn de Vries, Chief Technology Officer of Bright Computing. “Version 8.1 adds many new features that our customers have asked for, such as better insight into cluster utilization and performance, cloud bursting, and more flexibility with machine learning package deployment.”

Reinventing the Retail Industry Through Machine and Deep Learning

Today, deep learning techniques are poised to disrupt the retail industry. As artificial neural networks become more and more efficient, and as graphics processing units get more and more powerful, so does their influence on retail. Download the new insideHPC special report, courtesy of Dell and NIVIDA, to learn more about how machine and deep learning is revolutionizing the retail industry. 

Consumer GPUs Power 2 Petaflop Deep Learning Cluster at ASTRON

Today ClusterVision announced the successful deployment of a new high performance computing GPU cluster system for the Netherlands Institute for Radio Astronomy (ASTRON). “By utilizing the deep learning capabilities of the GPU cluster, the telescopes will be able to detect pulsar flashes with much greater accuracy through self-learning. In the past, ASTRON scientists had to manually detect and input pulsar patterns. With deep learning, ARTS does it for them.”

Using the Titan Supercomputer to Accelerate Deep Learning Networks

A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the laboratory’s Titan supercomputer.

How AI is Reshaping HPC

Karl Freund from Moor Insights gave this talk at SC17. “Researchers have begun putting Machine Learning to work solving problems that do not lend themselves well to traditional numerical analysis, or that require unaffordable computational capacity. This talk with discuss three primary approaches being used today, and will share some case studies that show significant promise of lower latency, improved accuracy, and lower cost.”

Adapting Deep Learning to New Data Using ORNL’s Titan Supercomputer

Travis Johnston from ORNL gave this talk at SC17. “Multi-node evolutionary neural networks for deep learning (MENNDL) is an evolutionary approach to performing this search. MENNDL is capable of evolving not only the numeric hyper-parameters, but is also capable of evolving the arrangement of layers within the network. The second approach is implemented using Apache Spark at scale on Titan. The technique we present is an improvement over hyper-parameter sweeps because we don’t require assumptions about independence of parameters and is more computationally feasible than grid-search.”

Transforming Financial Services with AI Technologies

As the financial industry increasingly realizes the impact of faster analytical insights on overall business strategy, artificial intelligence techniques like machine learning are permeating nearly every industry. Download the new white paper from HPE and NVIDIA to learn how to transform financial services with AI technologies, as well as drive business value with NVIDIA GPU-accelerated deep learning. 

Video: Deep Learning for Science

Prabhat from NERSC and Michael F. Wehner from LBNL gave this talk at the Intel HPC Developer Conference in Denver. “Deep Learning has revolutionized the fields of computer vision, speech recognition and control systems. Can Deep Learning (DL) work for scientific problems? This talk will explore a variety of Lawrence Berkeley National Laboratory’s applications that are currently benefiting from DL.”