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Edge Computing Proves Critical for Drilling Rigs, Pipeline Integrity

This is the third entry in a five-part insideHPC series that takes an in-depth look at how machine learning, deep learning and AI are being used in the energy industry. Read on to learn how edge computing is playing a role in operating drilling rigs, ensuring pipeline integrity and more. 

Energy Companies Embrace Deep Learning for Inspections, Exploration & More

This is the second entry in a five-part insideHPC series that takes an in-depth look at how machine learning, deep learning and AI are being used in the energy industry. Read on to learn how energy companies are embracing deep learning for inspections, exploration and more. 

Opportunities Abound: HPC and Machine Learning for Energy Exploration

The is the first entry in a five-part insideHPC series that takes an in-depth look at how machine learning, deep learning and AI are being used in the energy industry. Read on to find out how machine learning is driving energy exploration. “Any tool that reduces the time needed to understand where the deposits are located can save a company millions of dollars.”

How Deep Learning Tech Can Contribute to Success

Frameworks, applications, libraries and toolkits—journeying through the world of deep learning can be daunting. If you’re trying to decide whether or not to begin a machine or deep learning project, there are several points that should first be considered. This is the fourth article in a five-part series that covers the steps to take before launching a machine learning startup. This post covers how deep learning is contributing to success across a variety of industries.

Machine Learning in Energy: A Hot Spot in Seismic Processing

Artificial intelligence and machine learning, based on widely available hardware and novel software techniques, give energy exploration companies the confidence to pinpoint drilling locations, resulting in lower costs.  Download the new insideHPC special report, courtesy of Dell EMC and Nvidia, to learn how HPC technology is being used for energy exploration, ranging from drilling and well completion to modeling oil-refining strategies. 

Inference systems: The 2nd Piece of the Deep Learning Puzzle

Frameworks, applications, libraries and toolkits—journeying through the world of deep learning can be daunting. If you’re trying to decide whether or not to begin a machine or deep learning project, there are several points that should first be considered. This is the third article in a five-part series that covers the steps to take before launching a machine learning startup. This article explores the role of inference systems in machine learning.

Unified Deep Learning Configurations and Emerging Applications

This is the final post in a five-part series from a report exploring the potential machine and a variety of computational approaches, including CPU, GPU and FGPA technologies. This article explores unified deep learning configurations and emerging applications. 

What Next? Entering the World of Machine Learning

Frameworks, applications, libraries and toolkits—journeying through the world of deep learning can be daunting. If you’re trying to decide whether or not to begin a machine or deep learning project, there are several points that should first be considered. This is the final article in a five-part series that covers the steps to take before launching a machine learning startup. This article provides a variety of resources to employ when first exploring machine learning. 

Exploring the Possibilities of Deep Learning Software

This is the second post in a five-part series from a report that explores the potential of unified deep learning with CPU, GPU and FGPA technologies. This post explores the possibilities and functions of software for deep learning.

Why Use Containers for HPC on the NVIDIA GPU Cloud?

“Containers just make life easy. So one of the things that people have issues with running bare metal is from time to time their libraries change, maybe they want to try the new version of CUDA, the new version of cuDNN, and they forget to simlink it back to the original path. If you have packaged your app into a container, it’s the same every time.”