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Exploring the ROI Potential of GPU Supercomputing

The growing prevalence of artificial intelligence and machine learning is putting heightened focus on the quantities of data that organizations have recently accumulated — as well as the value potential in this data. Companies looking to gain a competitive edge in their market are turning to tools like graphic processing units – or GPUs – to ramp up computing power. That’s according to a new white paper from Penguin Computing.

How Oil and Gas Firms Can Create Competitive Advantage with GPU-Accelerated Computing

Previously, oil and gas firms relied on costly, central processing unit (CPU) intensive infrastructure to manage data usage and analysis speed. GPUs for oil and gas firms have given rise to a new set of opportunities. Download the new report from Penguin Computing outlines how the adoption of GPU-accelerated computing can offer oil and gas firms significant return on investment (ROI) today and pave the way to gain additional advantage from future technical developments.

The ROI of GPU-Accelerated Computing

Previously, many organizations trying to analyze big data relied on costly, central processing unit (CPU) intensive infrastructure. With graphics processing unit (GPU)-accelerated computing, though, the information technology (IT) industry has a new, more effective, more efficient alternative. Download the new white paper from Penguin Computing that explores how adoption of GPU-accelerated computing can offer a significant return on investment (ROI) today and pave the way to gain additional advantage from future technical developments.

GPUs and Flash in Radar Simulation and Anti-Submarine Warfare Applications

In this week’s Sponsored Post, Katie Garrison, of One Stop Systems explains how GPUs and Flash solutions are used in radar simulation and anti-submarine warfare applications. “High-performance compute and flash solutions are not just used in the lab anymore. Government agencies, particularly the military, are using GPUs and flash for complex applications such as radar simulation, anti-submarine warfare and other areas of defense that require intensive parallel processing and large amounts of data recording.”

GPU Accelerated Servers for Deep Learning Applications

Applications such as machine learning and deep learning require incredible compute power, and these are becoming more crucial to daily life every day. These applications help provide artificial intelligence for self-driving cars, climate prediction, drugs that treat today’s worst diseases, plus other solutions to more of our world’s most important challenges. There is a multitude of ways to increase compute power but one of the easiest is to use the most powerful GPUs.

GPU computing with The Dell PowerEdge C4130

This white paper describes the system architecture and performance characterization of the PowerEdge C4130. The C4130 offers a highly configurable system design and ultra-high accelerator/coprocessor density. The combination of these factors have resulted in substantial performance improvement in for a number of industry standard HPC benchmarks and applications.