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Commercial Industries
Commercial Industries
GPU technology is transforming a range of commercial industries—from finance and consumer-product development to aircraft design and entertainment—by improving the efficiency of processes and enabling the development of new products and services that were not previously possible.
The GPU allows manufacturers to replace physical modeling with simulations. This can dramatically speed time to market and reduce costs. It enables designers to easily experiment with materials and design to find the most cost-effective and ecologically responsible ways to solve problems.
The industries highlighted below are just a few examples of where the GPU has had deep impact.
Product Design
NVIDIA technology accelerates design and development cycles for everything from cars to shampoo. Mechanical design applications that use computational fluid dynamics to simulate the interaction of surfaces and fluid flow are seeing performance double through the use of NVIDIA Tesla GPUs. Manufacturers can run tests utilizing wind tunnels or crash-simulation software, for example, which previously required physical models.GPUs are also accelerating the computations that lead to the development of new drugs and personal care products. For instance, in initiatives that can help discover more environmentally sound detergents, researchers are investigating the cleaning properties of different surfactant molecules by running simulations powered by NVIDIA Tesla GPUs.
Improving the Quality of Consumer Products
Improving the cleaning power of shampoos and liquid detergents and making them more environmentally friendly is as much a computer problem as it is a balance of chemicals. By harnessing the power of NVIDIA® Tesla™ GPUs, researchers at Temple University are developing a computer simulation model which provides companies like Procter and Gamble with a fast, cost effective and accurate tool for research and development of surfactant molecules. Hear from the team at Temple University.
Improving the cleaning power of shampoos and liquid detergents and making them more environmentally friendly is as much a computer problem as it is a balance of chemicals. By harnessing the power of NVIDIA® Tesla™ GPUs, researchers at Temple University are developing a computer simulation model which provides companies like Procter and Gamble with a fast, cost effective and accurate tool for research and development of surfactant molecules. Hear from the team at Temple University.
Watch the video here: http://www.youtube.com/embed/0DhHUMrtmPc
Automotive Industry
NVIDIA technology has been used in the automotive industry for more than a decade. NVIDIA Quadro workstations are used to design vehicles, engines and other body components. GPU-accelerated design allows manufacturers to build computer models and fine-tune features without having to create physical models, reducing both the amount of materials used and the time spent to build them. NVIDIA Tesla technology, based on the CUDA parallel processing architecture, allows for the development of high-performance computing applications such as crash simulation and computational fluid dynamics. And NVIDIA’s line of Tegra mobile processors is being used to help make cars safer and through digital instrument clusters and driver-assistance systems.Case Study: Speeding Pharmaceutical Research
Discovering a new drug is a complex and laborious task. Biochemists have to try millions of compounds before they can figure out which ones are effective against a particular virus or bacteria or which cause a desired reaction in the human body. To speed this process, researchers turn to computer simulations, which historically have required supercomputers, which are, unfortunately, in short supply. Today NVIDIA GPUs can accelerate life sciences applications by an order of magnitude allowing researchers to conduct work on desktop computers with supercomputing capabilities. In spring of 2010, AMBER 11, one of the most widely used applications for biochemists and others involved in molecular dynamics research, launched a version optimized for GPUs. AMBER 11 lets bioscientists harness the power of a supercomputer on their desktop PC, speeding up this software tool by up to a 100-fold over that on a traditional CPU-based server.
“With GPUs, we can now do most of our work at the desktop and that changes everything.”
-- Dr. Ross Walker, research professor at the San Diego Supercomputer Center, at the University of California, San Diego, and a principle AMBER contributor
National Security and Defense
NVIDIA GPUs are helping military, law enforcement, and even local municipalities, improve security by providing the processing power needed to extract meaningful information from radar, sensor, sonar, video and infrared sources.In the case of video processing, GPUs are being used in a number of image-enhancement applications that reveal previously hidden data in satellite images. Video surveillance is another area in which GPUs are helping to improve security and defense. Thanks to the power of parallel processing, it is now possible to use real-time stabilization and enhancement techniques to clean up video feeds. Whether these feeds come from drones on the battlefield or security cameras on the streets, critical information from video surveillance is captured in time to take action.
On the ground in local municipalities, our GPUs are helping state and local governments quickly and cost-effectively unlock the practical value of data from sophisticated geographic information systems (GIS) software, which analyzes satellite imagery by applying complex image processing filters. By speeding up these compute-intensive calculations, GPUs help local authorities in everything from disaster planning and prevention to improving 911 response times.
Oil and Gas Exploration
The GPU allows oil and gas exploration to be undertaken in a more efficient and environmentally sensitive manner. By enabling oil companies to find oil reserves more precisely, the GPU can minimize the impact on the earth while maximizing extraction yields. Tesla GPU-based clusters enable much higher performance than CPU-only clusters. Thus, exploration efforts can deploy smaller, more computationally dense clusters which use less energy and still meet the ever-increasing demand of applications such as seismic processing.GIVE US YOUR FEEDBACK
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