Companies typically purchase large amounts of hardware in an attempt to reduce runtimes of computing tasks; multiple servers that occupy a lot of space and generate additional costs associated with housing, operating and maintaining this equipment.

In a case where the user's software can run on only one computer at a time, companies are then constrained by the available resources in that particular machine.

The use of GPUs to address general-purpose computing tasks is an emerging competitive technology in fields where users engage in intensive computer modeling, such as seismic data processing, biomedical imaging and electromagnetic simulation. Instead of a computer's CPU handling the data processing required to complete the task, the GPU is used. Graphics cards possess much greater computational parallelism than single or multi-core CPU computing platforms. For example, while today's Intel or AMD CPUs can perform four or eight tasks in parallel, today's GPUs can perform 128 or more tasks in parallel.

"Our technology requires a tremendously computer-intensive engine to render three dimensional images," said Dr. Hagness. "Acceleware's hardware solution enables us to complete our computations and generate images in hours instead of days. Minimizing the time required to generate complex images is fundamental to helping save lives and reduce suffering."

Dr. Susan C Hagness, Professor
Department of Electrical and Computer Engineering
University of Wisconsin-Madison
Author, Computational Electrodynamics