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GPU Computing - XENON


GPU-accelerated computing is the use of a graphics processing unit (GPU) together with a CPU to accelerate scientific, engineering, and enterprise applications. Pioneered in 2007 by NVIDIA®, GPUs now power energy-efficient datacentres in government labs, universities, enterprises, and small-and-medium businesses around the world.

How Do Applications Accelerate with GPUs?

GPU-accelerated computing offers unprecedented application performance by offloading compute-intensive portions of the application to the GPU, while the remainder of the code still runs on the CPU. From a user’s perspective, applications simply run significantly faster. Many applications are already coded for GPU acceleration (download the list). For other custom coded applications, the NVIDIA® CUDA programming toolkit allows for minor changes to the code to take advantage of the massive parallelism that GPUs offer. The benefit is 100x increase in run time and processing of computationally intensive workloads.

XENON GPU Systems

XENON has been building GPU Computing solutions since 2008. We offer a full range of solutions, from managed services in the cloud to individual personal GPU based super computers, through to XENON GPU Clusters.