+49 421 40 966 0 oder per Mail
GPU-accelerated computing is the use of GPUs in conjunction with CPUs to significantly accelerate HPC, deep learning, analysis and engineering applications. Compute-intensive application parts are run on the GPUs and the remaining tasks are processed by the CPUs.
GPU accelerators provide extreme computing power to energy-efficient data centers in research facilities, universities and large, small and medium-sized enterprises around the world. They play a major role in accelerating AI applications in platforms ranging from Machine and Deep Learning, Data Analytics, Rendering, etc.
A simple way to understand the difference between a GPU and a CPU is to compare how they handle tasks. A CPU consists of a few cores optimized for sequential serial processing. A GPU has a massively parallel architecture consisting of thousands of smaller, more efficient cores designed to handle multiple tasks simultaneously.