There is an ever increasing demand of computational power in scientific or industrial research. At the same time, high-performance computing systems consume very much power.
The deployment of accelerator technology for additional and specialized computing hardware components constitutes a big leap in computational power while, at the same time, lowering energy-consumption significantly.
GPUs - Graphics Processing Units
CPUs - Central Processing Units
For building future Exascale high-performance computing systems, a low energy consumption is key. Even many of the current TOP500 list supercomputing systems possess accelerators as a core ingredient, thus achieving their excellent performance.
Graphics Processing Units (GPUs) as well as specialized x86-based many-core systems may act as accelerators.
These co-processors are able to perform certain parts of the scientific calculation more efficient. Tasks that are computationally intense and highly parallelized are not executed on the CPU, the system’s main processor, but are transferred to the co-processor. This way not only a significant reduction of time-to-result is gained, but also the energy consumed is lowered.
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UNLIMITED COMPUTING POWER FOR UNLIMITED POSSIBILITIES
Modern data centers are key to solving some of the world’s most important scientific and big data challenges using high performance computing (HPC) and artificial intelligence (AI).
The innovative NVIDIA-Pascal™-architecture is specifically designed for computer systems, which can learn, see and simulate our world – a world which is demanding more and more computing power.
Artificial intelligence for self-propelled cars. Predictions for our climate. New medicine for cancer treatment. For some of the most important challenges we must urgently find a solution, which require enormous computing efforts, though. Today‘s computing centres rely on many inter-connected standard computing nodes. This, however, slows performance, which would be necessary for important calculations in the areas High Performance Computing (HPC) and Hyperscale.
Pascal is the most performant computing architecture in a graphics processor ever developed. It turns an ordinary computer into a supercomputer with a performance unrivaled to date. Pascal delivers a performance of more than 5 TeraFLOPs at double the speed for HPC-calculations. In the field of Deep Learning a Pascal-powered system reaches a performance jump by more than 12 times current graphics processor architectures would, when conditioning neural networks.
More than 400 HPC-applications, in particular 9 out of the 10 most important ones, and all Deep-Learning-Frameworks have been accelerated already. Each HPC-customer can therefore use accelerating graphics processors in their computing centre.
Find out if your application is being accelerated by NVIDIA® GPUs. See the link below: read more
Usage of a resource-intensive application ...
... on a cluster in the data center.