Numerous researches on implementation of Artificial Intelligence defining its capability in transforming the world, has been carried since 1950s. It continues to nurture importance through increased adoption of digital technology around various industries.
NVIDIA AMPERE architecture to Graphical Processing Units has become a breakthrough invention to compute-intensive applications in training modules, genomics, video analytics, data analysis & 5G Services. Data being the crux of the Fourth Industrial Revolution, the need for real-time accessing and data processing necessitates GPU accelerated cloud computing.
NVIDIA DGX A100 TENSOR CORES
The latest NVIDIA Ampere Architecture made a revolutionary change in the data-centric processing requirements by unveiling its new multi-instance GPU virtualization particularly beneficial to cloud service providers.
NVIDIA is most common among the Gamers providing graphical processing improvements supporting next-gen gaming inclusive of the advanced technologies like: Ray-Tracing. However, the recently released DGX A100 is not for gamers and is meant only for Data centers. Eight such A100 GPUs combined with the Third-Generation NVLink, it ensures high-speed interconnection providing maximum bandwidth for communication across the GPUs. DGX A100 would be replacing previously used Tesla V100 & DGX Systems to power the supercomputer in processing huge amounts of data all around the world.
Take a quick look into how Artificial Intelligence influences various sectors in modifying approach to complete Digitalisation. Processing cores plays a vital role in transforming machine learning to a whole new level. Imagine a normal human being performing several tasks all at a time like: typing on a keyboard, thinking, clicking a mouse at intervals and also reading on screen. Ability to process multiple tasks at a time is known as multi-tasking and such is not the case for machines as they require time to process different tasks and perform according to the set rules. Machine Learning aims to process data and train them so that the artificial neural capability of a machine increases to perform like a human being. Tensor Cores adds immediate path for faster training and greater deep learning performance with the ability of matrix multiplication in real-time basis.