New Zealand’s strongest supercomputer for synthetic intelligence functions has been put in on the University of Waikato by Nvidia companion Fujitsu.
The Nvidia DGX A100 is the primary pc of its variety in New Zealand and the world’s most superior system for powering common AI workloads, the University stated.
It can quickly and effectively course of large quantities of information, enabling machine studying and synthetic intelligence that may remedy complicated issues.
Machine studying makes use of algorithms to discover enormous information units and create fashions that may be skilled to recognise patterns, facial expressions and spoken phrases — or to seek out anomalies comparable to bank card fraud.
One of the primary initiatives the pc is getting used for is to coach fashions that may study and classify New Zealand’s vegetation and animals, primarily based on a publicly accessible database of a couple of million pictures.
The large computing engine matches into one quarter of a computing rack within the University’s primary server room, powered by processors designed particularly to speed up the distinctive wants of AI workloads.
Nvidia’s Mellanox InfiniBand networking ensures information is quickly provided to the system.
The DGX A100 has eight A100 GPUs containing 40GB of reminiscence every for a complete of 320 GB of GPU reminiscence.
“AI is a powerful tool that enables researchers to achieve scientific breakthroughs and discoveries on areas such as climate change and biodiversity, which are critically important to New Zealand and the world,” stated Sudarshan Ramachandran, nation supervisor of Nvidia.
Professor Albert Bifet stated college students and researchers might take months, and even years, to course of the information wanted to create fashions just like the one they’re engaged on if that they had to make use of extra conventional computing.
“This pc will enable our researchers to course of that information in a matter of days. It will allow them to achieve insights and progress their analysis at an unprecedented scale,” he said.
The purchase was made possible through income from the sale of commercial licenses to the Weka software, a suite of Java-based software tools for machine learning and data mining that the machine learning group at the University has been developing for more than 20 years.
“Being able to use the funds from Weka, which has proved so successful, is a real win for us,” said professor Bifet.
“Weka software has been bought by several large international IT companies. It shows the success and depth of expertise we have here and has enabled us to reinvest back into our group.”