Netweb Technologies India Limited (Netweb), the Indian OEM in high-end computing, announced that it is now a manufacturing partner for the NVIDIA Grace CPU Superchip and GH200 Grace Hopper Superchip MGX server designs. Netweb will build and produce more than ten server variations under its Tyrone range of AI systems meant for a wide range of AI and high-performance computing/supercomputing applications.
With NVIDIA MGX, Netweb’s AI systems will target complex workloads of HPC, data science, large language models, edge computing, enterprise AI, and design and simulation, the company said. The product range will also support handling a range of simultaneous workloads such as AI training, inference, and 5G on a single system. At the same time, the designs ensure seamless upgrades for upcoming hardware generations.
“Netweb has been at the forefront of driving high-end technology products for the Make-in-India initiative. NVIDIA is a leader in AI products and solutions, helping the world solve diverse problems efficiently. India possesses the immense skill, requirement, and appetite to capitalize on AI and its growth. The initiative of Make-in-India by NVIDIA to support the PMO vision is a great beginning. It will bring locally manufactured cutting-edge technologies at par with global standards,” said Sanjay Lodha, Chairman and Managing Director of Netweb.
“With artificial intelligence touching almost all businesses and industry verticals, building the right AI infrastructure at the right cost is one of enterprises’ greatest challenges,” said Vishal Dhupar, Managing Director for South Asia at NVIDIA. “NETWEB’s Tyrone AI systems based on NVIDIA MGX will help tackle these challenges and give flexibility to enterprises for a variety of applications, including generative AI, speech analytics, text analytics, automation and more.”
Netweb’s AI systems with NVIDIA MGX will give a boost to the country’s ‘Make in India’ mission. At the same time, the local manufacturing of systems will build a local ecosystem to better address the demands around AI and accelerated computing applications of both government and private enterprises, it said.