PM Narendra Modi inaugurates three Param Rudra supercomputing systems

Says India has taken significant steps towards self-reliance in computing

Prime Minister Narendra Modi on Thursday virtually inaugurated three Param Rudra supercomputers and High Performance Computing (HPC) systems for weather and climate research.

The supercomputers, developed indigenously under the National Supercomputing Mission (NSM) and at a cost of about Rs 130 crore, will be deployed in Pune, Delhi, and Kolkata to support high-performance scientific research and development.

“With the Param Rudra supercomputers and HPC system, India takes significant steps towards self-reliance in computing and driving innovation in science and technology. In the era of digital revolution, computing capacity is becoming synonymous with national capability,” he said in his address.

Modi also spoke about the direct dependence on science and technology, and computing capabilities for opportunities in research, economic growth, and other domains. 

 

He also inaugurated ‘Arka’ and ‘Arunika’, a High-Performance Computing (HPC) system tailored for weather and climate research, and interacted with scientists and researchers involved in the development of the infrastructure.

Union Minister for Electronics & Information Technology Ashwini Vasihnaw also attended the virtual inauguration.

The Giant Meter Radio Telescope (GMRT) in Pune will leverage the supercomputer for research on Fast Radio Bursts (FRBs) and other astrophysical phenomena.

In Delhi, the Inter-University Accelerator Center will focus on advancing research in physical sciences and nuclear physics, while S N Bose Center in Kolkata will use it for advanced courses in physics, cosmology, and earth sciences. 

The HPC system tailored for weather and climate research, is launched under a total project cost of Rs 850 crore, and is located at the Indian Institute of Tropical Meteorology (IITM) in Pune and the National Center for Medium-Range Weather Forecast (NCMRWF) in Noida.

These high-resolution models are expected to enhance the accuracy and lead time of predictions related to tropical cyclones, heavy precipitation, thunderstorms, hailstorms, heat waves, droughts, and other critical weather phenomena.