- Prime Minister Narendra Modi dedicated three PARAM Rudra supercomputers and two high-performance computing systems to the nation on 26 September 2024.
- These Computing systems were developed and manufactured indigenously under the National Supercomputer Mission and in line with the Make in India initiative
PARAM Rudra Supercomputers
- The PARAM Rudra Supercomputer, named after Lord Shiva, has been designed by the Centre for Development of Advanced Computing (C-DAC). It is based on the indigenous Rudra server developed by C-DAC and has a computing speed of one petaflops (1015 operations per second).
- C=DAC, under the Union Ministry of Electronics & Information Technology (MeiTY), started developing a High-Performance computing system in the country in 1988 and has developed a series of supercomputers called the PARAM series.
Dedicated PARAM Rudra Supercomputers
- The recently dedicated PARAM Rudra Supercomputers have been built at an estimated cost of Rs 130 crores.
- One PARAM Rudra Supercomputer has been installed at the Giant Metre Radio Telescope (GMRT) of the National Centre for Radio Astrophysics (NCRA) in Pune to conduct real-time searches for FRBs (Fast Radio Bursts) and pulsars.
- Another, installed at the Inter-University Accelerator Centre (IUAC) in Delhi, is expected to boost research and development in fields like material science and atomic physics.
- The PARAM Rudra supercomputer deployed at the S.N. Bose Centre in Kolkata will aid research and development in physics, cosmology, and earth sciences.
High-Performance Computing (HPC) system
- C-DAC has developed the recently inaugurated High-Performance Computing (HPC) by Prime Minister Narendra Modi for meteorological applications and to further research and development in weather and climate science.
- The High-Performance Computers named Arka and Arunika have been installed at the Indian Institute of Tropical Meteorology (IITM) in Pune and the National Center for Medium-Range Weather Forecast (NCMRWF) in Noida, Uttar Pradesh.
- The HPC is expected to strengthen and significantly enhance the accuracy and lead time of predictions related to tropical cyclones, heavy precipitation, thunderstorms, hailstorms, heat waves, droughts, and other critical weather phenomena.