world’s fastest
The power of supercomputers is often measured in flops, short for FLoating-point Operations per Second. It counts how many floating point calculations a machine can perform every second. The earliest supercomputers operated at about 1 flop. By 1964, the United States saw a machine capable of one million flops, or one megaflop. Today, Frontier leads the field, with peak performance surpassing 1.6 exaflops, which means more than a quintillion floating point operations per second.
Russia maintains a robust set of homegrown supercomputers and holds a notable position in the global Top500 rankings. Within this list, several Russian systems figure prominently, including Chervonenkis and Lyapunov on Yandex, Cristofari Neo and Christofari from Sber, Lomonosov-2 at Moscow State University, and GROM from MTS. The ongoing development and maintenance of these systems reflect the strength of Russia’s IT industry and its research ecosystem.
What are supercomputers used for? They serve a wide range of applications. High-powered machines can transform sectors such as financial analytics, engineering simulations, medicine, energy, government work, and defense. Building a domestic pipeline for producing machines with extraordinary computing power is viewed as a strategic priority for national science and industry.
Another field closely tied to supercomputing is artificial intelligence. The AI sector in Russia has shown rapid growth, with market estimates indicating substantial expansion and a measurable impact on the economy. By 2023, operating costs across companies were reduced through AI technologies, and projections for 2025 show continued, meaningful savings. The broader global market for high performance computing was forecast to exceed $56 billion in 2023, with healthy growth through 2028.
Experts in neural networks point out that artificial intelligence is already delivering benefits across many areas. They also caution that hype around AI may slow down real technical progress if not grounded in solid theory and rigorous development. A leading academic notes that the real challenge lies in education and governance; fully model-free approaches could undermine foundational knowledge in science and mathematics if not guided by disciplined study.
Technologies of the future
Institutes have begun organizing collaborative efforts that involve financial institutions to address real-world problems arising from AI deployment in agriculture and other sectors. Hackathons, where diverse teams work under time constraints to tackle defined problems, demonstrate that breakthroughs can come from unexpected participants, including highly capable students working alongside seasoned researchers. This dynamic shows that strong talent can emerge from varied backgrounds and levels of experience.
Neural networks are becoming a routine part of daily life for both professionals and everyday users. As data volumes grow, the demand for computing power rises correspondingly. Leaders have called for continued advancement in high performance computing to keep pace with emerging AI challenges and opportunities.
Ongoing progress in supercomputing is evident in new testing and deployment efforts. One research center recently completed a large-scale evaluation of a new system designed to solve complex problems across mathematics, physics, biology, and other sciences. The anticipated outcomes include accelerated research and deeper insights across multiple disciplines.
Forecasts suggest that more powerful machines will come online in the coming years, with several new supercomputers projected to be added by 2030. These developments are part of strategic plans drawn up by government and industry bodies to ensure a strong technological foundation and continued leadership in computational science. The roadmap emphasizes trusted infrastructure and coordinated efforts among industry partners to advance the hardware and software ecosystems that support AI and scientific discovery.
Overall, the push for greater computing power reflects a shared aim: to turn raw speed into practical breakthroughs. Through focused investment, international collaboration, and a steady stream of talented researchers, the trajectory points toward a future where supercomputing remains a cornerstone of innovation and competitiveness.