The global high-performance computing (HPC) market is expected to reach $87,31-billion by 2030 and is expected to grow at 7,2% CAGR from 2025 to 2030, according to a new study by Grand View Research.
High-performance computing can be categorised into high-performance technical computing (HPTC) and high-performance business computing (HPBC).
HPTC is highly used in the fields of science and engineering. It is particularly used by government agencies, defence agencies, educational and research institutions, and incumbents of the manufacturing industry among others. On the other hand, HPBC is suitable for applications such as gaming and fraud detection. Logistics companies and providers of financial services, among others, also opt for HPBC.
The rising popularity of HPC systems among manufacturing companies, government departments, and defence agencies is primarily driving the growth of the high-performance computing industry.
High-performance computing systems envisage a cluster of computers that can run long algorithms and solve complex problems and equations at high speeds and with higher accuracy than those offered by conventional computing systems.
Previously, HPC systems were used only by the navigation and aerospace industries. However, the diversification of the IT industry, growing adoption of cloud computing, continuous developments in artificial intelligence, and the rising need for business analytics are prompting various end-use industries to adopt HPC systems.
Data centres particularly require an architecture capable of processing large volumes of data. High-performance computing systems can ensure adequate computing power for these. Various other organisations also adopt HPC systems to process their data at higher speed, with higher accuracy in order to simplify their complex business procedures. Research and academic institutions have also started adopting HPC systems to maximise the computational efficiency required during the initial stages of research.
The high computational capabilities offered by HPC systems have paved the way to execute high-end research projects that were previously deemed impossible. As such, HPC systems can be helpful in several fields including computational biology, genetics, medicine, structural analysis, geophysics statistics, electromagnetism, nuclear physics, astrophysics, and mathematical modeling among others.
Similarly, the high efficiency offered by HPC systems can help researchers in undertaking research activities in various fields such as deep neural networks, human genome mapping and modeling, and artificial intelligence.
The vendors of high-performance computing systems are increasingly focusing on delivering enhanced solutions that can cater to diverse requirements. These solutions may include basic configurations and management tools that are easy to deploy and capable of adapting to changing workloads.
However, although the application portfolio of HPC systems continues to grow, the lack of awareness about HPC systems, budget constraints at small and medium-sized enterprises, and concerns such as data security remain hindrances to the growth of the high-performance computing industry.
Highlights of the HPC market report include:
- The on-premises segment dominated the market in 2024 driven by the need for greater control, security, and customisation in managing high-performance workloads.
- The servers segment dominated the market and accounted for revenue share of over 32% in 2024 driven by the rising demand for high-speed and high-capacity computing infrastructure to support the increasing complexity of data-intensive workloads.
- The government and defence segment dominated the market in 2024 driven by the need for advanced data processing, national security, and technological competitiveness.
- The North America high-performance computing market dominated the global market and accounted for a revenue share of 41,6% in 2024 driven by the presence of a large number of leading technology companies and research institutions that demand cutting-edge computational power.