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High-Performance Computing (HPC) is an important technology that enables the operation of AI servers. AI applications, especially deep learning models and large-scale neural networks, require vast processing capabilities to process large datasets and perform complex calculations. High-Performance Computing is a foundational level technology for AI servers. HPC enables the raw processing power to perform high-performance tasks, such as 3D imaging and loT processing, which also include AI model training as well as scientific simulations that can be executed by a server using advanced processors or GPUs and large-scale storage capacities. Servers from MSI, ASUSTeK Computer Inc., IBM, and Dell Inc., that support scalable architectures, high-throughput networking, and accelerators with massive datasets and complex calculations at the most incredible velocities, have been optimized by HPC. Servers that will be built to ensure support for such a wide area of application will be the autonomous vehicle, healthcare, media production, and industrial automation. In response to high demand from customers for enhanced computing capabilities and efficiency, companies have started to bring AI servers that are embedded with high-performance computing abilities. It is expected that these systems will be designed to be able to address the large and resource-heavy workloads of modern applications of AI. For instance, in May 2024 MSI declared its new optimized server platforms for HPC and AI applications. Its products incorporate AMD processors as well as 5th Gen Intel Xeon Scalable processors. These seek to meet the demand for computing power and dense deployment driven by the rising use of AI through better efficiency, using liquid cooling technologies, among others.
Machine learning segment by application will hold the largest share in the forecasted timeline.
Machine learning holds the largest market share in the AI server market. It is the core driver for AI applications fueling the demand for high-performance AI servers specifically tailored to address complex computational needs of training and deploying machine learning models. These AI servers have dominated the market by offering optimized configurations and highly sophisticated hardware components such as GPUs, TPUs, and custom ASICs to speed up ML workflows. GPUs are especially efficient at training large deep neural networks due to their capacity to conduct massive parallel processing operations like matrix multiplications that are crucial for processing complex datasets quickly and accurately. TPUs, which Google designed specifically for tensor-based operations, add further acceleration by enabling fast processing and the scaling of ML models which are used for large-scale applications. Further, the custom ASICs built into many AI servers are tailored for ML tasks allowing efficiency gains and the ability for organizations to meet up with the burgeoning demands for AI-driven insights across fields such as finance, healthcare and autonomous systems.
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North America region will hold the largest share in the forecasted timeline.
North America holds the largest market share in the AI server market. The region has been highly advanced in artificial intelligence implementation in various industries such as healthcare, finance, technology, retail, and manufacturing sectors. The presence of various AI server manufacturers in the region such as, NVIDIA Corporation (US), Dell Inc. (US), Hewlett Packard Enterprise Development LP (US), IBM (US), and Cisco Systems, Inc. (US) is complementing the growth of the market in North America. Along with this, the growing trend of cloud computing has radically increased the economic impact of data center investments made by leading service providers such as Amazon Web Services, Inc. (AWS) (US), Meta (US), Google (US), and Microsoft (US). The expansion of emerging startups in countries like US further fuels the innovations in AI servers. Concentrating on harnessing the potential of artificial intelligence for economic growth, a better customer experience, and solution of complex challenges, North America remains the hub of innovation and entrepreneurship in artificial intelligence and drives the demand for AI servers in the region.
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