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市场调查报告书
商品编码
1662753
2030 年人工智慧增强型 HPC 市场预测:按组件、部署、组织规模、计算类型、最终用户和地区进行的全球分析AI Enhanced HPC Market Forecasts to 2030 - Global Analysis By Component (Hardware, Software and Services), Deployment (Cloud and On-premises), Organization Size, Computing Type, End User and By Geography |
根据 Stratistics MRC 的数据,全球 AI 增强 HPC 市场预计在 2024 年达到 29.5 亿美元,到 2030 年将达到 56.4 亿美元,预测期内的复合年增长率为 11.4%。将人工智慧整合到传统 HPC 系统中以提高运算效率、可扩展性和高级解决问题的能力,称为 AI 增强 HPC。透过利用 AI 演算法、机器学习模型和神经网络,AI 增强型 HPC 可以显着加快资料处理和分析速度。它还可以实现更准确、更快速的模拟、预测建模和即时决策。这种人工智慧与高效能运算的结合在医学、工程、金融和气候变迁研究等大型资料集需要快速复杂运算的领域尤其有效。
根据高效能运算-人工智慧领导组织(HALO)的数据,高效能运算-人工智慧市场正在快速成长,预计到2022年全球资料中心支出将达到620亿美元,其中179亿美元将来自推动机器学习和深度学习的超大规模公司。
即时分析的需求
在我们快节奏的世界中,快速决策至关重要。由人工智慧驱动的 HPC 可以快速且有效率地处理大量资料,实现即时分析,因此企业可以立即对趋势和事件做出反应。人工智慧广泛应用于自动驾驶汽车等产业,即时处理感测器资料,确保高效、安全的导航。由人工智慧 HPC 系统进行的即时市场资料分析可帮助投资者做出明智的决策。此外,即时患者资料监测可以帮助医疗保健等行业实现更快的诊断和个人化治疗。
维护和整合的复杂性
将 AI 增强型 HPC 系统融入现有IT基础设施是一个困难且耗时的过程。除了复杂的演算法之外,这些系统还需要特定的硬体和软体设置,而这些设置可能无法在旧系统上运行。人工智慧增强型 HPC 系统的复杂性因其管理和维护通常需要高素质人员而进一步加剧。确保跨多个部门和职能的顺利整合和营运对于组织来说可能是一个挑战。此外,缺乏技术专业知识(尤其是人工智慧和 HPC 技术)也会阻碍这些系统的部署和维护。
永续性和气候建模的发展
人工智慧驱动的 HPC 对于解决永续性和气候变迁等全球问题至关重要。人工智慧驱动的 HPC 系统透过模拟气候模型和分析大量环境资料,帮助科学家了解天气模式、预测气候变迁并评估其对生态系统的影响。可再生能源技术的设计、能源分配的最佳化以及环境政策的评估都是使用 HPC 驱动的模拟进行的。此外,随着政府和组织增加对人工智慧和高效能运算的投资以实现永续性目标,参与环境研究、清洁能源和永续性创新的公司将面临许多机会。
获得技术人才的机会有限
阻碍人工智慧 HPC 市场扩张的关键问题之一是人工智慧、HPC、资料科学和机器学习领域合格人才的短缺。人工智慧和高效能运算需要高阶专业知识,尤其是在管理大量资料、创建演算法、训练复杂模型和最大化运算能力方面。这些领域对专家的需求日益增长,造成了人才缺口,这不仅推高了人事费用,而且限制了企业部署和维护 AI 增强型 HPC 系统的能力。此外,大学和其他教育机构无法满足合适的培训课程和课程的需求,也加剧了人才短缺的情况。
随着产业和研究机构寻求先进的运算能力来应对全球健康危机,COVID-19 疫情显着加速了对人工智慧增强型高效能运算 (HPC) 的需求。快速疫苗开发、流行病学建模和医学资料分析的需求导致人工智慧模拟和预测分析的普及度不断提高。这使得人们越来越意识到 HPC 系统的功能。此外,各行各业向远距工作和数位转型的转变导致对云端基础的AI 增强型 HPC 解决方案的依赖性增加。疫情促使云端基础的HPC 迅速普及,并增加了对人工智慧研究的投资,同时也凸显了人工智慧在解决紧迫问题方面发挥的关键作用以及市场对强大基础设施的依赖。
预计预测期内硬体部分将成为最大的部分。
预计预测期内硬体部分将占据最大的市场占有率。这主要是由于针对 AI 工作负载进行调整的专用处理器、GPU 和 TPU 等复杂硬体元件的需求不断增长。这些硬体进步对于有效处理大型资料集、深度学习模型和复杂的人工智慧演算法至关重要。随着人工智慧的应用不断扩大,尤其是在医疗保健、汽车和金融服务等行业,对能够管理运算密集型任务的高效能硬体的需求正在推动这一市场的成长。此外,硬体架构的发展和处理器中人工智慧特定功能的加入对硬体产业提出了进一步的要求。
预计云端运算领域在预测期内将实现最高复合年增长率
预计云端运算领域将在预测期内实现最高的成长率。这种扩展是由对云端基础的解决方案所提供的可扩展、适应性强且价格合理的运算能力的日益增长的需求所推动的。云端平台透过为企业提供对高效能运算资源的按需存取来支援 AI 工作负载的运算密集型需求。对于希望将人工智慧与高效能运算结合的企业来说,云端运算已经成为热门选择,因为它消除了与内部部署基础设施相关的前期投资,并且可以根据需求快速扩大或缩小规模。
预计预测期内北美地区将占据最大的市场占有率。该地区的优势在于各行各业采用了尖端的高效能运算解决方案、对人工智慧研发进行了大量的投资、以及知名科技公司的强大影响力。北美凭藉其完善的IT基础设施处于人工智慧主导创新的前沿,该基础设施使用 HPC 处理製造业、医疗保健、金融和汽车等行业的复杂计算任务。
预计预测期内亚太地区将呈现最高的复合年增长率。中国、印度、日本和韩国等国家的快速技术进步和数位转型正在推动这一成长。由于对人工智慧、云端运算和超级运算基础设施的投资不断增加,亚太地区正在成为 HPC 市场的主要参与企业。此外,该地区製造业、医疗业和汽车业等各行业对人工智慧应用的需求日益增长,加上政府鼓励技术创新的项目,都在加速人工智慧增强 HPC 解决方案的采用。
According to Stratistics MRC, the Global AI Enhanced HPC Market is accounted for $2.95 billion in 2024 and is expected to reach $5.64 billion by 2030 growing at a CAGR of 11.4% during the forecast period. The integration of artificial intelligence with conventional HPC systems to provide increased computational efficiency, scalability, and sophisticated problem-solving capabilities is known as AI-enhanced HPC. AI-enhanced HPC can greatly speed up data processing and analysis by utilizing AI algorithms, machine learning models, and neural networks. Moreover, this allows for more accurate and faster simulations, predictive modeling, and real-time decision-making. In fields like healthcare, engineering, finance, and climate research, where large datasets necessitate quick, intricate calculations, this combination of AI and HPC has a particularly significant impact.
According to the HPC-AI Leadership Organization (HALO), The HPC-AI market has taken off, with $62 billion in worldwide data center spending in 2022, including a whopping $17.9 billion from Hyperscale companies who drive machine learning and deep learning.
Demand for analytics in real time
In the fast-paced world, making decisions quickly is essential. Businesses can react to trends and events as they occur owing to AI-enhanced HPC, which processes enormous volumes of data quickly and efficiently to enable real-time analytics. AI is used extensively in industries such as autonomous vehicles to process sensor data in real-time, guaranteeing efficient and safe navigation. Instantaneous market data analysis by AI-powered HPC systems aids investors in making well-informed decisions. Additionally, real-time patient data monitoring can result in more rapid diagnoses and individualized treatments in industries like healthcare.
Complexity of maintenance and integration
The process of incorporating AI-enhanced HPC systems into pre-existing IT infrastructures can be difficult and time-consuming. In addition to complex algorithms, these systems call for specific hardware and software setups that might not work with older systems. The complexity of AI-enhanced HPC systems is further increased by the fact that they frequently need highly qualified staff to manage and maintain them. Ensuring smooth integration and operation across multiple departments and functions can present challenges for organizations. Furthermore, deployment and maintenance of these systems may also be hampered by a lack of technical expertise, especially in AI and HPC technologies.
Developments in sustainability and climate modeling
AI-enhanced HPC is essential for tackling global issues like sustainability and climate change. AI-enhanced HPC systems are assisting scientists in better understanding weather patterns, forecasting climate shifts, and evaluating the effects of climate change on ecosystems by simulating climate models and analyzing enormous volumes of environmental data. Designing renewable energy technologies, optimizing energy distribution, and evaluating environmental policies are all being done with HPC-driven simulations. Moreover, businesses engaged in environmental research, clean energy, and sustainability innovations have a plethora of opportunities as governments and organizations invest more in AI and HPC to meet sustainability goals.
Restricted access to skilled talent
One significant issue that might impede the expansion of the AI-enhanced HPC market is the lack of qualified experts in AI, HPC, data science, and machine learning. Highly specialized knowledge is needed for AI and HPC, especially for managing massive amounts of data, creating algorithms, training intricate models, and maximizing computational power. A talent gap is being caused by the growing need for experts in these domains, which not only drives up labor expenses but also restricts an organization's capacity to implement and maintain AI-enhanced HPC systems. Additionally, the shortage is being made worse by universities and other educational institutions' inability to meet the demand for pertinent training programs and courses.
The COVID-19 pandemic significantly accelerated the demand for AI-enhanced High-Performance Computing (HPC) as industries and research institutions sought advanced computational power to tackle the global health crisis. AI-driven simulations and predictive analytics have increased in popularity due to the need for quick vaccine development, epidemiological modeling, and healthcare data analysis. This has increased awareness of HPC systems' capabilities. Furthermore, reliance on cloud-based AI-enhanced HPC solutions grew as a result of the shift to remote work and digital transformation across industries. The pandemic pushed for a quicker adoption of cloud-based HPC and increased investments in AI research, while also highlighting the crucial role AI plays in solving pressing issues and the market's reliance on robust infrastructure.
The Hardware segment is expected to be the largest during the forecast period
The Hardware segment is expected to account for the largest market share during the forecast period. The main cause of this is the rising demand for sophisticated hardware elements like specialized processors that are tailored for AI workloads, GPUs, and TPUs. These hardware advancements are essential for efficiently processing large datasets, deep learning models, and intricate AI algorithms. The demand for high-performance hardware that can manage computationally demanding tasks is fueling the growth of this market as AI applications continue to expand, particularly in industries like healthcare, automotive, and financial services. Moreover, the demand in the hardware industry is also being further increased by developments in hardware architecture and the incorporation of AI-specific capabilities in processors.
The Cloud segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the Cloud segment is predicted to witness the highest growth rate. The growing need for scalable, adaptable, and reasonably priced computing power-all of which cloud-based solutions offer-is what is driving this expansion. Cloud platforms support the computationally demanding requirements of AI workloads by giving businesses on-demand access to high-performance computing resources. The cloud is a popular option for businesses wishing to combine AI with high-performance computing because it can quickly scale up and down in response to demands without requiring the upfront capital investment associated with on-premises infrastructure.
During the forecast period, the North America region is expected to hold the largest market share. The region's dominance can be ascribed to the adoption of state-of-the-art high-performance computing solutions across a range of industries, the substantial investments made in AI research and development, and the strong presence of prominent technology companies. North America is at the forefront of AI-driven innovations owing to its well-established IT infrastructure, which uses HPC to handle complex computational tasks in industries like manufacturing, healthcare, finance, and automotive.
Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR. Rapid technological advancements and digital transformation in nations like China, India, Japan, and South Korea are driving this growth. The APAC region is becoming a major player in the HPC market as a result of rising investments in AI, cloud computing, and supercomputing infrastructure. Moreover, the region is adopting AI-enhanced HPC solutions more quickly due to the growing need for AI applications in a variety of industries, such as manufacturing, healthcare, and automotive, as well as government programs to encourage technological innovation.
Key players in the market
Some of the key players in AI Enhanced HPC market include Amazon Web Services, Inc., Fujitsu Limited, NEC Corporation, Cisco Systems, Inc., Google LLC, Arm Limited (SoftBank Group Corp.), Hewlett Packard Enterprise Development LP, Dell Technologies Inc., Samsung Electronics Co., Ltd., IBM Corporation, Advanced Micro Devices Inc. (AMD), Lenovo Group Limited, Huawei Technologies Co., Ltd., Intel Corporation and Microsoft Corporation.
In February 2025, Amazon Web Services (AWS) has entered into a new Whole-of-Government agreement with the Australian Government's Digital Transformation Agency (DTA) to offer access to cloud and emerging technologies. The agreement, initially set for a term of three years, builds on a previous arrangement signed in 2019, which aided in streamlining access to AWS services for all levels of government including local councils and public sector entities.
In September 2024, Fujitsu Limited and Stellar Science Foundation have entered into a partnership focused on discovering and supporting the next generation of scientific researchers and fostering the creation of cutting-edge research topics. Through this partnership, Fujitsu will contribute funds to SS-F to support the creation of a unique scientific research ecosystem that promotes collaboration and interaction among researchers.
In August 2024, NEC Corporation and Spectro Cloud have signed a strategic agreement to advance cloud-native innovation for organisations. With the exponential growth of modern, containerised applications inclusive of AI/ML workloads, real-time analytics and databases with various use cases across multiple industries, organisations need enterprise-grade capabilities to run these applications efficiently and securely.