The report "Data Center Accelerator Industry by GPU, CPU, FPGA, ASIC, Training, Inference, Cloud Data Center, Enterprise Data Center, IT & Telecom, Healthcare, BFSI, Government, Energy, Automotive and Retail & E-commerce - Global Forecast to 2030" The data center accelerator market is expected to be valued at USD 170.81 billion in 2025 and USD 372.68 billion by 2030, growing at a CAGR of 16.9% from 2025 to 2030. Key drivers for the data center accelerator market include the surging demand for high-performance computing to support artificial intelligence, machine learning, and big data analytics. Accelerators such as GPUs, FPGAs, and ASICs enhance processing speed, energy efficiency, and workload optimization, enabling advanced cloud and edge applications. Rising hyperscale data center investments and the growing need for low-latency computing in sectors such as BFSI, healthcare, and autonomous systems further fuel adoption. Additionally, innovations in chip design and integration strengthen market growth.
By processor type, the ASIC segment is expected to
register the highest CAGR during the forecast period.
The ASIC segment is projected to register the
highest CAGR in the data center accelerator market during 2025–2030, driven by
its superior performance efficiency, scalability, and workload optimization
capabilities. Application-specific integrated circuits (ASICs) are
purpose-built to handle specific computational tasks, such as AI model
training, deep learning inference, and high-frequency trading, delivering
faster processing speeds and lower power consumption than general-purpose
processors. As hyperscale data centers and cloud service providers increasingly
prioritize energy efficiency and performance-per-watt, ASICs are becoming a
preferred solution for accelerating high-density workloads. Their adoption is
further supported by advancements in semiconductor design, integration with
next-generation networking technologies, and the growing demand for low-latency
computing across diverse industries, including healthcare, automotive, and
financial services. While GPUs remain dominant in flexible AI applications,
ASICs are witnessing stronger uptake in large-scale, specialized environments
where predictable performance and cost efficiency are critical. Additionally,
the increasing development of AI-specific ASICs by leading technology companies
is expanding the product pipeline, enhancing competitiveness, and reducing
barriers to deployment. With their ability to deliver optimized performance for
emerging data-intensive applications, ASICs are positioned as a central growth
driver in the evolution of the global data center accelerator market.
Based on function, the inference segment is likely
to account for the largest market share in 2030.
The inference segment is expected to hold the
largest share of the data center accelerator market in 2030, driven by the
rapid growth of artificial intelligence (AI) and machine learning (ML)
applications across diverse industries. Inference workloads, which involve
applying trained AI models to process real-time data, are critical for enabling
functions such as image recognition, natural language processing, fraud
detection, recommendation systems, and autonomous decision-making. As
enterprises increasingly deploy AI at scale, accelerators such as GPUs, ASICs,
and FPGAs are adopted to deliver low-latency, high-throughput inference
capabilities with optimized power efficiency. The proliferation of edge
computing and IoT ecosystems further amplifies demand, as inference processing
needs to be executed closer to data sources for real-time responsiveness.
Additionally, cloud service providers and hyperscale data centers are expanding
inference-focused infrastructure to support enterprise AI adoption. Advancements
in accelerator architecture, such as domain-specific chips and heterogeneous
integration, further enhance performance and cost efficiency. With AI-driven
workloads becoming mainstream in sectors such as healthcare, finance, retail,
and automotive, the inference function is positioned as the cornerstone of
next-generation data center operations, ensuring scalability, efficiency, and
responsiveness in an increasingly digital economy.
By region, North America is expected to account for
the largest market share in 2030.
During the forecast period, North America is
expected to hold the largest share of the data center accelerator market in
2030, driven by the robust adoption of high-performance computing, artificial
intelligence, and cloud services across enterprise and hyperscale data centers.
Favorable government initiatives, significant investments in next-generation
data center infrastructure, and widespread deployment of AI and machine
learning workloads support market growth. The US, in particular, is witnessing
the rapid integration of GPUs, FPGAs, and ASICs to optimize compute-intensive
tasks, enhance energy efficiency, and reduce latency for critical applications
in BFSI, healthcare, autonomous systems, and scientific research. Leading
technology providers and hyperscale cloud operators are actively developing
modular and scalable accelerator solutions, supported by advanced software
stacks and AI frameworks, to maximize performance across heterogeneous
workloads. Canada also contributes through strategic investments in edge
computing and green data center initiatives, aligning with regional
sustainability and energy-efficiency objectives. Continuous innovation in
accelerator architectures and rising demand for real-time analytics,
high-throughput processing, and cloud-based services position North America as
a key regional driver of the global data center accelerator market, reinforcing
its leadership in advanced computing technologies.
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The report profiles key players, such as NVIDIA
Corporation (US), Advanced Micro Devices, Inc. (US), Intel Corporation (US),
Alphabet, Inc. (US), Amazon Web Services, Inc. (US), Qualcomm Technologies,
Inc. (US), Marvell (US), Achronix Semiconductor Corporation (US), Broadcom
(US), and Graphcore, Ltd. (UK). These players have adopted various organic and
inorganic growth strategies, such as product launches/developments,
collaborations, partnerships, and acquisitions.
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