Accelerator Cards

Global Accelerator Cards Market to Reach US$26.8 Billion by 2030

The global market for Accelerator Cards estimated at US$4.3 Billion in the year 2024, is expected to reach US$26.8 Billion by 2030, growing at a CAGR of 35.7% over the analysis period 2024-2030. High-Performance Computing Accelerator Type, one of the segments analyzed in the report, is expected to record a 32.2% CAGR and reach US$13.8 Billion by the end of the analysis period. Growth in the Cloud Accelerator Type segment is estimated at 40.2% CAGR over the analysis period.

The U.S. Market is Estimated at US$1.2 Billion While China is Forecast to Grow at 45.5% CAGR

The Accelerator Cards market in the U.S. is estimated at US$1.2 Billion in the year 2024. China, the world`s second largest economy, is forecast to reach a projected market size of US$6.9 Billion by the year 2030 trailing a CAGR of 45.5% over the analysis period 2024-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 29.3% and 31.9% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 30.2% CAGR.

Global Accelerator Cards Market – Key Trends & Drivers Summarized

Why Are Accelerator Cards Becoming Critical Enablers of High-Performance Computing, AI Workloads, and Data Center Optimization?
Accelerator cards are gaining strategic importance as computing architectures evolve to meet the demands of data-intensive applications, real-time analytics, artificial intelligence (AI), and machine learning (ML). These plug-in components—typically based on GPUs, FPGAs, or ASICs—are designed to offload and accelerate specific computational tasks from CPUs, significantly enhancing processing speed, throughput, and energy efficiency. Their adoption is being driven by enterprise and hyperscale data centers, research institutions, and industry verticals that rely on high-throughput, parallelized computing.

With workloads becoming more heterogeneous and specialized, traditional CPU-centric systems are proving insufficient to handle the complexity and scale of next-generation use cases. Accelerator cards address this gap by providing tailored compute capacity for inference engines, deep learning frameworks, genomic sequencing, real-time fraud detection, and data encryption, among others. These performance-intensive environments require scalable, workload-specific acceleration to maintain responsiveness and maximize resource utilization.

Additionally, the surge in AI-driven services, cloud-native applications, and edge computing architectures is fueling demand for efficient, high-bandwidth accelerators that can process complex algorithms locally or in distributed clusters. As organizations pursue digital transformation strategies centered around intelligent automation, accelerator cards are emerging as foundational components in next-gen IT infrastructure.

How Are Architectural Advancements, Open Standards, and Software Ecosystems Shaping the Design and Deployment of Accelerator Cards?
Ongoing innovations in chip architecture and interconnect design are pushing the performance boundaries of accelerator cards. Vendors are adopting heterogeneous computing models that combine CPUs with multiple types of accelerators on the same board or system, allowing workload-specific optimization. Technologies such as HBM (High Bandwidth Memory), PCIe Gen 5, and NVLink are enhancing data transfer rates and reducing latency between components, which is vital for real-time and memory-intensive applications.

The shift toward open standards—including OpenCL, CUDA, ROCm, and SYCL—is expanding software support across hardware platforms, enabling developers to write portable code for different accelerators. Ecosystems built around machine learning frameworks like TensorFlow, PyTorch, and ONNX are driving adoption by simplifying integration and deployment of accelerator-enhanced workflows. Software toolchains, compilers, and orchestration layers are evolving to support dynamic load balancing and resource pooling across CPUs, GPUs, and FPGAs.

The trend toward modular, disaggregated infrastructure—especially in hyperscale and cloud environments—is facilitating plug-and-play adoption of accelerator cards. System integrators and OEMs are embedding accelerators into rack-scale architectures, edge nodes, and hybrid cloud deployments. This modularity enables workload agility, allowing enterprises to scale compute resources based on changing performance requirements without overhauling core systems.

Which Use Cases, Industry Verticals, and Regional Markets Are Driving the Proliferation of Accelerator Cards?
AI and ML workloads remain the dominant use cases for accelerator cards, particularly in training and inferencing processes that demand high-speed matrix computations. Applications in computer vision, speech recognition, autonomous navigation, and natural language processing rely on accelerators to meet latency and accuracy thresholds. In scientific computing, accelerator cards are used in simulations, weather modeling, and particle physics to reduce computation times for large-scale datasets.

The financial services sector leverages accelerators for high-frequency trading, risk modeling, and blockchain encryption, while healthcare institutions use them in medical imaging, diagnostics, and bioinformatics. Media and entertainment companies deploy accelerator cards for real-time rendering, video transcoding, and virtual production workflows. Telecommunications firms integrate them into 5G infrastructure for baseband processing and network function virtualization (NFV).

Regionally, North America leads in adoption due to its concentration of hyperscale cloud providers, AI startups, and research centers. Europe follows closely with investment in HPC clusters and sovereign AI initiatives. Asia-Pacific, particularly China, South Korea, and Japan, is a fast-growing market propelled by digital infrastructure buildouts, AI commercialization, and regional data sovereignty drives. Meanwhile, emerging economies are exploring accelerators to enable cost-efficient performance gains in public sector and enterprise digitalization projects.

What Strategic Role Will Accelerator Cards Play in the Evolution of Data-Driven Enterprises and Intelligent Infrastructure?
Accelerator cards are poised to play a defining role in enabling the next wave of digital infrastructure—where real-time intelligence, decentralized processing, and extreme-scale analytics converge. Their ability to deliver task-specific performance with lower power consumption and higher operational density supports critical goals in cloud computing, AI model deployment, and edge-based autonomy. As enterprises increasingly view compute as a strategic asset, accelerators offer a pathway to future-proof systems and unlock new capabilities.

The rise of composable infrastructure, AI-as-a-Service, and zero-trust security models will further amplify the strategic relevance of accelerator cards. These cards are not only computational enhancers but also key components in energy-efficient data centers and sustainable IT strategies. Their role extends from core processing to enabling workload migration, orchestration, and AI lifecycle management.

As enterprises move toward decentralized, data-centric decision-making powered by intelligent systems, could accelerator cards become the architectural linchpin that redefines performance scalability and operational agility across digital ecosystems?

SCOPE OF STUDY:

The report analyzes the Accelerator Cards market in terms of units by the following Segments, and Geographic Regions/Countries:

Segments:
Accelerator Type (High-Performance Computing Accelerator Type, Cloud Accelerator Type); Processor Type (Central Processing Unit, Graphics Processing Unit, Field-Programmable Gate Array, Application-Specific Integrated Circuit); Application (Video & Image Processing Application, Machine Learning Application, Data Analytics Application, Mobile Phones Application, Other Applications)

Geographic Regions/Countries:
World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; Spain; Russia; and Rest of Europe); Asia-Pacific (Australia; India; South Korea; and Rest of Asia-Pacific); Latin America (Argentina; Brazil; Mexico; and Rest of Latin America); Middle East (Iran; Israel; Saudi Arabia; United Arab Emirates; and Rest of Middle East); and Africa.

Select Competitors (Total 34 Featured) -

• Achronix Semiconductor Corporation
• Advanced Micro Devices, Inc. (AMD)
• ATTO Technology
• Broadcom Inc.
• Cisco Systems, Inc.
• Dell Technologies Inc.
• Fujitsu Limited
• Hewlett Packard Enterprise (HPE)
• Huawei Technologies Co., Ltd.
• IBM Corporation
• Intel Corporation
• Inspur Group
• Lenovo Group Limited
• Marvell Technology Group Ltd.
• Matrox Graphics, Inc.
• Microsemi Corporation
• Napatech A/S
• NVIDIA Corporation
• Oracle Corporation
• Xilinx, Inc.

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