Global data center accelerator market size was valued at USD 14.09 billion in 2023, which is estimated to reach USD 16.92 billion in 2024 and USD 70.95 billion by 2031, growing at a CAGR of 22.72% from 2024 to 2031.

The global Data Center Accelerator Market is witnessing rapid expansion as enterprises, cloud service providers, and hyperscalers race to deploy purpose-built compute engines to meet surging demand from artificial intelligence (AI), machine learning (ML), high-performance computing (HPC), and real-time analytics workloads. Accelerators — including GPUs, FPGAs, ASICs/TPUs, and other purpose-built processors — are increasingly integrated into data center architectures to deliver orders-of-magnitude improvements in throughput and energy efficiency over general-purpose CPUs.

According to Kings Research (report basis), the market is experiencing sustained growth driven by large language models (LLMs), inference at the edge, densification of data centers, and an emphasis on power-efficient compute. This press release outlines market growth drivers, trends, demand dynamics, segmentation, leading players, and regional analysis formatted in paragraph and bullet style for clarity and rapid adoption by communications teams.

Key Market Trends & Insights

• The adoption of accelerator-first architectures is shifting data center design from CPU-centric to heterogeneous compute models, where accelerators handle specialized workloads while CPUs manage orchestration and I/O.
• AI training and inference remain the primary demand engines — training favors high-memory, high-bandwidth accelerator clusters, whereas inference drives deployment of lower-latency, power-efficient accelerators closer to application endpoints.
• Energy efficiency and TCO (total cost of ownership) are becoming central purchasing criteria; modern accelerators deliver better performance-per-watt and allow operators to reduce rack power density and cooling costs per unit of useful throughput.
• Software and ecosystem maturation — including containerization, orchestration layers (Kubernetes-based device plugins), and optimized compilers (e.g., XLA, TVM) — are lowering barriers to accelerator adoption and improving utilization rates.
• Custom silicon (ASIC/TPU) adoption is rising among hyperscalers seeking differentiated performance and cost profiles; at the same time, GPU ecosystems remain dominant for model portability and broad developer familiarity.
• Edge and distributed inference deployments are increasing, prompting hybrid accelerator strategies spanning cloud, colocation, and edge data centers.

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Market Growth & Forecast

Kings Research's market analysis shows the Data Center Accelerator Market entering a multi-year expansion phase as capital expenditure (CapEx) cycles for cloud providers and large enterprises rotate into accelerator investments. Demand from generative AI models, real-time analytics for financial services, genomics, and scientific computing is creating a two-pronged market pull: (1) hyperscalers investing in massive training clusters and custom ASICs/TPUs; and (2) enterprises and CSPs procuring GPU/FPGA instances to accelerate inference and domain-specific workloads. Market growth is further amplified by falling unit costs for accelerators, improved software stacks that increase utilization, and regulatory/industry mandates prioritizing compute efficiency. These forces combine to produce a robust mid-to-long-term forecast for the accelerator segment within the broader data center equipment market.

Demand Drivers & Dynamics

• AI & ML Workloads: The explosive growth of transformer-based models, recommendation systems, and foundation models has pushed organizations to invest in accelerators for both training and inference.
• Cloud Migration & XaaS Models: Cloud service providers offering accelerator instances (GPU/FPGA/TPU as a Service) expand access and lower entry barriers for SMEs and startups, widening market adoption.
• HPC & Scientific Research: Academia and research institutions require accelerators for simulation, weather modelling, and genomics, adding a high-value, high-performance demand stream.
• Real-Time Analytics & Edge Inference: Industries such as telecom, automotive, retail, and manufacturing deploy accelerators to enable low-latency, on-premise inferencing and near-edge processing.
• Energy & Cooling Optimization: Accelerators that deliver higher performance per watt and support efficient cooling integration are preferred, influencing procurement cycles and data center retrofits.
• Software & Ecosystem Maturity: Better tooling, pre-trained model availability, and managed orchestration reduce the complexity of running accelerator workloads, improving ROI and utilization.

List of Key Companies in Data Center Accelerator Market:

·         NVIDIA Corporation

·         IBM

·         Dell Inc.

·         Advanced Micro Devices, Inc.

·         Qualcomm Technologies, Inc.

·         Marvell

·         Intel Corporation

·         Micron Technology, Inc.

·         Achronix Semiconductor Incorporated

·         Lattice Semiconductor

·         Lenovo

·         Microchip Technology Inc.

·         NEC Corporation

·         Synopsys, Inc.

·         Voltron Data

Infrastructure & Segment Insights

The Data Center Accelerator Market can be segmented by accelerator type, deployment model, enterprise size, end-user vertical, and region. Below we present insights for each major segmentation axis:

Accelerator Type

• GPUs (General-purpose / AI GPUs): Continue to lead due to developer familiarity, vast software ecosystems, and flexibility across training/inference workloads.
• FPGAs: Preferred for low-latency, reprogrammable inference tasks and telecom/network offload; attractive for operators seeking lower power draw and customizable data paths.
• ASICs / TPUs / NPUs: Gaining traction with hyperscalers and cloud giants where scale and power efficiency justify custom silicon investments.
• Other accelerators (DPUs, IPUs, custom neural processors): Growing niche adoption for specific workloads like networking offload (DPUs) and highly parallel graph processing (IPUs).

Deployment Model

• On-Premise: Large enterprises and regulated industries deploy accelerators in private data centers for latency, security, and data-sovereignty reasons.
• Cloud (Public/Hybrid): CSPs offer flexible accelerator instances; pay-as-you-go models accelerate adoption among smaller organizations.
• Colocation & Edge: Colocation providers integrate accelerator racks for tenants; edge data centers use compact accelerators for local inferencing.

Enterprise Size

• Large Enterprise: Major spenders on accelerator hardware to host critical AI/analytics workloads.
• Small & Medium Enterprises (SMEs): Increasingly adopt accelerator services via public cloud, reducing upfront hardware investment.

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End-Use Verticals

• Cloud Service Providers & Hyperscalers
• Technology & IT Services
• Financial Services (Low latency trading, fraud detection)
• Healthcare & Life Sciences (Genomics, imaging)
• Telecommunications (5G/6G network functions, vRAN acceleration)
• Automotive & Autonomous Systems
• Retail & E-commerce (Recommendation engines, personalization)
• Energy & Utilities (Grid optimisation, sensor analytics)
• Government & Defense (Secure on-prem AI deployments)

Regional Insights

North America

• North America leads in accelerator adoption, driven by the concentration of hyperscalers, cloud providers, and AI startups. Significant R&D investment and proximity to major accelerator vendors support rapid deployment cycles.

Europe

• Europe shows steady adoption with increasing enterprise investments and focused public funding for AI infrastructure. Energy efficiency and sustainability mandates influence procurement choices in the region.

Asia Pacific

• Asia Pacific is among the fastest-growing markets — led by China, India, Japan, and South Korea — where rising cloud adoption, local AI startups, and government initiatives spur demand. India, in particular, is emerging as a high-growth market as enterprises embrace cloud AI services and localized accelerator deployments.

Latin America

• Delayed but growing adoption due to expanding cloud availability and localized colocation investments. Telco virtualization and edge deployments are notable growth vectors.

Middle East & Africa

• Investment in smart city projects, telecom upgrades (5G), and government digitalization programs are driving nascent accelerator demand, often via partnerships with global cloud providers.

Regional Highlights (Bulleted)

• North America: Market leader with major hyperscaler investment.
• Asia Pacific: Fastest CAGR potential due to large addressable markets and rapid cloud adoption.
• Europe: Focus on energy-efficient accelerators and sustainable deployments.
• Latin America & MEA: Emerging demand tied to telco and government projects.

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