DUBLIN--(BUSINESS WIRE)--The "Data Center Accelerator Market by Processor Type (CPU, GPU, FPGA, ASIC), Type (HPC Accelerator, Cloud Accelerator), Application (Deep Learning Training, Public Cloud Interface, Enterprise Interface), and Geography - Global Forecast to 2026" report has been added to ResearchAndMarkets.com's offering.
The data center accelerator market was valued at USD 13.7 billion in 2021 and is anticipated to reach USD 65.3 billion by 2026, growing at a CAGR of 36.7% between 2021 to 2026. The growing demand for data center accelerator in applications such as deep learning is driving the growth of data center accelerator market.
Deep learning services being made available over the cloud are reducing the initial costs associated with executing business operations and curtailing server maintenance tasks. A growing number of tech giants and startups have begun offering machine learning as a cloud service due to the burgeoning demand for AI-based computation. Most companies and startups do not develop their own specialized hardware or software to apply deep learning to their specific business needs. Cloud-based solutions are ideal for small and midsized businesses that find on-premises solutions costlier. Thus, the increasing adoption of cloud-based technology is necessitating the need for deep learning.
Cloud data center is dominating the data center accelerator market owing to rise in demand for AI based solution. The growth of AI is leading to changes in cloud server configuration. The cloud computing market has witnessed significant growth owing to the surge in the volume of data being transferred to the cloud from consumers. The surge in AI-centric data has led to the growth of co-processors (accelerators) embedded in the servers. The accelerators optimize data processing at the servers by reducing the latency.
According to Intel, currently, ~7% of the servers are used in deep learning activities. There are ~12 million server units around the globe as of 2021. In the AI-capable servers for deep learning training, the typical CPU to GPU attach rate is 1-4 GPUs; in some cases, it is around 1-8 GPUs. Deep learning is expected to account for the majority of cloud workload during the forecast period, which, in turn, is likely to propel the demand for accelerators for cloud servers. More than one-third of servers to be shipped in 2026 are likely to run either deep learning training algorithms or deep learning inference algorithms. Accelerators are likely to be deployed in the cloud servers for both public and enterprise cloud inference applications. However, training applications are expected to account for the majority of the server applications by the end of 2026.
The data center accelerator market in APAC is anticipated to register the highest CAGR of 42.7% between 2021 and 2026. The organizations in APAC have more preference for deploying a hybrid cloud. The organizations are adopting a mix of on-premises, third-party, co-location, private cloud, hosted cloud, and public cloud - depending on the nature of workloads, legacy decisions made by the team, budgets, and technology maturity within the organization.
Key Topics Covered:
1 Introduction
2 Research Methodology
3 Executive Summary
4 Premium Insights
4.1 Attractive Opportunities in the Data Center Accelerator Market
4.2 Data Center Accelerator Market, by Type
4.3 Market for Cloud Data Center Accelerator, by Country
4.4 APAC: Data Center Accelerator Market, by Application & Country
4.5 Data Center Accelerator Market, by Processor Type
5 Market Overview
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Growth of Cloud-Based Services
5.2.1.2 Focus on Parallel Computing in Ai Data Centers
5.2.1.3 Deep Learning Usage in Big Data Analytics
5.2.2 Restraints
5.2.2.1 Premium Pricing of Accelerators
5.2.2.2 Limited Ai Hardware Experts
5.2.3 Opportunities
5.2.3.1 Demand in the Market for FPGA-Based Accelerators
5.2.3.2 Rising Need for Co-Processors due to the Slowdown of Moore's Law
5.2.4 Challenges
5.2.4.1 Unreliability of Ai Algorithms
5.2.4.2 Complex Ai Mechanisms
5.3 Impact of COVID-19
5.4 Ecosystem
5.5 Technology Analysis
5.6 Case Studies
5.7 Value Chain Analysis
5.8 Standards and Guidelines for the Data Center Market
5.9 Regulations
5.10 Porter's Five Forces Analysis
5.11 Pricing Analysis
5.12 Patent Analysis
5.13 Yc-Ycc Shift - Data Center Accelerator
5.14 Trade Analysis
6 Data Center Accelerator Market, by Processor Type
7 Data Center Accelerator Market, by Type
8 Data Center Accelerator Market, by Application
9 Geographic Analysis
10 Competitive Landscape
11 Company Profiles
- Achronix Semiconductor
- Advantech Co., Ltd
- Amd
- Bittware
- Enflame Technology
- Fujitsu
- Graphcore
- Gyrfalcon Technology Inc.
- Huawei Technologies
- IBM
- Intel
- Lattice Semiconductor
- Leap Mind Inc.
- Marvell
- Microchip Technology
- Micron
- NEC
- Nvidia
- Qnap System Inc.
- Qualcomm
- Sambanova
- Semptian
- Wave Computing
- Xilinx
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