A specialised hardware device, or group of devices, known as a data center accelerator is created to improve the efficiency of computational and data-intensive applications in a data centre setting.
These accelerators can be utilised for a number of purposes, including accelerating artificial intelligence (AI) and machine learning (ML) workloads, carrying out difficult mathematical operations, speeding up data processing, and enhancing network performance.
Applications-specific integrated circuits (ASICs), graphics processing units (GPUs), field-programmable gate arrays (FPGAs), and tensor processing units are a few examples of data centre accelerators (TPUs).
Organizations can significantly increase application performance, cut power consumption, and lower total expenses of running data centres by utilising data centre accelerators.
Data Center Accelerator Market Overview
The data center accelerator market has been experiencing significant growth in recent years, driven by the increasing demand for high-performance computing (HPC) applications, artificial intelligence (AI), and machine learning (ML).
The global data center accelerator market size was valued at USD 6.59 billion in 2022. It is projected to reach USD 23.15 billion by 2031, growing at a CAGR of 14.98% during the forecast period (2023-2031).
CPU (central processing unit) dominates the processor type segment
Artificial intelligence dominates the FPGA segment
Asia-Pacific is the highest contributor to the market
The market is primarily driven by the growing demand for improved data processing capabilities in data center environments. The rising demand for real-time analytics and the need for faster data processing in various industries, such as healthcare, finance, and automotive, are also contributing to the growth of the market. In addition, the increasing adoption of cloud computing and the growing popularity of edge computing are driving the demand for data center accelerators.
Graphics processing units (GPUs) currently dominate the data center accelerator market due to their versatility and high processing power. However, other accelerators such as field-programmable gate arrays (FPGAs) and application-specific integrated circuits (ASICs) are also gaining popularity in the market.
The CPU (central processing unit) segment is the highest contributor to the market and is estimated to grow at a CAGR of 8.08% during the forecast period. The central processor of a computer system is called the CPU.Improved CPUs were required as data centres transitioned from physical servers to virtualized systems to fulfil the needs of high-performance computing.
CPU-based computing has historically dominated data centres, but as next-generation workloads in areas like Big Data and streaming analytics, artificial intelligence (AI), the internet of things (IoT), genomics, and network security emerge, CPUs are now forced to deal with a variety of new algorithms, varying data types, and varying file sizes.
Moreover, microprocessor makers continuously enhance their processors by adding new instructions and data formats to speed up ML workloads. Machine Learning (ML) workloads are typically conducted on CPUs. Hence, the utilisation of CPUs for ML workloads is expanded.
Here are some potential pros and cons of the data center accelerator market:
- Improved performance: Data center accelerators can significantly improve the performance of computing and data-intensive applications, enabling faster data processing, real-time analytics, and faster training of AI/ML models.
- Cost savings: By using data center accelerators, organizations can achieve significant cost savings by reducing power consumption and increasing operational efficiency. This is especially important in large data center environments where energy costs can be a significant expense.
- Scalability: Data center accelerators can be easily scaled up or down to meet changing workloads, making them a flexible solution for data center environments.
- Versatility: Different types of accelerators can be used for different applications, making them a versatile solution for various industries and use cases.
- Cost: The upfront cost of data center accelerators can be high, making them a significant investment for organizations. Additionally, some accelerators may require specialized expertise to deploy and manage, which can also add to the cost.
- Compatibility: Not all applications are compatible with data center accelerators, so organizations may need to modify or optimize their applications to take advantage of the benefits that accelerators provide.
- Complexity: The deployment and management of data center accelerators can be complex, especially for organizations with limited experience in this area. This can require specialized expertise or additional training for IT staff.
- Vendor lock-in: Organizations may become dependent on a specific vendor’s hardware and software when deploying data center accelerators, which can limit their flexibility in choosing different solutions in the future.