Hardware Acceleration Market - Size, Share, Industry Trends, and Forecasts (2025 - 2032)

By Type:

Based on the type, the market is segmented into graphics processing units (GPUs), field-programmable gate arrays (FPGAs), tensor processing units (TPUs), cryptographic accelerators, DPU accelerators, AI accelerators, and others.

Trends in the Type:

• Data centers are increasingly leveraging DPU accelerator to improve the performance of infrastructure technologies in turn driving the hardware acceleration market trend.
• The increasing machine learning workload is driving the adoption of tensor processing units accelerator which in turn drives the hardware acceleration market trend.

Graphics processing unit accelerator accounted for the largest revenue share in the year 2024.

• The adoption of the GPU accelerator significantly speeds up video encoding, decoding, and image processing tasks, enabling faster rendering and real-time editing capabilities driving the GPU accelerator which in turn propels the hardware acceleration market share.
• Moreover, the growing emphasis on AI-specific hardware and rising adoption of AI in various applications is driving the need for GPU accelerator which in turn fuels the hardware acceleration market size.
• Further, GPUs are increasingly being integrated with edge computing, enabling real-time data processing and analysis driving the hardware acceleration market growth.
• For instance, in June 2024, Databricks partnered with NVIDIA to enhance support for NVIDIA GPU acceleration on the Databricks Platform. The partnership aims to drive the adoption of generative AI applications, or digital twins.
• Thus, the growing emphasis on AI and enhanced image processing tasks is driving the GPU accelerator.

AI accelerator is anticipated to register the fastest CAGR during the forecast period.

• The primary role of AI accelerators is to increase performance, scalability, and efficiency to meet the rising demand for high-performance devices built to handle user AI workloads.
• Further, the ability to save time and power as well as deliver simple, cost-effective AI scalability solutions is driving the adoption of AI accelerators in cloud computing, and others.
• For instance, in November 2024, IBM collaborated with AMD to develop AMD Instinct MI300X accelerators. The collaboration aims to enhance performance and power efficiency for Gen AI models such as high-performance computing applications.
• Therefore, the ability to save time and power as well as deliver simple, cost-effective AI scalability is anticipated to boost the market during the forecast period.

By Application:

Based on the application, the market is segmented into deep learning inference, product design and production, data processing & analysis, public cloud inference, inventory & supply chain management, and others.

Trends in Application:

• The trend towards the adoption of digital twin in the manufacturing industry is driving the adoption of accelerators for applications such as product design and production.
• The trends toward increasing numbers of data centers are driving the need for the hardware acceleration industry for data processing and analysis applications.

The deep learning inference accounted for the largest revenue share in the year 2024 and is anticipated to register the fastest CAGR during the forecast period.

• The advantages of adopting an accelerator in deep learning interference include reduced time, increased speed, improved efficiency, and reduced cost of training and deployment in turn fueling the hardware acceleration market.
• Further, the hardware accelerator significantly reduces the time to train and deploy deep learning models driving the need for accelerators in deep learning interference applications.
• For instance, in May 2023, MiTAC Computing Technology collaborated with Hailo Technologies to launch the MiTAC MiAi-H8 Card. The card is a hardware accelerator designed to leverage the power of artificial intelligence (AI) and deep learning inference tasks, in edge computing environments.
• Thus, according to the hardware acceleration market analysis, the aforementioned advantages of adopting an accelerator in deep learning interface applications in turn drive the hardware acceleration market.

By End User:

Based on the end-user, the market is segmented into IT & telecommunication, manufacturing, healthcare, consumer electronics, retail & warehousing, and others.

Trends in the End-User:

• The trend towards increasing adoption of autonomous vehicles is driving the need for accelerators in the automotive sector.
• The trend towards rising wearable devices that are leveraging accelerators for boosting performance and accelerating services such as video, images, music real-time processing, and streaming.

IT & telecommunication accounted for the largest revenue share of 30.10% in the year 2024.

• The IT & telecommunication sector plays a crucial role in driving the adoption of hardware accelerators to speed up the processing of transactions, optimize production processes, and improve product quality as well as render high-quality graphics.
• Further, 5G deployment is driving the demand for hardware acceleration which plays a crucial role in ensuring the efficient and reliable delivery of high-speed, low-latency communications.
• For instance, in April 2021, IEI launched a 5G network solution embedded with PUZZLE-IN005, which is a processor by Intel. The processor integrates hardware acceleration of compute-intensive workloads to maximize CPU utilization and support higher data rates.
• Thus, 5G deployment is driving the hardware acceleration market share in the IT & telecommunication sector.

Healthcare is anticipated to register the fastest CAGR during the forecast period.

• Healthcare sector is leveraging accelerators for increasing computing tasks, processing medical data, aiding diagnosis decision-making, and advanced analytics.
• Further, the CT, MRI image processing, and smart hospital data systems utilize accelerators for data processing & analysis in turn boosting hardware acceleration market size.
• For instance, in September 2022, Acceleration Robotics launched ROBOTCORE, which is used to accelerate robot operating systems. The system features ROS 2 hardware acceleration which has the ability to react faster, consume less energy, and deliver additional real-time capabilities. The robot is designed for applications including autonomous mobility, industrial manipulation, and healthcare applications.
• Therefore, according to the hardware acceleration market analysis, the rising need for data processing & analysis in healthcare is anticipated to boost the market during the forecast period.