Deep learning training to hold largest share of Data Center Accelerator Market worth $21.19 billion by 2023 – Report by MarketsandMarkets™

The key factor driving the growth of the data center accelerator market for deep learning training is the increasing use of the technology in various applications such as voice recognition, fraud detection, voice search, recommendation engines, sentiment analysis, image recognition, and motion detection.

According to the recent research report 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 2023″, the data center accelerator market is expected to be valued at USD 2.84 billion by 2018 and is expected to reach USD 21.19 billion by 2023, at a CAGR of 49.47% from 2018 to 2023.

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The shifting focus toward parallel computing in AI data centers and growth of cloud-based services are among the factors driving the growth of the data center accelerator market. A growing number of tech giants and start-ups have begun offering machine learning as a cloud service due to the burgeoning demand for AI-based computation. Cloud-based solutions are ideal for small and midsized businesses that find on-premise solutions costlier. Thus, the increasing adoption of cloud-based technology is necessitating the need for deep learning.

Deep learning training to hold largest share during forecast period

The companies such as Amazon Web Services (US) and Microsoft (US) have developed a deep learning interface, which can be used to prototype, build, train, and deploy machine learning models for cloud and mobile apps.

GPU held largest share of market based on processor type in 2017

The key factor driving the growth of data center accelerator market is the focus on parallel computing in AI data centers. Deep neural networks and machine learning would require parallel computing solutions that can speed up 90% of algorithms in AI. GPUs are suitable for parallel computing because of their parallel architecture with thousands of cores within, which enable them to handle multiple instructions concurrently. Parallel computing model is ideal for implementing deep learning training and interface as artificial neural networks principally work more efficiently with a parallel computing framework.

North America held largest share for data center accelerator market in 2017

North America held the largest market share in 2017. The growing trend of cloud computing has radically increased the economic impact of data center investments made by leading service providers, such as Amazon (US), Facebook (US), Google (US), and Microsoft (US).  Also, there is a demand for sophisticated infrastructure and services in North America, which encourages the owners of data centers to opt for the ANSI/TIA-942 standard and also, continually, invest in upgrading their equipment and processes.

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Major players operating in the data center accelerator market include NVIDIA (US), Intel (US), Alphabet (US), Advanced Micro Devices (US), Achronix Semiconductor (US), Oracle (US), Xilinx (US), IBM (US), HP (US), Dell (US), Lenovo (China), Fujitsu (Japan), and Cisco (US).

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