Asia-Pacific Deep Learning Processors for Data Center Market, Forecast to 2022

This study explores the explosion of Artificial Intelligence (AI), and more specifically, deep learning. We look into the current applications of deep learning as well what lies ahead for the future from the data centers. The advancement of deep learning (DL) stimulates the development of artificial intelligence (AI). DL includes 2 learning phases which are training and inference. The study period is expected to see increasing deep learning workload, both training and inference, in the data centers for internal usage and of providing computing power as a cloud service. The support of hardware and processors with better compute performance and power-efficiency are critical to accelerate the development of deep learning in addition to big data and advanced algorithms.

Research Scope

This study also focuses largely on the computing solutions that are powering deep learning networks, broken down into the key market players, platforms and architecture. Key players such as Intel, NVIDIA, Xilinx, AMD, Google, IBM etc., have placed their investment on different architectures and technology including Graphics Processing Unit (GPU), Field-Programmable Gate Arrays (FPGA), Application-Specific Integrated Circuit (ASIC), neuromorphic chips and quantum computing, etc., to lead the market. A growing number of funds are also invested on the potential start-ups by venture capitals. This study scans different types of DL processors in the data center and analyzes the key players in the industry. In addition, the research also explores the new entrants for the innovation of deep learning processors for data centers. An examination of application of artificial intelligence in APAC market, the development in the APAC region, and the future trends of DL processors in the data center will be included in this report.

Research Highlights

In brief, this research service provides the following:
1. Introduction of DL
2. Key drivers and challenges and applications
3. DL workload in the data center and market of the DL processors
4. Key players and competitive analysis
5. Potential new entrants
5. Highlight of APAC region development
6. Trends and future of DL processors in data centers

Key Issues Addressed

• What is deep learning and its current applications in the market?
• How DL processors benefit data centers? What is the reason that data centers require processors particularly for DL workload?
• How’s the current market development of DL processor for data center?
• Who are key players and what are their strategies in the market? Is there any potential new entrant worth noticing?
• How’s the development of DL in the data center in APAC market? What are the key strengths of the market?
• What are the trends of DL processor development in data centers in terms of product and business partnership or ecosystem development?