Deep-Learning Computing Unit Market

Deep-Learning Computing Unit Market aims to provide a comprehensive presentation of the global market for Deep-Learning Computing Unit (DCU), with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Deep-Learning Computing Unit (DCU). Deep-Learning Computing Unit Market contains market size and forecasts of Deep-Learning Computing Unit (DCU) in global, including the following market information:
Global Deep-Learning Computing Unit (DCU) Market Revenue, 2018-2023, 2024-2029, ($ millions)
Global Deep-Learning Computing Unit (DCU) Market Sales, 2018-2023, 2024-2029, (K Units)
Global top five Deep-Learning Computing Unit (DCU) companies in 2022 (%)
The global Deep-Learning Computing Unit (DCU) market was valued at US$ million in 2022 and is projected to reach US$ million by 2029, at a CAGR of % during the forecast period. The influence of COVID-19 and the Russia-Ukraine War were considered while estimating market sizes.
The U.S. Market is Estimated at $ Million in 2022, While China is Forecast to Reach $ Million.
GPGPU Segment to Reach $ Million by 2029, with a % CAGR in next six years.
The global key manufacturers of Deep-Learning Computing Unit (DCU) include NVIDIA, AMD, Intel, Google, Xilinx, Hygon, Hisilicon, Cambricon Technologies and Iluvatar CoreX, etc. in 2022, the global top five players have a share approximately % in terms of revenue.
We surveyed the Deep-Learning Computing Unit (DCU) manufacturers, suppliers, distributors and industry experts on this industry, involving the sales, revenue, demand, price change, product type, recent development and plan, industry trends, drivers, challenges, obstacles, and potential risks.
Total Market by Segment:
Global Deep-Learning Computing Unit (DCU) Market, by Type, 2018-2023, 2024-2029 ($ Millions) & (K Units)
Global Deep-Learning Computing Unit (DCU) Market Segment Percentages, by Type, 2022 (%)
GPGPU
ASIC
FPGA
Others
Global Deep-Learning Computing Unit (DCU) Market, by Application, 2018-2023, 2024-2029 ($ Millions) & (K Units)
Global Deep-Learning Computing Unit (DCU) Market Segment Percentages, by Application, 2022 (%)
Business Computing and Big Data Analytics
Artificial Intelligence
Others
Global Deep-Learning Computing Unit (DCU) Market, By Region and Country, 2018-2023, 2024-2029 ($ Millions) & (K Units)
Global Deep-Learning Computing Unit (DCU) Market Segment Percentages, By Region and Country, 2022 (%)
North America
US
Canada
Mexico
Europe
Germany
France
U.K.
Italy
Russia
Nordic Countries
Benelux
Rest of Europe
Asia
China
Japan
South Korea
Southeast Asia
India
Rest of Asia
South America
Brazil
Argentina
Rest of South America
Middle East & Africa
Turkey
Israel
Saudi Arabia
UAE
Rest of Middle East & Africa
Competitor Analysis
The report also provides analysis of leading market participants including:
Key companies Deep-Learning Computing Unit (DCU) revenues in global market, 2018-2023 (Estimated), ($ millions)
Key companies Deep-Learning Computing Unit (DCU) revenues share in global market, 2022 (%)
Key companies Deep-Learning Computing Unit (DCU) sales in global market, 2018-2023 (Estimated), (K Units)
Key companies Deep-Learning Computing Unit (DCU) sales share in global market, 2022 (%)
Further, the report presents profiles of competitors in the market, key players include:
NVIDIA
AMD
Intel
Google
Xilinx
Hygon
Hisilicon
Cambricon Technologies
Iluvatar CoreX
Outline of Major Chapters:
Chapter 1: Introduces the definition of Deep-Learning Computing Unit (DCU), market overview.
Chapter 2: Global Deep-Learning Computing Unit (DCU) market size in revenue and volume.
Chapter 3: Detailed analysis of Deep-Learning Computing Unit (DCU) manufacturers competitive landscape, price, sales and revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6: Sales of Deep-Learning Computing Unit (DCU) in regional level and country level. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space of each country in the world.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 8: Global Deep-Learning Computing Unit (DCU) capacity by region & country.
Chapter 9: Introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 10: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 11: The main points and conclusions of the report.