Deep-Learning Computing Unit (DCU) Market 2022: Industry Size, Emerging Trends, Growth Insights, Opportunities, and Forecast By 2028
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This report aims to provide a comprehensive presentation of the global market for Deep-Learning Computing Unit (DCU) study by Market Intellix gives insights concerning the market elements influencing the market, Market scope, Market division, and overlays shadow upon the leading market players featuring the positive cutthroat scene and patterns beating the years.
Global Deep-Learning Computing Unit (DCU) Market Revenue, 2017-2022, 2023-2028, ($ millions)
Global Deep-Learning Computing Unit (DCU) Market Sales, 2017-2022, 2023-2028, (K Units)
Global top five Deep-Learning Computing Unit (DCU) companies in 2021 (%)
The global Deep-Learning Computing Unit (DCU) market was valued at million in 2021 and is projected to reach US$ million by 2028, at a CAGR of % during the forecast period 2022-2028.
The U.S. Market is Estimated at $ Million in 2021, While China is Forecast to Reach $ Million by 2028.
GPGPU Segment to Reach $ Million by 2028, 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 2021, the global top five players have a share approximately % in terms of revenue.
The study provides 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.
Segmental Outline:
Global Deep-Learning Computing Unit (DCU) Market, by Type, 2017-2022, 2023-2028 ($ Millions) & (K Units)
Global Deep-Learning Computing Unit (DCU) Market Segment Percentages, by Type, 2021 (%)
GPGPU
ASIC
FPGA
Others
Global Deep-Learning Computing Unit (DCU) Market, by Application, 2017-2022, 2023-2028 ($ Millions) & (K Units)
Global Deep-Learning Computing Unit (DCU) Market Segment Percentages, by Application, 2021 (%)
Business Computing and Big Data Analytics
Artificial Intelligence
Others
Global Deep-Learning Computing Unit (DCU) Market, By Region and Country, 2017-2022, 2023-2028 ($ Millions) & (K Units)
Global Deep-Learning Computing Unit (DCU) Market Segment Percentages, By Region and Country, 2021 (%)
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, 2017-2022 (Estimated), ($ millions)
Key companies Deep-Learning Computing Unit (DCU) revenues share in global market, 2021 (%)
Key companies Deep-Learning Computing Unit (DCU) sales in global market, 2017-2022 (Estimated), (K Units)
Key companies Deep-Learning Computing Unit (DCU) sales share in global market, 2021 (%)
Further, the report presents profiles of competitors in the market, key players include:
NVIDIA
AMD
Intel
Xilinx
Hygon
Hisilicon
Cambricon Technologies
Iluvatar CoreX
This Report Addresses:
– Market Intelligence enables effective decision-making
– Market estimates and forecasts from 2022 to 2028
– Growth opportunities and trend analysis
– Segment and regional revenue forecast for market evaluation
– Competitive strategy and analysis of market segments
– List of product innovations to stay on top.
– The impact of COVID-19 and how to survive in these fast-growing markets.
1 Introduction to Research & Analysis Reports
1.1 Deep-Learning Computing Unit (DCU) Market Definition
1.2 Market Segments
1.2.1 Market by Type
1.2.2 Market by Application
1.3 Global Deep-Learning Computing Unit (DCU) Market Overview
1.4 Features & Benefits of This Report
1.5 Methodology & Sources of Information
1.5.1 Research Methodology
1.5.2 Research Process
1.5.3 Base Year
1.5.4 Report Assumptions & Caveats
2 Global Deep-Learning Computing Unit (DCU) Overall Market Size
2.1 Global Deep-Learning Computing Unit (DCU) Market Size: 2021 VS 2028
2.2 Global Deep-Learning Computing Unit (DCU) Revenue, Prospects & Forecasts: 2017-2028
2.3 Global Deep-Learning Computing Unit (DCU) Sales: 2017-2028
3 Company Landscape
3.1 Top Deep-Learning Computing Unit (DCU) Players in Global Market
3.2 Top Global Deep-Learning Computing Unit (DCU) Companies Ranked by Revenue
3.3 Global Deep-Learning Computing Unit (DCU) Revenue by Companies
3.4 Global Deep-Learning Computing Unit (DCU) Sales by Companies
3.5 Global Deep-Learning Computing Unit (DCU) Price by Manufacturer (2017-2022)
3.6 Top 3 and Top 5 Deep-Learning Computing Unit (DCU) Companies in Global Market, by Revenue in 2021
3.7 Global Manufacturers Deep-Learning Computing Unit (DCU) Product Type
3.8 Tier 1, Tier 2 and Tier 3 Deep-Learning Computing Unit (DCU) Players in Global Market
3.8.1 List of Global Tier 1 Deep-Learning Computing Unit (DCU) Companies
3.8.2 List of Global Tier 2 and Tier 3 Deep-Learning Computing Unit (DCU) Companies
4 Sights by Product
4.1 Overview
4.1.1 By Type - Global Deep-Learning Computing Unit (DCU) Market Size Markets, 2021 & 2028
4.1.2 GPGPU
4.1.3 ASIC
4.1.4 FPGA
4.1.5 Others
4.2 By Type - Global Deep-Learning Computing Unit (DCU) Revenue & Forecasts
4.2.1 By Type - Global Deep-Learning Computing Unit (DCU) Revenue, 2017-2022
4.2.2 By Type - Global Deep-Learning Computing Unit (DCU) Revenue, 2023-2028
4.2.3 By Type - Global Deep-Learning Computing Unit (DCU) Revenue Market Share, 2017-2028
4.3 By Type - Global Deep-Learning Computing Unit (DCU) Sales & Forecasts
4.3.1 By Type - Global Deep-Learning Computing Unit (DCU) Sales, 2017-2022
4.3.2 By Type - Global Deep-Learning Computing Unit (DCU) Sales, 2023-2028
4.3.3 By Type - Global Deep-Learning Computing Unit (DCU) Sales Market Share, 2017-2028
4.4 By Type - Global Deep-Learning Computing Unit (DCU) Price (Manufacturers Selling Prices), 2017-2028
5 Sights By Application
5.1 Overview
5.1.1 By Application - Global Deep-Learning Computing Unit (DCU) Market Size, 2021 & 2028
5.1.2 Business Computing and Big Data Analytics
5.1.3 Artificial Intelligence
5.1.4 Others
5.2 By Application - Global Deep-Learning Computing Unit (DCU) Revenue & Forecasts
5.2.1 By Application - Global Deep-Learning Computing Unit (DCU) Revenue, 2017-2022
5.2.2 By Application - Global Deep-Learning Computing Unit (DCU) Revenue, 2023-2028
5.2.3 By Application - Global Deep-Learning Computing Unit (DCU) Revenue Market Share, 2017-2028
5.3 By Application - Global Deep-Learning Computing Unit (DCU) Sales & Forecasts
5.3.1 By Application - Global Deep-Learning Computing Unit (DCU) Sales, 2017-2022
5.3.2 By Application - Global Deep-Learning Computing Unit (DCU) Sales, 2023-2028
5.3.3 By Application - Global Deep-Learning Computing Unit (DCU) Sales Market Share, 2017-2028
5.4 By Application - Global Deep-Learning Computing Unit (DCU) Price (Manufacturers Selling Prices), 2017-2028
6 Sights by Region
6.1 By Region - Global Deep-Learning Computing Unit (DCU) Market Size, 2021 & 2028
6.2 By Region - Global Deep-Learning Computing Unit (DCU) Revenue & Forecasts
6.2.1 By Region - Global Deep-Learning Computing Unit (DCU) Revenue, 2017-2022
6.2.2 By Region - Global Deep-Learning Computing Unit (DCU) Revenue, 2023-2028
6.2.3 By Region - Global Deep-Learning Computing Unit (DCU) Revenue Market Share, 2017-2028
6.3 By Region - Global Deep-Learning Computing Unit (DCU) Sales & Forecasts
6.3.1 By Region - Global Deep-Learning Computing Unit (DCU) Sales, 2017-2022
6.3.2 By Region - Global Deep-Learning Computing Unit (DCU) Sales, 2023-2028
6.3.3 By Region - Global Deep-Learning Computing Unit (DCU) Sales Market Share, 2017-2028
6.4 North America
6.4.1 By Country - North America Deep-Learning Computing Unit (DCU) Revenue, 2017-2028
6.4.2 By Country - North America Deep-Learning Computing Unit (DCU) Sales, 2017-2028
6.4.3 US Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.4.4 Canada Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.4.5 Mexico Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.5 Europe
6.5.1 By Country - Europe Deep-Learning Computing Unit (DCU) Revenue, 2017-2028
6.5.2 By Country - Europe Deep-Learning Computing Unit (DCU) Sales, 2017-2028
6.5.3 Germany Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.5.4 France Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.5.5 U.K. Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.5.6 Italy Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.5.7 Russia Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.5.8 Nordic Countries Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.5.9 Benelux Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.6 Asia
6.6.1 By Region - Asia Deep-Learning Computing Unit (DCU) Revenue, 2017-2028
6.6.2 By Region - Asia Deep-Learning Computing Unit (DCU) Sales, 2017-2028
6.6.3 China Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.6.4 Japan Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.6.5 South Korea Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.6.6 Southeast Asia Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.6.7 India Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.7 South America
6.7.1 By Country - South America Deep-Learning Computing Unit (DCU) Revenue, 2017-2028
6.7.2 By Country - South America Deep-Learning Computing Unit (DCU) Sales, 2017-2028
6.7.3 Brazil Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.7.4 Argentina Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.8 Middle East & Africa
6.8.1 By Country - Middle East & Africa Deep-Learning Computing Unit (DCU) Revenue, 2017-2028
6.8.2 By Country - Middle East & Africa Deep-Learning Computing Unit (DCU) Sales, 2017-2028
6.8.3 Turkey Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.8.4 Israel Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.8.5 Saudi Arabia Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
6.8.6 UAE Deep-Learning Computing Unit (DCU) Market Size, 2017-2028
7 Manufacturers & Brands Profiles
7.1 NVIDIA
7.1.1 NVIDIA Corporate Summary
7.1.2 NVIDIA Business Overview
7.1.3 NVIDIA Deep-Learning Computing Unit (DCU) Major Product Offerings
7.1.4 NVIDIA Deep-Learning Computing Unit (DCU) Sales and Revenue in Global (2017-2022)
7.1.5 NVIDIA Key News
7.2 AMD
7.2.1 AMD Corporate Summary
7.2.2 AMD Business Overview
7.2.3 AMD Deep-Learning Computing Unit (DCU) Major Product Offerings
7.2.4 AMD Deep-Learning Computing Unit (DCU) Sales and Revenue in Global (2017-2022)
7.2.5 AMD Key News
7.3 Intel
7.3.1 Intel Corporate Summary
7.3.2 Intel Business Overview
7.3.3 Intel Deep-Learning Computing Unit (DCU) Major Product Offerings
7.3.4 Intel Deep-Learning Computing Unit (DCU) Sales and Revenue in Global (2017-2022)
7.3.5 Intel Key News
7.4 Google
7.4.1 Google Corporate Summary
7.4.2 Google Business Overview
7.4.3 Google Deep-Learning Computing Unit (DCU) Major Product Offerings
7.4.4 Google Deep-Learning Computing Unit (DCU) Sales and Revenue in Global (2017-2022)
7.4.5 Google Key News
7.5 Xilinx
7.5.1 Xilinx Corporate Summary
7.5.2 Xilinx Business Overview
7.5.3 Xilinx Deep-Learning Computing Unit (DCU) Major Product Offerings
7.5.4 Xilinx Deep-Learning Computing Unit (DCU) Sales and Revenue in Global (2017-2022)
7.5.5 Xilinx Key News
7.6 Hygon
7.6.1 Hygon Corporate Summary
7.6.2 Hygon Business Overview
7.6.3 Hygon Deep-Learning Computing Unit (DCU) Major Product Offerings
7.6.4 Hygon Deep-Learning Computing Unit (DCU) Sales and Revenue in Global (2017-2022)
7.6.5 Hygon Key News
7.7 Hisilicon
7.7.1 Hisilicon Corporate Summary
7.7.2 Hisilicon Business Overview
7.7.3 Hisilicon Deep-Learning Computing Unit (DCU) Major Product Offerings
7.7.4 Hisilicon Deep-Learning Computing Unit (DCU) Sales and Revenue in Global (2017-2022)
7.7.5 Hisilicon Key News
7.8 Cambricon Technologies
7.8.1 Cambricon Technologies Corporate Summary
7.8.2 Cambricon Technologies Business Overview
7.8.3 Cambricon Technologies Deep-Learning Computing Unit (DCU) Major Product Offerings
7.8.4 Cambricon Technologies Deep-Learning Computing Unit (DCU) Sales and Revenue in Global (2017-2022)
7.8.5 Cambricon Technologies Key News
7.9 Iluvatar CoreX
7.9.1 Iluvatar CoreX Corporate Summary
7.9.2 Iluvatar CoreX Business Overview
7.9.3 Iluvatar CoreX Deep-Learning Computing Unit (DCU) Major Product Offerings
7.9.4 Iluvatar CoreX Deep-Learning Computing Unit (DCU) Sales and Revenue in Global (2017-2022)
7.9.5 Iluvatar CoreX Key News
8 Global Deep-Learning Computing Unit (DCU) Production Capacity, Analysis
8.1 Global Deep-Learning Computing Unit (DCU) Production Capacity, 2017-2028
8.2 Deep-Learning Computing Unit (DCU) Production Capacity of Key Manufacturers in Global Market
8.3 Global Deep-Learning Computing Unit (DCU) Production by Region
9 Key Market Trends, Opportunity, Drivers and Restraints
9.1 Market Opportunities & Trends
9.2 Market Drivers
9.3 Market Restraints
10 Deep-Learning Computing Unit (DCU) Supply Chain Analysis
10.1 Deep-Learning Computing Unit (DCU) Industry Value Chain
10.2 Deep-Learning Computing Unit (DCU) Upstream Market
10.3 Deep-Learning Computing Unit (DCU) Downstream and Clients
10.4 Marketing Channels Analysis
10.4.1 Marketing Channels
10.4.2 Deep-Learning Computing Unit (DCU) Distributors and Sales Agents in Global
11 Conclusion
12 Appendix
12.1 Note
12.2 Examples of Clients
12.3 Disclaimer
Research Methodology:
Deep Learning Computing Unit (DCU) Market Size Estimation
To estimate market size and trends, we use a combination of top-down and bottom-up methods. This allows us to evaluate the market from various perspectives—by company, region, product type, and end users.
Our estimates are based on actual sales data, excluding any discounts. Segment breakdowns and market shares are calculated using weighted averages based on usage rates and average prices. Regional insights are determined by how widely a product or service is adopted in each area.
Key companies are identified through secondary sources like industry reports and company filings. We then verify revenue estimates and other key data points through primary research, including interviews with industry experts, company executives, and decision-makers.
We take into account all relevant factors that could influence the market and validate our findings with real-world input. Our final insights combine both qualitative and quantitative data to provide a well-rounded view. Please note, these estimates do not account for unexpected changes such as inflation, economic downturns, or policy shifts.
Data Source
Secondary Sources
This study draws on a wide range of secondary sources, including press releases, annual reports, non-profit organizations, industry associations, government agencies, and customs data. We also referred to reputable databases and directories such as Bloomberg, Wind Info, Hoovers, Factiva, Trading Economics, Statista, and others. Additional references include investor presentations, company filings (e.g., SEC), economic data, and documents from regulatory and industry bodies.
These sources were used to gather technical and market-focused insights, identify key players, analyze market segmentation and classification, and track major trends and developments across industries.
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Primary Sources
As part of our primary research, we interviewed a variety of stakeholders from both the supply and demand sides to gather valuable qualitative and quantitative insights.
On the supply side, we spoke with product manufacturers, competitors, industry experts, research institutions, distributors, traders, and raw material suppliers. On the demand side, we engaged with business leaders, marketing and sales heads, technology and innovation directors, supply chain executives, and end users across key organizations.
These conversations helped us better understand market segmentation, pricing, applications, leading players, supply chains, demand trends, industry outlook, and key market dynamics—including risks, opportunities, barriers, and strategic developments.
Key Data Information from Primary Sources
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