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

Google

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

Methodology/Research Approach

This research study involved the extensive usage of both primary and secondary data sources. The research process involved the study of various factors affecting the industry, including the government policy, market environment, competitive landscape, historical data, present trends in the market, technological innovation, upcoming technologies and the technical progress in related industry, and market risks, opportunities, market barriers and challenges. The following illustrative figure shows the market research methodology applied in this report.

Research Programs/Design

Historical Data (2015-2019)	Industry Trends Competitive Landscape By Company Expansion Mergers and Acquisitions Market Segment by Type by Application By Regions/ Geography	Value Status and Outlook Value for Major Players Market Share Growth Rate Present Situation Analysis Value Market Share Growth Rate Present Situation Analysis
Influencing Factors	Market Environment Government Policy Technological Changes Market Risks	Market Drivers Growing Demand of Downstream Reduction in Cost
Market Forecast (2021-2026)	Overall Size by Type by Application By Regions/Geography	Key Data (Value) Market Share Growth Rate CAGR (2021-2026)

Market Size Estimation

Top-down and bottom-up approaches are used to validate the global Voluntary Carbon Offset market size market and estimate the market size for Company, regions segments, product segments and Application (end users).

The market estimations in this report are based on the marketed sale price of Voluntary Carbon Offset (excluding any discounts provided by the player, distributor, wholesaler or traders). The percentage splits, market share, and breakdowns of the product segments are derived on the basis of weights assigned to each of the segments on the basis of their utilization rate and average sale price. The regional splits of the overall Voluntary Carbon Offset market and its sub-segments are based on the percentage adoption or utilization of the given product in the respective region or country.

Major Company in the market is identified through secondary research and their market revenues determined through primary and secondary research. Secondary research included the research of the annual and financial reports of the top Company; whereas, primary research included extensive interviews of key opinion leaders and industry experts such as experienced front-line staff, directors, CEOs and marketing executives. The percentage splits, market share, Growth Rate and breakdowns of the product markets are determined through using secondary sources and verified through the primary sources.

All possible factors that influence the markets included in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data. The market size for top-level markets and sub-segments is normalized, and the effect of inflation, economic downturns, and regulatory & policy changes or other factors are not accounted for in the market forecast. This data is combined and added with detailed inputs and analysis from Market Intellix and presented in this report

The following figure shows an illustrative representation of the overall market size estimation process used for this study.

Market Breakdown and Data Triangulation

After complete market engineering with calculations for market statistics; market size estimations; market forecasting; market breakdown; and data triangulation, extensive primary research was conducted to gather information and verify and validate the critical numbers arrived at. In the complete market engineering process, both top-down and bottom-up approaches were extensively used, along with several data triangulation methods, to perform market estimation and market forecasting for the overall market segments and sub-segments listed in this report. Extensive qualitative and further quantitative analysis is also done from all the numbers arrived at in the complete market engineering process to list key information throughout the report.

Data Source

Secondary Sources

Secondary sources include such as press releases, annual reports, non-profit organizations, industry associations, governmental agencies and customs data, etc. This research study involves the usage of widespread secondary sources, directories, databases such as Bloomberg Business, Wind Info, Hoovers, Factiva (Dow Jones & Company), and TRADING ECONOMICS, and News Network, statista, Federal Reserve Economic Data, annual reports, BIS Statistics, ICIS; company house documents; CAS(American Chemical Society); investor presentations; and SEC filings of companies. Secondary research was used to identify and collect information useful for the extensive, technical, market-oriented, and Hospitals study of the Voluntary Carbon Offset market. It was also used to obtain important information about the top companies, market classification and segmentation according to industry trends to the bottom-most level, and key developments related to market and technology perspectives.

Market Size	Segmental value Geographic Penetration Product Adoption Rate for Different market	Journals, Websites, and Press Releases Annual Reports and SEC Filings Company Websites and Press Releases Public and Paid Databases Market Intellix Data Repository
Market Position of Top Company	Product Financials Geographic value Mix Total Company value Business/Segmental value Mix
Qualitative Analysis	Influence Factors Market Potential Market Risks and Opportunities Industry Trends Geographical Features Government Policies	Company Websites and Press Releases Public and Paid Databases Annual Reports Industry Associations Market Intellix Data Repository

Primary Sources

In the primary research process, various sources from both the supply and demand sides were interviewed to obtain qualitative and quantitative information for this report. The primary sources from the supply side include product Company (and their competitors), opinion leaders, industry experts, research institutions, distributors, dealer and traders, as well as the raw materials suppliers and producers, etc.

The primary sources from the demand side include industry experts such as business leaders, marketing and sales directors, technology and innovation directors, supply chain executive, end use (product buyers), and related key executives from various key companies and organizations operating in the global market.

Primary research was conducted to identify segmentation Type, product price range, product Application, key Company, raw materials supply and the downstream demand, industry status and outlook, and key market dynamics such as risks, influence factors, opportunities, market barriers, industry trends, and key player strategies.

Key Executives Interviewed

Key Data Information from Primary Sources

Primary Sources	Parameters	Key Data
Market Segments(by Application, by Type)	Value by Type Status and Forecast Value by Application Value by Regions, Status and Forecast (2021-2026)	Value Market Share by Type Value Growth Rate by Type Value by Application Percentage and Growth Rate by Application Value Growth Rate and Market Share by Regions Market Size Status and Forecast (2021-2026)
Total Market	Overall Size, Status and Forecast	Market Size Status and Forecast (2021-2026)