Global (United States, European Union and China) GPU for Deep Learning Market Research Report 2019-2025
Table of Contents
1 Report Overview
- 1.1 Research Scope
- 1.2 Major Manufacturers Covered in This Report
- 1.3 Market Segment by Type
- 1.3.1 Global GPU for Deep Learning Market Size Growth Rate by Type (2019-2025)
- 1.3.2 RAM <4GB
- 1.3.3 RAM 4~8 GB
- 1.3.4 RAM 8~12GB
- 1.3.5 RAM >12GB
- 1.4 Market Segment by Application
- 1.4.1 Global GPU for Deep Learning Market Share by Application (2019-2025)
- 1.4.2 Personal Computers,
- 1.4.3 Workstations
- 1.4.4 Game Consoles
- 1.5 Study Objectives
- 1.6 Years Considered
2 Global Growth Trends
- 2.1 Production and Capacity Analysis
- 2.1.1 Global GPU for Deep Learning Production Value 2014-2025
- 2.1.2 Global GPU for Deep Learning Production 2014-2025
- 2.1.3 Global GPU for Deep Learning Capacity 2014-2025
- 2.1.4 Global GPU for Deep Learning Marketing Pricing and Trends
- 2.2 Key Producers Growth Rate (CAGR) 2019-2025
- 2.2.1 Global GPU for Deep Learning Market Size CAGR of Key Regions
- 2.2.2 Global GPU for Deep Learning Market Share of Key Regions
- 2.3 Industry Trends
- 2.3.1 Market Top Trends
- 2.3.2 Market Drivers
3 Market Share by Manufacturers
- 3.1 Capacity and Production by Manufacturers
- 3.1.1 Global GPU for Deep Learning Capacity by Manufacturers
- 3.1.2 Global GPU for Deep Learning Production by Manufacturers
- 3.2 Revenue by Manufacturers
- 3.2.1 GPU for Deep Learning Revenue by Manufacturers (2014-2019)
- 3.2.2 GPU for Deep Learning Revenue Share by Manufacturers (2014-2019)
- 3.2.3 Global GPU for Deep Learning Market Concentration Ratio (CR5 and HHI)
- 3.3 GPU for Deep Learning Price by Manufacturers
- 3.4 Key Manufacturers GPU for Deep Learning Plants/Factories Distribution and Area Served
- 3.5 Date of Key Manufacturers Enter into GPU for Deep Learning Market
- 3.6 Key Manufacturers GPU for Deep Learning Product Offered
- 3.7 Mergers & Acquisitions, Expansion Plans
4 Market Size by Type
- 4.1 Production and Production Value for Each Type
- 4.1.1 RAM <4GB Production and Production Value (2014-2019)
- 4.1.2 RAM 4~8 GB Production and Production Value (2014-2019)
- 4.1.3 RAM 8~12GB Production and Production Value (2014-2019)
- 4.1.4 RAM >12GB Production and Production Value (2014-2019)
- 4.2 Global GPU for Deep Learning Production Market Share by Type
- 4.3 Global GPU for Deep Learning Production Value Market Share by Type
- 4.4 GPU for Deep Learning Ex-factory Price by Type
5 Market Size by Application
- 5.1 Overview
- 5.2 Global GPU for Deep Learning Consumption by Application
6 Production by Regions
- 6.1 Global GPU for Deep Learning Production (History Data) by Regions 2014-2019
- 6.2 Global GPU for Deep Learning Production Value (History Data) by Regions
- 6.3 United States
- 6.3.1 United States GPU for Deep Learning Production Growth Rate 2014-2019
- 6.3.2 United States GPU for Deep Learning Production Value Growth Rate 2014-2019
- 6.3.3 Key Players in United States
- 6.3.4 United States GPU for Deep Learning Import & Export
- 6.4 European Union
- 6.4.1 European Union GPU for Deep Learning Production Growth Rate 2014-2019
- 6.4.2 European Union GPU for Deep Learning Production Value Growth Rate 2014-2019
- 6.4.3 Key Players in European Union
- 6.4.4 European Union GPU for Deep Learning Import & Export
- 6.5 China
- 6.5.1 China GPU for Deep Learning Production Growth Rate 2014-2019
- 6.5.2 China GPU for Deep Learning Production Value Growth Rate 2014-2019
- 6.5.3 Key Players in China
- 6.5.4 China GPU for Deep Learning Import & Export
- 6.6 Rest of World
- 6.6.1 Japan
- 6.6.2 Korea
- 6.6.3 India
- 6.6.4 Southeast Asia
7 GPU for Deep Learning Consumption by Regions
- 7.1 Global GPU for Deep Learning Consumption (History Data) by Regions
- 7.2 United States
- 7.2.1 United States GPU for Deep Learning Consumption by Type
- 7.2.2 United States GPU for Deep Learning Consumption by Application
- 7.3 European Union
- 7.3.1 European Union GPU for Deep Learning Consumption by Type
- 7.3.2 European Union GPU for Deep Learning Consumption by Application
- 7.4 China
- 7.4.1 China GPU for Deep Learning Consumption by Type
- 7.4.2 China GPU for Deep Learning Consumption by Application
- 7.5 Rest of World
- 7.5.1 Rest of World GPU for Deep Learning Consumption by Type
- 7.5.2 Rest of World GPU for Deep Learning Consumption by Application
- 7.5.1 Japan
- 7.5.2 Korea
- 7.5.3 India
- 7.5.4 Southeast Asia
8 Company Profiles
- 8.1 Nvidia
- 8.1.1 Nvidia Company Details
- 8.1.2 Company Description and Business Overview
- 8.1.3 Production and Revenue of GPU for Deep Learning
- 8.1.4 GPU for Deep Learning Product Introduction
- 8.1.5 Nvidia Recent Development
- 8.2 AMD
- 8.2.1 AMD Company Details
- 8.2.2 Company Description and Business Overview
- 8.2.3 Production and Revenue of GPU for Deep Learning
- 8.2.4 GPU for Deep Learning Product Introduction
- 8.2.5 AMD Recent Development
- 8.3 Intel
- 8.3.1 Intel Company Details
- 8.3.2 Company Description and Business Overview
- 8.3.3 Production and Revenue of GPU for Deep Learning
- 8.3.4 GPU for Deep Learning Product Introduction
- 8.3.5 Intel Recent Development
9 Market Forecast
- 9.1 Global Market Size Forecast
- 9.1.1 Global GPU for Deep Learning Capacity, Production Forecast 2019-2025
- 9.1.2 Global GPU for Deep Learning Production Value Forecast 2019-2025
- 9.2 Market Forecast by Regions
- 9.2.1 Global GPU for Deep Learning Production and Value Forecast by Regions 2019-2025
- 9.2.2 Global GPU for Deep Learning Consumption Forecast by Regions 2019-2025
- 9.3 United States
- 9.3.1 Production and Value Forecast in United States
- 9.3.2 Consumption Forecast in United States
- 9.4 European Union
- 9.4.1 Production and Value Forecast in European Union
- 9.4.2 Consumption Forecast in European Union
- 9.5 China
- 9.5.1 Production and Value Forecast in China
- 9.5.2 Consumption Forecast in China
- 9.6 Rest of World
- 9.6.1 Japan
- 9.6.2 Korea
- 9.6.3 India
- 9.6.4 Southeast Asia
- 9.7 Forecast by Type
- 9.7.1 Global GPU for Deep Learning Production Forecast by Type
- 9.7.2 Global GPU for Deep Learning Production Value Forecast by Type
- 9.8 Consumption Forecast by Application
10 Value Chain and Sales Channels Analysis
- 10.1 Value Chain Analysis
- 10.2 Sales Channels Analysis
- 10.2.1 GPU for Deep Learning Sales Channels
- 10.2.2 GPU for Deep Learning Distributors
- 10.3 GPU for Deep Learning Customers
11 Opportunities & Challenges, Threat and Affecting Factors
- 11.1 Market Opportunities
- 11.2 Market Challenges
- 11.3 Porter's Five Forces Analysis
12 Key Findings
13 Appendix
- 13.1 Research Methodology
- 13.1.1 Methodology/Research Approach
- 13.1.1.1 Research Programs/Design
- 13.1.1.2 Market Size Estimation
- 13.1.1.3 Market Breakdown and Data Triangulation
- 13.1.2 Data Source
- 13.1.2.1 Secondary Sources
- 13.1.2.2 Primary Sources
- 13.1.1 Methodology/Research Approach
- 13.2 Author Details
A graphics processing unit (GPU) is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device. GPUs are used in embedded systems, mobile phones, personal computers, workstations, and game consoles. Modern GPUs are very efficient at manipulating computer graphics and image processing, and their highly parallel structure makes them more efficient than general-purpose CPUs for algorithms where the processing of large blocks of data is done in parallel. In a personal computer, a GPU can be present on a video card, or it can be embedded on the motherboard or—in certain CPUs—on the CPU die.
In 2019, the market size of GPU for Deep Learning is xx million US$ and it will reach xx million US$ in 2025, growing at a CAGR of xx% from 2019; while in China, the market size is valued at xx million US$ and will increase to xx million US$ in 2025, with a CAGR of xx% during forecast period.
In this report, 2018 has been considered as the base year and 2019 to 2025 as the forecast period to estimate the market size for GPU for Deep Learning.
This report studies the global market size of GPU for Deep Learning, especially focuses on the key regions like United States, European Union, China, and other regions (Japan, Korea, India and Southeast Asia).
This study presents the GPU for Deep Learning production, revenue, market share and growth rate for each key company, and also covers the breakdown data (production, consumption, revenue and market share) by regions, type and applications. history breakdown data from 2014 to 2019, and forecast to 2025.
For top companies in United States, European Union and China, this report investigates and analyzes the production, value, price, market share and growth rate for the top manufacturers, key data from 2014 to 2019.
In global market, the following companies are covered:
Nvidia
AMD
Intel
...
Market Segment by Product Type
RAM <4GB
RAM 4~8 GB
RAM 8~12GB
RAM >12GB
Market Segment by Application
Personal Computers,
Workstations
Game Consoles
Key Regions split in this report: breakdown data for each region.
United States
China
European Union
Rest of World (Japan, Korea, India and Southeast Asia)
The study objectives are:
To analyze and research the GPU for Deep Learning status and future forecast in United States, European Union and China, involving sales, value (revenue), growth rate (CAGR), market share, historical and forecast.
To present the key GPU for Deep Learning manufacturers, presenting the sales, revenue, market share, and recent development for key players.
To split the breakdown data by regions, type, companies and applications
To analyze the global and key regions market potential and advantage, opportunity and challenge, restraints and risks.
To identify significant trends, drivers, influence factors in global and regions
To analyze competitive developments such as expansions, agreements, new product launches, and acquisitions in the market
In this study, the years considered to estimate the market size of GPU for Deep Learning are as follows:
History Year: 2014-2018
Base Year: 2018
Estimated Year: 2019
Forecast Year 2019 to 2025