Global High Performance Computing for Automotive 麻豆原创 2024 by Company, Regions, Type and Application, Forecast to 2030

Publication ID:

GIR122401851

Publication Date:

December 5, 2024

Pages:

110

Publisher:

GIR

Countries:

Global [1]

USD 3,480.00

Software [2]

IT Services [3]

Computing & Electronics [4]

Description:

The global High Performance Computing for Automotive market size was valued at USD 1274.3 million in 2023 and is forecast to a readjusted size of USD 2325.9 million by 2030 with a CAGR of 9.0% during review period.
High performance computing platforms are the hardware guarantee for the development of automotive intelligence. With the continuous enrichment and upgrading of intelligent driving functions, the requirements for high-performance computing platforms from host manufacturers are constantly increasing, and the demand for high-performance computing chips is also gradually increasing. It is expected that the market size of high-performance computing for automobiles will continue to expand in the future.
The report includes an overview of the development of the High Performance Computing for Automotive industry chain, the market status of Automated Driving (Software, Hardware), Vehicle Safety & Motion (Software, Hardware), and key enterprises in developed and developing market, and analysed the cutting-edge technology, patent, hot applications and market trends of High Performance Computing for Automotive.
Regionally, the report analyzes the High Performance Computing for Automotive markets in key regions. North America and Europe are experiencing steady growth, driven by government initiatives and increasing consumer awareness. Asia-Pacific, particularly China, leads the global High Performance Computing for Automotive market, with robust domestic demand, supportive policies, and a strong manufacturing base.
Key Features:
The report presents comprehensive understanding of the High Performance Computing for Automotive market. It provides a holistic view of the industry, as well as detailed insights into individual components and stakeholders. The report analysis market dynamics, trends, challenges, and opportunities within the High Performance Computing for Automotive industry.
The report involves analyzing the market at a macro level:
麻豆原创 Sizing and Segmentation: Report collect data on the overall market size, including the revenue generated, and market share of different by Type (e.g., Software, Hardware).
Industry Analysis: Report analyse the broader industry trends, such as government policies and regulations, technological advancements, consumer preferences, and market dynamics. This analysis helps in understanding the key drivers and challenges influencing the High Performance Computing for Automotive market.
Regional Analysis: The report involves examining the High Performance Computing for Automotive market at a regional or national level. Report analyses regional factors such as government incentives, infrastructure development, economic conditions, and consumer behaviour to identify variations and opportunities within different markets.
麻豆原创 Projections: Report covers the gathered data and analysis to make future projections and forecasts for the High Performance Computing for Automotive market. This may include estimating market growth rates, predicting market demand, and identifying emerging trends.
The report also involves a more granular approach to High Performance Computing for Automotive:
Company Analysis: Report covers individual High Performance Computing for Automotive players, suppliers, and other relevant industry players. This analysis includes studying their financial performance, market positioning, product portfolios, partnerships, and strategies.
Consumer Analysis: Report covers data on consumer behaviour, preferences, and attitudes towards High Performance Computing for Automotive This may involve surveys, interviews, and analysis of consumer reviews and feedback from different by Application (Automated Driving, Vehicle Safety & Motion).
Technology Analysis: Report covers specific technologies relevant to High Performance Computing for Automotive. It assesses the current state, advancements, and potential future developments in High Performance Computing for Automotive areas.
Competitive Landscape: By analyzing individual companies, suppliers, and consumers, the report present insights into the competitive landscape of the High Performance Computing for Automotive market. This analysis helps understand market share, competitive advantages, and potential areas for differentiation among industry players.
麻豆原创 Validation: The report involves validating findings and projections through primary research, such as surveys, interviews, and focus groups.
麻豆原创 Segmentation
High Performance Computing for Automotive market is split by Type and by Application. For the period 2019-2030, the growth among segments provides accurate calculations and forecasts for consumption value by Type, and by Application in terms of value.
麻豆原创 segment by Type
Software
Hardware
Service
麻豆原创 segment by Application
Automated Driving
Vehicle Safety & Motion
Other
麻豆原创 segment by players, this report covers
NXP
Continental AG
Bosch
Microsoft
Rescale
NVIDIA
ZF Friedrichshafen AG
Amazon
BlackBerry
Huawei
Qualcomm
麻豆原创 segment by regions, regional analysis covers
North America (United States, Canada, and Mexico)
Europe (Germany, France, UK, Russia, Italy, and Rest of Europe)
Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Australia and Rest of Asia-Pacific)
South America (Brazil, Argentina and Rest of South America)
Middle East & Africa (Turkey, Saudi Arabia, UAE, Rest of Middle East & Africa)
The content of the study subjects, includes a total of 13 chapters:
Chapter 1, to describe High Performance Computing for Automotive product scope, market overview, market estimation caveats and base year.
Chapter 2, to profile the top players of High Performance Computing for Automotive, with revenue, gross margin and global market share of High Performance Computing for Automotive from 2019 to 2024.
Chapter 3, the High Performance Computing for Automotive competitive situation, revenue and global market share of top players are analyzed emphatically by landscape contrast.
Chapter 4 and 5, to segment the market size by Type and application, with consumption value and growth rate by Type, application, from 2019 to 2030.
Chapter 6, 7, 8, 9, and 10, to break the market size data at the country level, with revenue and market share for key countries in the world, from 2019 to 2024.and High Performance Computing for Automotive market forecast, by regions, type and application, with consumption value, from 2025 to 2030.
Chapter 11, market dynamics, drivers, restraints, trends and Porters Five Forces analysis.
Chapter 12, the key raw materials and key suppliers, and industry chain of High Performance Computing for Automotive.
Chapter 13, to describe High Performance Computing for Automotive research findings and conclusion.

Please Note - This is an on demand report and will be delivered in 2 business days (48 Hours) post payment.

Table Of Contents:

1 麻豆原创 Overview
1.1 Product Overview and Scope of High Performance Computing for Automotive
1.2 麻豆原创 Estimation Caveats and Base Year
1.3 Classification of High Performance Computing for Automotive by Type
1.3.1 Overview: Global High Performance Computing for Automotive 麻豆原创 Size by Type: 2019 Versus 2023 Versus 2030
1.3.2 Global High Performance Computing for Automotive Consumption Value 麻豆原创 Share by Type in 2023
1.3.3 Software
1.3.4 Hardware
1.3.5 Service
1.4 Global High Performance Computing for Automotive 麻豆原创 by Application
1.4.1 Overview: Global High Performance Computing for Automotive 麻豆原创 Size by Application: 2019 Versus 2023 Versus 2030
1.4.2 Automated Driving
1.4.3 Vehicle Safety & Motion
1.4.4 Other
1.5 Global High Performance Computing for Automotive 麻豆原创 Size & Forecast
1.6 Global High Performance Computing for Automotive 麻豆原创 Size and Forecast by Region
1.6.1 Global High Performance Computing for Automotive 麻豆原创 Size by Region: 2019 VS 2023 VS 2030
1.6.2 Global High Performance Computing for Automotive 麻豆原创 Size by Region, (2019-2030)
1.6.3 North America High Performance Computing for Automotive 麻豆原创 Size and Prospect (2019-2030)
1.6.4 Europe High Performance Computing for Automotive 麻豆原创 Size and Prospect (2019-2030)
1.6.5 Asia-Pacific High Performance Computing for Automotive 麻豆原创 Size and Prospect (2019-2030)
1.6.6 South America High Performance Computing for Automotive 麻豆原创 Size and Prospect (2019-2030)
1.6.7 Middle East and Africa High Performance Computing for Automotive 麻豆原创 Size and Prospect (2019-2030)
2 Company Profiles
2.1 NXP
2.1.1 NXP Details
2.1.2 NXP Major Business
2.1.3 NXP High Performance Computing for Automotive Product and Solutions
2.1.4 NXP High Performance Computing for Automotive Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.1.5 NXP Recent Developments and Future Plans
2.2 Continental AG
2.2.1 Continental AG Details
2.2.2 Continental AG Major Business
2.2.3 Continental AG High Performance Computing for Automotive Product and Solutions
2.2.4 Continental AG High Performance Computing for Automotive Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.2.5 Continental AG Recent Developments and Future Plans
2.3 Bosch
2.3.1 Bosch Details
2.3.2 Bosch Major Business
2.3.3 Bosch High Performance Computing for Automotive Product and Solutions
2.3.4 Bosch High Performance Computing for Automotive Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.3.5 Bosch Recent Developments and Future Plans
2.4 Microsoft
2.4.1 Microsoft Details
2.4.2 Microsoft Major Business
2.4.3 Microsoft High Performance Computing for Automotive Product and Solutions
2.4.4 Microsoft High Performance Computing for Automotive Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.4.5 Microsoft Recent Developments and Future Plans
2.5 Rescale
2.5.1 Rescale Details
2.5.2 Rescale Major Business
2.5.3 Rescale High Performance Computing for Automotive Product and Solutions
2.5.4 Rescale High Performance Computing for Automotive Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.5.5 Rescale Recent Developments and Future Plans
2.6 NVIDIA
2.6.1 NVIDIA Details
2.6.2 NVIDIA Major Business
2.6.3 NVIDIA High Performance Computing for Automotive Product and Solutions
2.6.4 NVIDIA High Performance Computing for Automotive Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.6.5 NVIDIA Recent Developments and Future Plans
2.7 ZF Friedrichshafen AG
2.7.1 ZF Friedrichshafen AG Details
2.7.2 ZF Friedrichshafen AG Major Business
2.7.3 ZF Friedrichshafen AG High Performance Computing for Automotive Product and Solutions
2.7.4 ZF Friedrichshafen AG High Performance Computing for Automotive Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.7.5 ZF Friedrichshafen AG Recent Developments and Future Plans
2.8 Amazon
2.8.1 Amazon Details
2.8.2 Amazon Major Business
2.8.3 Amazon High Performance Computing for Automotive Product and Solutions
2.8.4 Amazon High Performance Computing for Automotive Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.8.5 Amazon Recent Developments and Future Plans
2.9 BlackBerry
2.9.1 BlackBerry Details
2.9.2 BlackBerry Major Business
2.9.3 BlackBerry High Performance Computing for Automotive Product and Solutions
2.9.4 BlackBerry High Performance Computing for Automotive Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.9.5 BlackBerry Recent Developments and Future Plans
2.10 Huawei
2.10.1 Huawei Details
2.10.2 Huawei Major Business
2.10.3 Huawei High Performance Computing for Automotive Product and Solutions
2.10.4 Huawei High Performance Computing for Automotive Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.10.5 Huawei Recent Developments and Future Plans
2.11 Qualcomm
2.11.1 Qualcomm Details
2.11.2 Qualcomm Major Business
2.11.3 Qualcomm High Performance Computing for Automotive Product and Solutions
2.11.4 Qualcomm High Performance Computing for Automotive Revenue, Gross Margin and 麻豆原创 Share (2019-2024)
2.11.5 Qualcomm Recent Developments and Future Plans
3 麻豆原创 Competition, by Players
3.1 Global High Performance Computing for Automotive Revenue and Share by Players (2019-2024)
3.2 麻豆原创 Share Analysis (2023)
3.2.1 麻豆原创 Share of High Performance Computing for Automotive by Company Revenue
3.2.2 Top 3 High Performance Computing for Automotive Players 麻豆原创 Share in 2023
3.2.3 Top 6 High Performance Computing for Automotive Players 麻豆原创 Share in 2023
3.3 High Performance Computing for Automotive 麻豆原创: Overall Company Footprint Analysis
3.3.1 High Performance Computing for Automotive 麻豆原创: Region Footprint
3.3.2 High Performance Computing for Automotive 麻豆原创: Company Product Type Footprint
3.3.3 High Performance Computing for Automotive 麻豆原创: Company Product Application Footprint
3.4 New 麻豆原创 Entrants and Barriers to 麻豆原创 Entry
3.5 Mergers, Acquisition, Agreements, and Collaborations
4 麻豆原创 Size Segment by Type
4.1 Global High Performance Computing for Automotive Consumption Value and 麻豆原创 Share by Type (2019-2024)
4.2 Global High Performance Computing for Automotive 麻豆原创 Forecast by Type (2025-2030)
5 麻豆原创 Size Segment by Application
5.1 Global High Performance Computing for Automotive Consumption Value 麻豆原创 Share by Application (2019-2024)
5.2 Global High Performance Computing for Automotive 麻豆原创 Forecast by Application (2025-2030)
6 North America
6.1 North America High Performance Computing for Automotive Consumption Value by Type (2019-2030)
6.2 North America High Performance Computing for Automotive Consumption Value by Application (2019-2030)
6.3 North America High Performance Computing for Automotive 麻豆原创 Size by Country
6.3.1 North America High Performance Computing for Automotive Consumption Value by Country (2019-2030)
6.3.2 United States High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
6.3.3 Canada High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
6.3.4 Mexico High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
7 Europe
7.1 Europe High Performance Computing for Automotive Consumption Value by Type (2019-2030)
7.2 Europe High Performance Computing for Automotive Consumption Value by Application (2019-2030)
7.3 Europe High Performance Computing for Automotive 麻豆原创 Size by Country
7.3.1 Europe High Performance Computing for Automotive Consumption Value by Country (2019-2030)
7.3.2 Germany High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
7.3.3 France High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
7.3.4 United Kingdom High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
7.3.5 Russia High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
7.3.6 Italy High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
8 Asia-Pacific
8.1 Asia-Pacific High Performance Computing for Automotive Consumption Value by Type (2019-2030)
8.2 Asia-Pacific High Performance Computing for Automotive Consumption Value by Application (2019-2030)
8.3 Asia-Pacific High Performance Computing for Automotive 麻豆原创 Size by Region
8.3.1 Asia-Pacific High Performance Computing for Automotive Consumption Value by Region (2019-2030)
8.3.2 China High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
8.3.3 Japan High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
8.3.4 South Korea High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
8.3.5 India High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
8.3.6 Southeast Asia High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
8.3.7 Australia High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
9 South America
9.1 South America High Performance Computing for Automotive Consumption Value by Type (2019-2030)
9.2 South America High Performance Computing for Automotive Consumption Value by Application (2019-2030)
9.3 South America High Performance Computing for Automotive 麻豆原创 Size by Country
9.3.1 South America High Performance Computing for Automotive Consumption Value by Country (2019-2030)
9.3.2 Brazil High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
9.3.3 Argentina High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
10 Middle East & Africa
10.1 Middle East & Africa High Performance Computing for Automotive Consumption Value by Type (2019-2030)
10.2 Middle East & Africa High Performance Computing for Automotive Consumption Value by Application (2019-2030)
10.3 Middle East & Africa High Performance Computing for Automotive 麻豆原创 Size by Country
10.3.1 Middle East & Africa High Performance Computing for Automotive Consumption Value by Country (2019-2030)
10.3.2 Turkey High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
10.3.3 Saudi Arabia High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
10.3.4 UAE High Performance Computing for Automotive 麻豆原创 Size and Forecast (2019-2030)
11 麻豆原创 Dynamics
11.1 High Performance Computing for Automotive 麻豆原创 Drivers
11.2 High Performance Computing for Automotive 麻豆原创 Restraints
11.3 High Performance Computing for Automotive Trends Analysis
11.4 Porters Five Forces Analysis
11.4.1 Threat of New Entrants
11.4.2 Bargaining Power of Suppliers
11.4.3 Bargaining Power of Buyers
11.4.4 Threat of Substitutes
11.4.5 Competitive Rivalry
12 Industry Chain Analysis
12.1 High Performance Computing for Automotive Industry Chain
12.2 High Performance Computing for Automotive Upstream Analysis
12.3 High Performance Computing for Automotive Midstream Analysis
12.4 High Performance Computing for Automotive Downstream Analysis
13 Research Findings and Conclusion
14 Appendix
14.1 Methodology
14.2 Research Process and Data Source
14.3 Disclaimer

Companies Mentioned:

NXP
Continental AG
Bosch
Microsoft
Rescale
NVIDIA
ZF Friedrichshafen AG
Amazon
BlackBerry
Huawei
Qualcomm

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