Machine Learning in Chip Design - Global Market Share and Ranking, Overall Sales and Demand Forecast 2024-2030

Publication ID:

PB511244276

Publication Date:

November 26, 2024

Pages:

130

Publisher:

MRRPB5

Countries:

Global [1]

USD 3,950.00

IT Services [2]

Computing & Electronics [3]

Description:

The global market for Machine Learning in Chip Design was estimated to be worth US$ million in 2023 and is forecast to a readjusted size of US$ million by 2030 with a CAGR of % during the forecast period 2024-2030.
North American market for Machine Learning in Chip Design was valued at $ million in 2023 and will reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
Asia-Pacific market for Machine Learning in Chip Design was valued at $ million in 2023 and will reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
Europe market for Machine Learning in Chip Design was valued at $ million in 2023 and will reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
The global key companies of Machine Learning in Chip Design include IBM, Applied Materials, Siemens, Google(Alphabet), Cadence Design Systems, Synopsys, Intel, NVIDIA and Mentor Graphics, etc. In 2023, the global five largest players hold a share approximately % in terms of revenue.
Report Scope
This report aims to provide a comprehensive presentation of the global market for Machine Learning in Chip Design, focusing on the total sales revenue, key companies market share and ranking, together with an analysis of Machine Learning in Chip Design by region & country, by Type, and by Application.
The Machine Learning in Chip Design market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. 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 Machine Learning in Chip Design.
Market Segmentation
By Company
IBM
Applied Materials
Siemens
Google(Alphabet)
Cadence Design Systems
Synopsys
Intel
NVIDIA
Mentor Graphics
Flex Logix Technologies
Arm Limited
Kneron
Graphcore
Hailo
Groq
Mythic AI
Segment by Type:
Supervised Learning
Semi-supervised Learning
Unsupervised Learning
Reinforcement Learning
Segment by Application
IDM
Foundry
By Region
North America
United States
Canada
Europe
Germany
France
U.K.
Italy
Russia
Asia-Pacific
China
Japan
South Korea
China Taiwan
Southeast Asia
India
Latin America
Mexico
Brazil
Argentina
Middle East & Africa
Turkey
Saudi Arabia
UAE
Chapter Outline
Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides 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 2: Detailed analysis of Machine Learning in Chip Design manufacturers competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 3: 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 4: 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 5: Revenue of Machine Learning in Chip Design in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.
Chapter 6: Revenue of Machine Learning in Chip Design in country level. It provides sigmate data by Type, and by Application for each country/region.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.
Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: 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 Market Overview
1.1 Machine Learning in Chip Design Product Introduction
1.2 Global Machine Learning in Chip Design Market Size Forecast
1.3 Machine Learning in Chip Design Market Trends & Drivers
1.3.1 Machine Learning in Chip Design Industry Trends
1.3.2 Machine Learning in Chip Design Market Drivers & Opportunity
1.3.3 Machine Learning in Chip Design Market Challenges
1.3.4 Machine Learning in Chip Design Market Restraints
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Competitive Analysis by Company
2.1 Global Machine Learning in Chip Design Players Revenue Ranking (2023)
2.2 Global Machine Learning in Chip Design Revenue by Company (2019-2024)
2.3 Key Companies Machine Learning in Chip Design Manufacturing Base Distribution and Headquarters
2.4 Key Companies Machine Learning in Chip Design Product Offered
2.5 Key Companies Time to Begin Mass Production of Machine Learning in Chip Design
2.6 Machine Learning in Chip Design Market Competitive Analysis
2.6.1 Machine Learning in Chip Design Market Concentration Rate (2019-2024)
2.6.2 Global 5 and 10 Largest Companies by Machine Learning in Chip Design Revenue in 2023
2.6.3 Global Top Companies by Company Type (Tier 1, Tier 2, and Tier 3) & (based on the Revenue in Machine Learning in Chip Design as of 2023)
2.7 Mergers & Acquisitions, Expansion
3 Segmentation by Type
3.1 Introduction by Type
3.1.1 Supervised Learning
3.1.2 Semi-supervised Learning
3.1.3 Unsupervised Learning
3.1.4 Reinforcement Learning
3.2 Global Machine Learning in Chip Design Sales Value by Type
3.2.1 Global Machine Learning in Chip Design Sales Value by Type (2019 VS 2023 VS 2030)
3.2.2 Global Machine Learning in Chip Design Sales Value, by Type (2019-2030)
3.2.3 Global Machine Learning in Chip Design Sales Value, by Type (%) (2019-2030)
4 Segmentation by Application
4.1 Introduction by Application
4.1.1 IDM
4.1.2 Foundry
4.2 Global Machine Learning in Chip Design Sales Value by Application
4.2.1 Global Machine Learning in Chip Design Sales Value by Application (2019 VS 2023 VS 2030)
4.2.2 Global Machine Learning in Chip Design Sales Value, by Application (2019-2030)
4.2.3 Global Machine Learning in Chip Design Sales Value, by Application (%) (2019-2030)
5 Segmentation by Region
5.1 Global Machine Learning in Chip Design Sales Value by Region
5.1.1 Global Machine Learning in Chip Design Sales Value by Region: 2019 VS 2023 VS 2030
5.1.2 Global Machine Learning in Chip Design Sales Value by Region (2019-2024)
5.1.3 Global Machine Learning in Chip Design Sales Value by Region (2025-2030)
5.1.4 Global Machine Learning in Chip Design Sales Value by Region (%), (2019-2030)
5.2 North America
5.2.1 North America Machine Learning in Chip Design Sales Value, 2019-2030
5.2.2 North America Machine Learning in Chip Design Sales Value by Country (%), 2023 VS 2030
5.3 Europe
5.3.1 Europe Machine Learning in Chip Design Sales Value, 2019-2030
5.3.2 Europe Machine Learning in Chip Design Sales Value by Country (%), 2023 VS 2030
5.4 Asia Pacific
5.4.1 Asia Pacific Machine Learning in Chip Design Sales Value, 2019-2030
5.4.2 Asia Pacific Machine Learning in Chip Design Sales Value by Country (%), 2023 VS 2030
5.5 South America
5.5.1 South America Machine Learning in Chip Design Sales Value, 2019-2030
5.5.2 South America Machine Learning in Chip Design Sales Value by Country (%), 2023 VS 2030
5.6 Middle East & Africa
5.6.1 Middle East & Africa Machine Learning in Chip Design Sales Value, 2019-2030
5.6.2 Middle East & Africa Machine Learning in Chip Design Sales Value by Country (%), 2023 VS 2030
6 Segmentation by Key Countries/Regions
6.1 Key Countries/Regions Machine Learning in Chip Design Sales Value Growth Trends, 2019 VS 2023 VS 2030
6.2 Key Countries/Regions Machine Learning in Chip Design Sales Value
6.3 United States
6.3.1 United States Machine Learning in Chip Design Sales Value, 2019-2030
6.3.2 United States Machine Learning in Chip Design Sales Value by Type (%), 2023 VS 2030
6.3.3 United States Machine Learning in Chip Design Sales Value by Application, 2023 VS 2030
6.4 Europe
6.4.1 Europe Machine Learning in Chip Design Sales Value, 2019-2030
6.4.2 Europe Machine Learning in Chip Design Sales Value by Type (%), 2023 VS 2030
6.4.3 Europe Machine Learning in Chip Design Sales Value by Application, 2023 VS 2030
6.5 China
6.5.1 China Machine Learning in Chip Design Sales Value, 2019-2030
6.5.2 China Machine Learning in Chip Design Sales Value by Type (%), 2023 VS 2030
6.5.3 China Machine Learning in Chip Design Sales Value by Application, 2023 VS 2030
6.6 Japan
6.6.1 Japan Machine Learning in Chip Design Sales Value, 2019-2030
6.6.2 Japan Machine Learning in Chip Design Sales Value by Type (%), 2023 VS 2030
6.6.3 Japan Machine Learning in Chip Design Sales Value by Application, 2023 VS 2030
6.7 South Korea
6.7.1 South Korea Machine Learning in Chip Design Sales Value, 2019-2030
6.7.2 South Korea Machine Learning in Chip Design Sales Value by Type (%), 2023 VS 2030
6.7.3 South Korea Machine Learning in Chip Design Sales Value by Application, 2023 VS 2030
6.8 Southeast Asia
6.8.1 Southeast Asia Machine Learning in Chip Design Sales Value, 2019-2030
6.8.2 Southeast Asia Machine Learning in Chip Design Sales Value by Type (%), 2023 VS 2030
6.8.3 Southeast Asia Machine Learning in Chip Design Sales Value by Application, 2023 VS 2030
6.9 India
6.9.1 India Machine Learning in Chip Design Sales Value, 2019-2030
6.9.2 India Machine Learning in Chip Design Sales Value by Type (%), 2023 VS 2030
6.9.3 India Machine Learning in Chip Design Sales Value by Application, 2023 VS 2030
7 Company Profiles
7.1 IBM
7.1.1 IBM Profile
7.1.2 IBM Main Business
7.1.3 IBM Machine Learning in Chip Design Products, Services and Solutions
7.1.4 IBM Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.1.5 IBM Recent Developments
7.2 Applied Materials
7.2.1 Applied Materials Profile
7.2.2 Applied Materials Main Business
7.2.3 Applied Materials Machine Learning in Chip Design Products, Services and Solutions
7.2.4 Applied Materials Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.2.5 Applied Materials Recent Developments
7.3 Siemens
7.3.1 Siemens Profile
7.3.2 Siemens Main Business
7.3.3 Siemens Machine Learning in Chip Design Products, Services and Solutions
7.3.4 Siemens Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.3.5 Google(Alphabet) Recent Developments
7.4 Google(Alphabet)
7.4.1 Google(Alphabet) Profile
7.4.2 Google(Alphabet) Main Business
7.4.3 Google(Alphabet) Machine Learning in Chip Design Products, Services and Solutions
7.4.4 Google(Alphabet) Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.4.5 Google(Alphabet) Recent Developments
7.5 Cadence Design Systems
7.5.1 Cadence Design Systems Profile
7.5.2 Cadence Design Systems Main Business
7.5.3 Cadence Design Systems Machine Learning in Chip Design Products, Services and Solutions
7.5.4 Cadence Design Systems Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.5.5 Cadence Design Systems Recent Developments
7.6 Synopsys
7.6.1 Synopsys Profile
7.6.2 Synopsys Main Business
7.6.3 Synopsys Machine Learning in Chip Design Products, Services and Solutions
7.6.4 Synopsys Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.6.5 Synopsys Recent Developments
7.7 Intel
7.7.1 Intel Profile
7.7.2 Intel Main Business
7.7.3 Intel Machine Learning in Chip Design Products, Services and Solutions
7.7.4 Intel Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.7.5 Intel Recent Developments
7.8 NVIDIA
7.8.1 NVIDIA Profile
7.8.2 NVIDIA Main Business
7.8.3 NVIDIA Machine Learning in Chip Design Products, Services and Solutions
7.8.4 NVIDIA Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.8.5 NVIDIA Recent Developments
7.9 Mentor Graphics
7.9.1 Mentor Graphics Profile
7.9.2 Mentor Graphics Main Business
7.9.3 Mentor Graphics Machine Learning in Chip Design Products, Services and Solutions
7.9.4 Mentor Graphics Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.9.5 Mentor Graphics Recent Developments
7.10 Flex Logix Technologies
7.10.1 Flex Logix Technologies Profile
7.10.2 Flex Logix Technologies Main Business
7.10.3 Flex Logix Technologies Machine Learning in Chip Design Products, Services and Solutions
7.10.4 Flex Logix Technologies Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.10.5 Flex Logix Technologies Recent Developments
7.11 Arm Limited
7.11.1 Arm Limited Profile
7.11.2 Arm Limited Main Business
7.11.3 Arm Limited Machine Learning in Chip Design Products, Services and Solutions
7.11.4 Arm Limited Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.11.5 Arm Limited Recent Developments
7.12 Kneron
7.12.1 Kneron Profile
7.12.2 Kneron Main Business
7.12.3 Kneron Machine Learning in Chip Design Products, Services and Solutions
7.12.4 Kneron Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.12.5 Kneron Recent Developments
7.13 Graphcore
7.13.1 Graphcore Profile
7.13.2 Graphcore Main Business
7.13.3 Graphcore Machine Learning in Chip Design Products, Services and Solutions
7.13.4 Graphcore Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.13.5 Graphcore Recent Developments
7.14 Hailo
7.14.1 Hailo Profile
7.14.2 Hailo Main Business
7.14.3 Hailo Machine Learning in Chip Design Products, Services and Solutions
7.14.4 Hailo Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.14.5 Hailo Recent Developments
7.15 Groq
7.15.1 Groq Profile
7.15.2 Groq Main Business
7.15.3 Groq Machine Learning in Chip Design Products, Services and Solutions
7.15.4 Groq Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.15.5 Groq Recent Developments
7.16 Mythic AI
7.16.1 Mythic AI Profile
7.16.2 Mythic AI Main Business
7.16.3 Mythic AI Machine Learning in Chip Design Products, Services and Solutions
7.16.4 Mythic AI Machine Learning in Chip Design Revenue (US$ Million) & (2019-2024)
7.16.5 Mythic AI Recent Developments
8 Industry Chain Analysis
8.1 Machine Learning in Chip Design Industrial Chain
8.2 Machine Learning in Chip Design Upstream Analysis
8.2.1 Key Raw Materials
8.2.2 Raw Materials Key Suppliers
8.2.3 Manufacturing Cost Structure
8.3 Midstream Analysis
8.4 Downstream Analysis (Customers Analysis)
8.5 Sales Model and Sales Channels
8.5.1 Machine Learning in Chip Design Sales Model
8.5.2 Sales Channel
8.5.3 Machine Learning in Chip Design Distributors
9 Research Findings and Conclusion
10 Appendix
10.1 Research Methodology
10.1.1 Methodology/Research Approach
10.1.2 Data Source
10.2 Author Details
10.3 Disclaimer

Companies Mentioned:

IBM
Applied Materials
Siemens
Google(Alphabet)
Cadence Design Systems
Synopsys
Intel
NVIDIA
Mentor Graphics
Flex Logix Technologies
Arm Limited
Kneron
Graphcore
Hailo
Groq
Mythic AI

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