Product Code: SE 9185
The global data center chip market is expected to grow from USD 206.96 billion in 2025 to USD 390.65 billion by 2030, growing at a CAGR of 13.5% from 2025 to 2030.
Scope of the Report |
Years Considered for the Study | 2020-2030 |
Base Year | 2023 |
Forecast Period | 2025-2030 |
Units Considered | Value (USD Billion) |
Segments | By Component, Application, Data Center Size, End User and Region |
Regions covered | North America, Europe, APAC, RoW |
The expansion of data center capacity is one of the primary drivers of growth in the data center chip market. With the growing demand for more digital services, organizations handle more significant volumes of data and are adopting emerging technologies, increasing the demand for data center capacity. This expansion comes from the proliferation of data-intensive applications, the birth of cloud computing, the rise in the number of IoT devices, and the trend of increased data-based decisions.
Generative AI in the Application segment to grow with the highest CAGR during the forecast period
The data center chip market is expected to experience a high growth rate in the Generative AI segment due to the rapid adoption of generative models such as GPT-4, DALL-E and Stable Diffusion across industries. In real-time, these models require massive computational power to generate high-quality content, such as text, images, and videos. The deployment of Generative AI for applications such as content creation, drug discovery, and design automation increases the demand for high-performance data center chips in various organizations. Companies like NVIDIA and AMD continue developing specific GPUs with highly improved tensor cores optimized to suit the parallel processing demands that the generative model requires. The growth in the market for custom AI accelerators, specially designed to fit generative tasks, such as those of Cerebras and Graphcore, is fueling its rapid growth. The capability to deal with the high computation of Generative AI models in reducing latency and energy consumption is a key factor fueling the accelerated growth in this market.
The AI processor is expected to have the largest market share in the processor market during the forecast period.
AI processor includes GPU, CPU, and FPGAs. Data center chips primarily contain the central processing unit, often called processors, as they have most of the computation work in executing processes to process data. These processors perform arithmetic and logical operations, perform input/output operations on the commands, and supervise the activities among other components in the data. Currently, the modern trend is for multicore processors with improvements in performance and decreasing power consumption through the execution of different tasks at a given time. A GPU is a powerful processor, which can handle multiple tasks simultaneously, making them ideal for accelerating complex computations, including machine learning, deep learning, and data analysis. It accelerates tasks that require lots of data and heavy processing, thus making it possible to execute big computing applications faster and more efficiently.
North America is expected to have the second-largest market during the forecast period.
North America took the second-largest market share of data center chip market share in 2024. The presence of prominent technology firms and data center operators is driving the market across the North American region. The region hosts companies such as NVIDIA Corporation (US), Intel Corporation (US), Advanced Micro Devices, Inc. (AMD) (US), and Google (US). Cloud service providers include Amazon Web Services, Inc. (AWS) (US), Microsoft Azure (US), and Google Cloud (US). These data centers are further backed by AI infrastructure to provide real-time services worldwide. The region also hosts several startups set up in the area for delivering data center chips for data centers, which include SAPEON Inc. (US), Tenstorrent (Canada), Taalas (Canada), Kneron, Inc. (US), SambaNova Systems, Inc. (US). Many modern data centers in this region are equipped with state-of-the-art AI hardware. The presence of large-scale data centers and leading data center chip developers in the area are driving the market growth.
In determining and verifying the market size for several segments and subsegments gathered through secondary research, extensive primary interviews have been conducted with key officials in the data center chip market. Following is the breakup of the profiles of the primary participants for the report.
- By Company Type: Tier 1 - 40 %, Tier 2 - 40%, and Tier 3 - 20%
- By Designation: Directors -40%, Managers- 40%, and Others - 20%
- By Region: North America- 40%, Asia Pacific - 20%, Europe- 30%, and RoW - 10%
The report profiles key players in the data center chip market and analyzes their market shares. Players profiled in this report are NVIDIA Corporation (US), Advanced Micro Devices, Inc. (AMD) (US), Intel Corporation (US), Micron Technology, Inc. (US), Google (US), SK HYNIX INC. (South Korea), AWS (US), Samsung (South Korea), Texas Instruments Incorporated (US), Alibaba (China), Analog Devices (US), Monolithic Power Systems, Inc., (US), STMicroelectronics (Switzerland), Sensirion AG (Switzerland), Honeywell International, Inc. (US), AKCP(US), Bosch Sensortec (Germany), Renesas Electronic Corporation (Japan), Infineon (Germany), Diodes Incorporated (US), Imagination Technologies (UK), Graphcore (UK), Cisco Systems, Inc. (US), Dell Inc. (US), Huawei Technologies Co., Ltd. (China).
Research Coverage
The report defines, describes, and forecasts the data center chip market based on component, data Center size, application, end-user, and region. It provides detailed information regarding drivers, restraints, opportunities, and challenges influencing its growth. It also analyzes competitive developments such as product launches, acquisitions, expansions, contracts, partnerships, and actions carried out by the key players to grow in the market.
Reasons to Buy This Report
The report will help market leaders and new entrants with information on the closest approximations of the revenue numbers for the overall data center chip market and the subsegments. It will also help stakeholders understand the competitive landscape and gain more insights to better position their businesses and plan suitable go-to-market strategies. The report also helps stakeholders understand the market pulse and provides information on key market drivers, restraints, challenges, and opportunities.
The report provides insights on the following pointers:
- Analysis of key drivers (Expansion of data center capacity, Surging demand for high data volumes and pressing need for fast and efficient data processing, Continuous advancement in machine learning and deep learning technologies, Rising focus on parallel computing in AI data center), restraints (Shortage of skilled professional, High cost associated with data center GPUs), opportunities (Emergence of sovereign AI, Emergence of FPGA-based Accelerator), and challenges (High energy consumption of data centers, Security concerns associated with data centers) influencing the growth of the data center chip market.
- Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the data center chip market
- Market Development: Comprehensive information about lucrative markets - the report analyses the data center chip market across varied regions
- Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the data center chip market
- Competitive Assessment: In-depth assessment of market shares, growth strategies, and offerings of leading players NVIDIA Corporation (US), Advanced Micro Devices, Inc. (US), Intel Corporation (US), Micron Technology, Inc. (US), SK HYNIX INC. (South Korea), among others in the data center chip market strategies.
TABLE OF CONTENTS
1 INTRODUCTION
- 1.1 STUDY OBJECTIVES
- 1.2 MARKET DEFINITION
- 1.3 STUDY SCOPE
- 1.3.1 MARKETS COVERED
- 1.3.2 INCLUSIONS AND EXCLUSIONS
- 1.3.3 YEARS CONSIDERED
- 1.4 CURRENCY CONSIDERED
- 1.5 UNIT CONSIDERED
- 1.6 LIMITATIONS
- 1.7 STAKEHOLDERS
2 RESEARCH METHODOLOGY
- 2.1 RESEARCH APPROACH
- 2.1.1 SECONDARY AND PRIMARY RESEARCH
- 2.1.2 SECONDARY DATA
- 2.1.2.1 List of key secondary sources
- 2.1.2.2 Key data from secondary sources
- 2.1.3 PRIMARY DATA
- 2.1.3.1 Key data from primary sources
- 2.1.3.2 List of primary interview participants
- 2.1.3.3 Breakdown of primaries
- 2.1.3.4 Key industry insights
- 2.2 MARKET SIZE ESTIMATION METHODOLOGY
- 2.2.1 BOTTOM-UP APPROACH
- 2.2.1.1 Approach to arrive at market size using bottom-up analysis (demand side)
- 2.2.2 TOP-DOWN APPROACH
- 2.2.2.1 Approach to arrive at market size using top-down analysis (supply side)
- 2.3 MARKET BREAKDOWN AND DATA TRIANGULATION
- 2.4 RESEARCH ASSUMPTIONS
- 2.5 RESEARCH LIMITATIONS
- 2.6 RISK ANALYSIS
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
- 4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN DATA CENTER CHIP MARKET
- 4.2 DATA CENTER CHIP MARKET, BY COMPONENT
- 4.3 DATA CENTER CHIP MARKET IN NORTH AMERICA, BY END USER AND COUNTRY
- 4.4 DATA CENTER CHIP MARKET, BY DATA CENTER SIZE
- 4.5 DATA CENTER CHIP MARKET, BY APPLICATION
- 4.6 DATA CENTER CHIP MARKET, BY COUNTRY
5 MARKET OVERVIEW
- 5.1 INTRODUCTION
- 5.2 MARKET DYNAMICS
- 5.2.1 DRIVERS
- 5.2.1.1 Rapid expansion of data center capacity
- 5.2.1.2 Rising need for low-latency and high-throughput data processing
- 5.2.1.3 Increasing deployment of machine learning and deep learning technologies
- 5.2.1.4 Growing emphasis on parallel computing in AI data centers
- 5.2.2 RESTRAINTS
- 5.2.2.1 Shortage of skilled workforce
- 5.2.2.2 High costs of data center GPUs
- 5.2.3 OPPORTUNITIES
- 5.2.3.1 Emergence of sovereign AI
- 5.2.3.2 Increasing adoption of FPGA-based accelerators
- 5.2.4 CHALLENGES
- 5.2.4.1 High energy consumption in data centers
- 5.2.4.2 Security concerns associated with data center hardware components
- 5.3 TECHNOLOGY ANALYSIS
- 5.3.1 KEY TECHNOLOGIES
- 5.3.2 COMPLEMENTARY TECHNOLOGIES
- 5.3.2.1 Data center power management and cooling systems
- 5.3.3 ADJACENT TECHNOLOGIES
- 5.4 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
- 5.5 PRICING ANALYSIS
- 5.5.1 INDICATIVE PRICING OF KEY PLAYERS, BY AI PROCESSOR, 2023
- 5.5.2 AVERAGE SELLING PRICE TREND, BY REGION, 2020-2023
- 5.6 VALUE CHAIN ANALYSIS
- 5.7 ECOSYSTEM ANALYSIS
- 5.8 INVESTMENT AND FUNDING SCENARIO
- 5.9 PATENT ANALYSIS
- 5.10 TRADE ANALYSIS
- 5.10.1 IMPORT SCENARIO (HS CODE 854231)
- 5.10.2 EXPORT SCENARIO (HS CODE 854231)
- 5.11 TARIFF AND REGULATORY LANDSCAPE
- 5.11.1 TARIFF ANALYSIS
- 5.11.2 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
- 5.11.3 STANDARDS
- 5.11.3.1 US
- 5.11.3.2 Europe
- 5.11.3.3 China
- 5.11.3.4 Japan
- 5.12 KEY CONFERENCES AND EVENTS, 2024-2025
- 5.13 CASE STUDY ANALYSIS
- 5.13.1 STMICROELECTRONICS DEPLOYS AMD EPYC PROCESSORS TO ENHANCE R&D DATA CENTER PERFORMANCE
- 5.13.2 JOCDN ADOPTS AMD EPYC PROCESSORS TO IMPROVE BROADCAST VIDEO STREAMING CAPABILITIES
- 5.13.3 DBS BANK LEVERAGES DELL SERVERS POWERED BY AMD EPYC PROCESSORS TO TRANSFORM DATA CENTER INFRASTRUCTURE
- 5.14 PORTER'S FIVE FORCES ANALYSIS
- 5.14.1 INTENSITY OF COMPETITIVE RIVALRY
- 5.14.2 BARGAINING POWER OF SUPPLIERS
- 5.14.3 BARGAINING POWER OF BUYERS
- 5.14.4 THREAT OF SUBSTITUTES
- 5.14.5 THREAT OF NEW ENTRANTS
- 5.15 KEY STAKEHOLDERS AND BUYING CRITERIA
- 5.15.1 KEY STAKEHOLDERS IN BUYING PROCESS
- 5.15.2 BUYING CRITERIA
- 5.16 IMPACT OF AI/GEN AI ON DATA CENTER CHIP MARKET
6 DATA CENTER CHIP MARKET, BY COMPONENT
- 6.1 INTRODUCTION
- 6.2 PROCESSORS
- 6.2.1 AI PROCESSOR
- 6.2.2 GENERAL-PURPOSE COMPUTING PROCESSOR
- 6.2.2.1 GPU
- 6.2.2.1.1 Ability to handle AI workloads and process vast data volumes to boost adoption
- 6.2.2.2 CPU
- 6.2.2.2.1 Rising demand for versatile and general-purpose AI processing to augment market growth
- 6.2.2.3 FPGA
- 6.2.2.3.1 Growing need for flexibility and customization for AI workloads to spur demand
- 6.2.2.4 DOJO & FSD
- 6.2.2.4.1 High demand for high-performance, energy-efficient AI processing in autonomous vehicles to fuel adoption
- 6.2.2.5 Trainium & Inferentia
- 6.2.2.5.1 Ability to train complex AI and deep learning models to drive adoption
- 6.2.2.6 Athena ASIC
- 6.2.2.6.1 Increasing need to handle complex NLP and language-based AI tasks to accelerate market growth
- 6.2.2.7 T-Head
- 6.2.2.7.1 Rising demand for customized, high-performance AI chips across Chinese data centers to stimulate market growth
- 6.2.2.8 MTIA
- 6.2.2.8.1 Meta's expansion into AR, VR, and Metaverse to fuel market growth
- 6.2.2.9 LPU
- 6.2.2.9.1 Increasing need to handle complex NLP and language-based AI tasks to accelerate market growth
- 6.2.2.10 Other ASIC
- 6.3 MEMORY
- 6.3.1 DDR
- 6.3.1.1 Rising adoption of AI-enabled CPUs in data centers to support market growth
- 6.3.2 HBM
- 6.3.2.1 Elevating need for high throughput in data-intensive AI tasks to fuel market growth
- 6.4 NETWORK
- 6.4.1 NIC/NETWORK ADAPTERS
- 6.4.1.1 InfiniBand
- 6.4.1.1.1 Growing utilization of HPC and AI models to minimize latency and maximize throughput to boost segmental growth
- 6.4.1.2 Ethernet
- 6.4.1.2.1 Rising demand for scalable and cost-effective networking solutions to propel growth
- 6.4.1.3 Others
- 6.4.2 INTERCONNECTS
- 6.4.2.1 Growing complexity of AI models requiring high-bandwidth data paths to fuel demand
- 6.5 SENSORS
- 6.5.1 TEMPERATURE SENSOR
- 6.5.1.1 Increased requirement for optimal operational efficiency to drive demand for temperature sensor
- 6.5.2 HUMIDITY SENSOR
- 6.5.2.1 Growing awareness of environmental factors driving adoption of humidity monitoring
- 6.5.3 AIRFLOW SENSOR
- 6.5.3.1 Increasing server racks to drive market for airflow sensor
- 6.5.4 OTHER SENSORS
- 6.6 POWER MANAGEMENT
- 6.6.1 MULTIPHASE CONTROLLER
- 6.6.1.1 Need to manage and optimize performance to drive segmental growth
- 6.6.2 POINT-OF-LOAD (POL) (DC/DC CONVERTER)
- 6.6.2.1 Increasing demand for energy efficiency and high-performance computing to fuel market growth
- 6.6.3 LOW DROPOUT (LDO)
- 6.6.3.1 Ability to maintain stable output voltage to drive demand
- 6.6.4 48V INTERMEDIATE BUS CONVERTER (IBC)
- 6.6.4.1 Helps ensure adequate supply of efficient power management
- 6.6.5 HOT SWAP CONTROLLER/EFUSE
- 6.6.5.1 Increasing demand for low latency in data centers to drive market for hot swap controller
- 6.6.6 POWER SEQUENCER
- 6.6.6.1 Helps regulate power-up sequence of different voltage rails
- 6.6.7 BASEBOARD MANAGEMENT CONTROLLER (BMC)
- 6.6.7.1 Increasing demand for remote monitoring and management of server hardware to drive market
- 6.7 ANALOG & MIXED-SIGNAL ICS
- 6.7.1 MULTICHANNEL ADC/DAC
- 6.7.1.1 Converters used to provide efficient control of data generated from various sensors
- 6.7.2 MULTICHANNEL ADC/DAC
- 6.7.2.1 Helps in high-speed data transfer among other components in data center chip
- 6.7.3 MUX
- 6.7.3.1 Helps in streaming between multiple data center server
- 6.7.4 CURRENT SENSOR AMPLIFIER
- 6.7.4.1 Necessity for monitoring power consumption to drive demand
- 6.7.5 SUPERVISORY ICS
- 6.7.5.1 Need for stabilization of power supply to fuel market growth
- 6.7.6 FAN CONTROLLER
- 6.7.6.1 Increasing scale and performance of data centers creating demand for fan controllers
- 6.7.7 CLOCK IC
- 6.7.7.1 Importance of stable high-speed data transfer to support market growth
7 DATA CENTER CHIP MARKET, BY DATA CENTER SIZE
- 7.1 INTRODUCTION
- 7.2 SMALL DATA CENTERS
- 7.2.1 NEED FOR EDGE, COMPUTING, COST EFFICIENCY, SCALABILITY, AND RAPID DEPLOYMENT TO DRIVE MARKET
- 7.3 MEDIUM-SIZED DATA CENTERS
- 7.3.1 REDUNDANCY AND HIGH AVAILABILITY FEATURES TO DRIVE DEMAND
- 7.4 LARGE DATA CENTERS
- 7.4.1 NEED FOR MASSIVE DATA PROCESSING, CLOUD COMPUTING, SCALABILITY, AND HIGH AVAILABILITY TO DRIVE MARKET
8 DATA CENTER CHIP MARKET, BY APPLICATION
- 8.1 INTRODUCTION
- 8.2 GENERATIVE AI
- 8.2.1 RULE-BASED MODELS
- 8.2.1.1 Rising need to detect fraud in finance sector to propel market
- 8.2.2 STATISTICAL MODELS
- 8.2.2.1 Requirement to make accurate predictions from complex data structures to boost segmental growth
- 8.2.3 DEEP LEARNING
- 8.2.3.1 Ability to advance AI technologies to boost demand
- 8.2.4 GENERATIVE ADVERSARIAL NETWORKS (GAN)
- 8.2.4.1 Pressing needs to handle large-scale data to fuel segmental growth
- 8.2.5 AUTOENCODERS
- 8.2.5.1 Ability to compress and restructure data to ensure optimum storage space in data centers to stimulate demand
- 8.2.6 CONVOLUTIONAL NEURAL NETWORKS (CNNS)
- 8.2.6.1 Surging demand for realistic and high-quality images and videos to accelerate market growth
- 8.2.7 TRANSFORMER MODELS
- 8.2.7.1 Increasing utilization in image synthesis and captioning applications to foster segmental growth
- 8.2.8 MACHINE LEARNING
- 8.2.8.1 Rising use in image and speech recognition and predictive analytics to contribute to market growth
- 8.2.9 NATURAL LANGUAGE PROCESSING
- 8.2.9.1 Increasing need for real-time applications to support market growth
- 8.2.10 COMPUTER VISION
- 8.2.10.1 Escalating need for advanced processing capabilities to boost demand
- 8.3 GENERAL-PURPOSE COMPUTING
9 DATA CENTER CHIP MARKET, BY END USER
- 9.1 INTRODUCTION
- 9.2 CLOUD SERVICE PROVIDERS
- 9.2.1 SURGING AI WORKLOADS AND CLOUD ADOPTION TO STIMULATE MARKET GROWTH
- 9.3 ENTERPRISES
- 9.3.1 ESCALATING USE OF NLP, IMAGE RECOGNITION, AND PREDICTIVE ANALYTICS TO CREATE GROWTH OPPORTUNITIES
- 9.3.2 HEALTHCARE
- 9.3.2.1 Integration of AI in computer-aided drug discovery and development to foster market growth
- 9.3.3 BFSI
- 9.3.3.1 Surging need for fraud detection in financial institutions to boost demand
- 9.3.4 AUTOMOTIVE
- 9.3.4.1 Growing focus on safe and enhanced driving experiences to fuel demand
- 9.3.5 RETAIL & E-COMMERCE
- 9.3.5.1 Increasing use of chatbots and virtual assistants to offer improved customer services to drive market
- 9.3.6 MEDIA & ENTERTAINMENT
- 9.3.6.1 Real-time analysis of viewer preferences and demographic information to augment market growth
- 9.3.7 OTHERS
- 9.4 GOVERNMENT ORGANIZATIONS
- 9.4.1 FOCUS ON AUTOMATING ROUTINE TASKS AND EXTRACTING REAL-TIME INSIGHTS TO SUPPORT MARKET GROWTH
10 DATA CENTER CHIP MARKET, BY REGION
- 10.1 INTRODUCTION
- 10.2 NORTH AMERICA
- 10.2.1 MACROECONOMIC OUTLOOK FOR NORTH AMERICA
- 10.2.2 US
- 10.2.2.1 Rising demand for digital solutions to drive market
- 10.2.3 CANADA
- 10.2.3.1 Growing digital transformation and 5G services to support market growth
- 10.2.4 MEXICO
- 10.2.4.1 Government-led initiatives to ensure connectivity within urban centers to boost demand
- 10.3 EUROPE
- 10.3.1 MACROECONOMIC OUTLOOK FOR EUROPE
- 10.3.2 GERMANY
- 10.3.2.1 Adoption of industry 4.0 and advancement in technology infrastructure to drive market
- 10.3.3 UK
- 10.3.3.1 Increasing adoption of data centers and HPC by various verticals to support market growth
- 10.3.4 FRANCE
- 10.3.4.1 Federal support to promote data center infrastructure to augment market growth
- 10.3.5 REST OF EUROPE
- 10.4 ASIA PACIFIC
- 10.4.1 MACROECONOMIC OUTLOOK FOR ASIA PACIFIC
- 10.4.2 CHINA
- 10.4.2.1 Rising demand for high-speed data processing to accelerate market growth
- 10.4.3 JAPAN
- 10.4.3.1 Surge in adoption of data-intensive technologies like AI and IoT to drive market
- 10.4.4 INDIA
- 10.4.4.1 Government initiatives to boost AI infrastructure to foster market growth
- 10.4.5 REST OF ASIA PACIFIC
- 10.5 ROW
- 10.5.1 MACROECONOMIC OUTLOOK FOR ROW
- 10.5.2 SOUTH AMERICA
- 10.5.2.1 Strong government support to develop network infrastructure to boost demand
- 10.5.3 MIDDLE EAST & AFRICA
- 10.5.3.1 GCC countries
- 10.5.3.2 Rest of Middle East & Africa
11 COMPETITIVE LANDSCAPE
- 11.1 OVERVIEW
- 11.2 KEY PLAYERS' STRATEGIES/RIGHT TO WIN, 2021-2024
- 11.3 REVENUE ANALYSIS, 2021-2023
- 11.4 MARKET SHARE ANALYSIS, 2023
- 11.5 COMPANY VALUATION AND FINANCIAL METRICS, 2024
- 11.6 BRAND/PRODUCT COMPARISON
- 11.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
- 11.7.1 STARS
- 11.7.2 EMERGING LEADERS
- 11.7.3 PERVASIVE PLAYERS
- 11.7.4 PARTICIPANTS
- 11.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023
- 11.7.5.1 Company footprint
- 11.7.5.2 Region footprint
- 11.7.5.3 Component footprint
- 11.7.5.4 End user footprint
- 11.7.5.5 Application footprint
- 11.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023
- 11.8.1 PROGRESSIVE COMPANIES
- 11.8.2 RESPONSIVE COMPANIES
- 11.8.3 DYNAMIC COMPANIES
- 11.8.4 STARTING BLOCKS
- 11.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023
- 11.8.5.1 Detailed list of key startups/SMEs
- 11.8.5.2 Competitive benchmarking of key startups/SMEs
- 11.9 COMPETITIVE SCENARIO
- 11.9.1 PRODUCT LAUNCHES
- 11.9.2 DEALS
- 11.9.3 OTHER DEVELOPMENTS
12 COMPANY PROFILES
- 12.1 KEY PLAYERS
- 12.1.1 NVIDIA CORPORATION
- 12.1.1.1 Business overview
- 12.1.1.2 Products/Solutions/Services offered
- 12.1.1.3 Recent developments
- 12.1.1.3.1 Product launches
- 12.1.1.3.2 Deals
- 12.1.1.4 MnM view
- 12.1.1.4.1 Key strengths/Right to win
- 12.1.1.4.2 Strategic choices
- 12.1.1.4.3 Weaknesses/Competitive threats
- 12.1.2 ADVANCED MICRO DEVICES, INC.
- 12.1.2.1 Business overview
- 12.1.2.2 Products/Solutions/Services offered
- 12.1.2.3 Recent developments
- 12.1.2.3.1 Product launches
- 12.1.2.3.2 Deals
- 12.1.2.4 MnM view
- 12.1.2.4.1 Key strengths/Right to win
- 12.1.2.4.2 Strategic choices
- 12.1.2.4.3 Weaknesses/Competitive threats
- 12.1.3 INTEL CORPORATION
- 12.1.3.1 Business overview
- 12.1.3.2 Products/Solutions/Services offered
- 12.1.3.3 Recent developments
- 12.1.3.3.1 Product launches
- 12.1.3.3.2 Deals
- 12.1.3.4 MnM view
- 12.1.3.4.1 Key strengths/Right to win
- 12.1.3.4.2 Strategic choices
- 12.1.3.4.3 Weaknesses/Competitive threats
- 12.1.4 SAMSUNG
- 12.1.4.1 Business overview
- 12.1.4.2 Products/Solutions/Services offered
- 12.1.4.3 Recent developments
- 12.1.4.3.1 Product launches
- 12.1.4.3.2 Deals
- 12.1.4.4 MnM view
- 12.1.4.4.1 Key strengths/Right to win
- 12.1.4.4.2 Strategic choices
- 12.1.4.4.3 Weaknesses/Competitive threats
- 12.1.5 SK HYNIX INC.
- 12.1.5.1 Business overview
- 12.1.5.2 Products/Solutions/Services offered
- 12.1.5.3 Recent developments
- 12.1.5.3.1 Product launches
- 12.1.5.3.2 Deals
- 12.1.5.3.3 Other developments
- 12.1.5.4 MnM view
- 12.1.5.4.1 Key strengths/Right to win
- 12.1.5.4.2 Strategic choices
- 12.1.5.4.3 Weaknesses/Competitive threats
- 12.1.6 GOOGLE
- 12.1.6.1 Business overview
- 12.1.6.2 Products/Solutions/Services offered
- 12.1.6.3 Recent developments
- 12.1.6.3.1 Product launches
- 12.1.6.3.2 Deals
- 12.1.7 AMAZON WEB SERVICES, INC.
- 12.1.7.1 Business overview
- 12.1.7.2 Products/Solutions/Services offered
- 12.1.7.3 Recent developments
- 12.1.7.3.1 Product launches
- 12.1.7.3.2 Deals
- 12.1.8 MONOLITHIC POWER SYSTEMS, INC
- 12.1.8.1 Business overview
- 12.1.8.2 Products/Solutions/Services Offered
- 12.1.8.3 Recent developments
- 12.1.9 TEXAS INSTRUMENTS INCORPORATED
- 12.1.9.1 Business overview
- 12.1.9.2 Products/Solutions/Services offered
- 12.1.9.3 Recent developments
- 12.1.9.3.1 Other developments
- 12.1.10 MICRON TECHNOLOGY, INC.
- 12.1.10.1 Business overview
- 12.1.10.2 Products/Solutions/Services offered
- 12.1.10.3 Recent developments
- 12.1.10.3.1 Product launches
- 12.1.10.3.2 Deals
- 12.1.11 ANALOG DEVICES, INC.
- 12.1.11.1 Business overview
- 12.1.11.2 Products/Solutions/Services offered
- 12.1.11.3 Recent developments
- 12.1.12 MICROSOFT
- 12.1.12.1 Business overview
- 12.1.12.2 Products/Solutions/Services offered
- 12.1.12.3 Recent developments
- 12.1.12.3.1 Product launches
- 12.1.12.3.2 Deals
- 12.2 OTHER PLAYERS
- 12.2.1 IMAGINATION TECHNOLOGIES
- 12.2.2 GRAPHCORE
- 12.2.3 CEREBRAS SYSTEMS INC.
- 12.2.4 GROQ, INC.
- 12.2.5 TESLA
- 12.2.6 STMICROELECTRONICS
- 12.2.7 SENSIRION AG
- 12.2.8 AKCP
- 12.2.9 BOSCH SENSORTEC GMBH
- 12.2.10 RENESAS ELECTRONICS CORPORATION
- 12.2.11 INFINEON TECHNOLOGIES AG
- 12.2.12 DIODES INCORPORATED
- 12.2.13 MICROCHIP TECHNOLOGY INC.
- 12.2.14 HUAWEI TECHNOLOGIES CO., LTD.
- 12.2.15 T-HEAD
- 12.2.16 BLAIZE
- 12.2.17 HAILO TECHNOLOGIES LTD
- 12.2.18 KNERON, INC.
- 12.2.19 TENSTORRENT
- 12.2.20 TAALAS
- 12.2.21 SAPEON INC.
- 12.2.22 REBELLIONS INC.
13 APPENDIX
- 13.1 DISCUSSION GUIDE
- 13.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
- 13.3 CUSTOMIZATION OPTIONS
- 13.4 RELATED REPORTS
- 13.5 AUTHOR DETAILS