Data Center Chip Market by Offerings (GPU, CPU, FPGA, Trainium, Inferentia, T-head, Athena ASIC, MTIA, LPU, Memory (DRAM (HBM, DDR)), Network (NIC/Network Adapters, Interconnects)) – Global Forecast to 2030
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.
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.
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:
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%
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.
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
5.3.1.1 Generative AI
5.3.2 COMPLEMENTARY TECHNOLOGIES
5.3.2.1 Data center power management and cooling systems
5.3.3 ADJACENT TECHNOLOGIES
5.3.3.1 Quantum AI
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
12.1.8.3.1 Deals
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
12.1.11.3.1 Expansions
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
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
5.3.1.1 Generative AI
5.3.2 COMPLEMENTARY TECHNOLOGIES
5.3.2.1 Data center power management and cooling systems
5.3.3 ADJACENT TECHNOLOGIES
5.3.3.1 Quantum AI
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
12.1.8.3.1 Deals
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
12.1.11.3.1 Expansions
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
