This report provides a comprehensive analysis of the global data center chip market, forecasting significant growth driven by expanding data center capacities and the surge in digital services. A primary growth engine is the rapid adoption of generative AI, which necessitates high-performance chips and specialized AI processors like GPUs to handle massive computational workloads. While North America maintains a dominant market presence due to leading technology firms, the report also explores regional trends, competitive landscapes, and key technological advancements.

Market Overview

The global data center chip market is projected to grow from USD 206.96 billion in 2025 to USD 390.65 billion by 2030, expanding at a compound annual growth rate (CAGR) of 13.5% during the forecast period from 2025 to 2030.

Market Growth Drivers

The expansion of data center capacity serves as one of the primary drivers for the market. As organizations handle increasingly significant volumes of data and adopt emerging technologies to meet the growing demand for digital services, the requirement for data center capacity rises. This expansion is fueled by several factors:

• The proliferation of data-intensive applications.
• The birth of cloud computing.
• The rise in the number of IoT devices.
• The increasing trend of data-based decision-making.

Segment Analysis

Application: Generative AI

The Generative AI segment is expected to experience the highest CAGR during the forecast period. This rapid growth is driven by the widespread adoption of generative models such as GPT-4, DALL-E, and Stable Diffusion across various industries.

• Computational Requirements: These models require massive computational power in real-time to generate high-quality text, images, and videos.
• Use Cases: Deployment for content creation, drug discovery, and design automation increases the demand for high-performance data center chips.
• Technological Advancements: Companies like NVIDIA and AMD are developing specialized GPUs with improved tensor cores optimized for the parallel processing demands of generative models. Additionally, the market for custom AI accelerators designed specifically for generative tasks—such as those from Cerebras and Graphcore—is fueling rapid growth.
• Efficiency Factors: The ability to manage high computation for Generative AI models while reducing latency and energy consumption is a key driver for this segment.

Processor Market

The AI processor segment is expected to hold the largest market share within the processor market during the forecast period.

• Components: The AI processor category includes GPUs, CPUs, and FPGAs.
• Central Processing Units (CPUs): Data center chips primarily contain CPUs, which handle the bulk of computation, perform arithmetic and logical operations, execute input/output operations on commands, and supervise activities among other components.
• Modern Trends: There is a shift toward multicore processors that improve performance and decrease power consumption by executing multiple tasks simultaneously.
• Graphics Processing Units (GPUs): GPUs are powerful processors capable of handling multiple tasks simultaneously, making them ideal for accelerating complex computations such as machine learning, deep learning, and data analysis. They accelerate data-heavy tasks, enabling big computing applications to run faster and more efficiently.

Regional Analysis: North America

North America is expected to hold the second-largest market share during the forecast period, having held the second-largest share in 2024. Market growth in this region is driven by the presence of prominent technology firms, data center operators, and large-scale data centers equipped with state-of-the-art AI hardware.

• Key Technology & Chip Firms:
• NVIDIA Corporation (US)
• Intel Corporation (US)
• Advanced Micro Devices, Inc. (AMD) (US)
• Google (US)
• Cloud Service Providers:
• Amazon Web Services, Inc. (AWS) (US)
• Microsoft Azure (US)
• Google Cloud (US)
• Emerging Startups & Specialized Providers:
• SAPEON Inc. (US)
• Tenstorrent (Canada)
• Taalas (Canada)
• Kneron, Inc. (US)
• SambaNova Systems, Inc. (US)

Research Methodology

To determine and verify market sizes for various segments and subsegments through secondary research, extensive primary interviews were conducted with key officials in the data center chip market.

Profile of Primary Participants

• By Company Type:
• Tier 1: 40%
• Tier 2: 40%
• Tier 3: 20%
• By Designation:
• Directors: 40%
• Managers: 40%
• Others: 20%
• By Region:
• North America: 40%
• Europe: 30%
• Asia Pacific: 20%
• Rest of World (RoW): 10%

Competitive Landscape

The report profiles key players and analyzes their market shares. The following companies are profiled:

• Alibaba (China)
• AKCP (US)
• Analog Devices (US)
• Advanced Micro Devices, Inc. (AMD) (US)
• AWS (US)
• Bosch Sensortec (Germany)
• Cisco Systems, Inc. (US)
• Dell Inc. (US)
• Diodes Incorporated (US)
• Google (US)
• Graphcore (UK)
• Huawei Technologies Co., Ltd. (China)
• Honeywell International, Inc. (US)
• Imagination Technologies (UK)
• Intel Corporation (US)
• Infineon (Germany)
• Micron Technology, Inc. (US)
• Monolithic Power Systems, Inc. (US)
• NVIDIA Corporation (US)
• Renesas Electronic Corporation (Japan)
• Samsung (South Korea)
• Sensirion AG (Switzerland)
• SK HYNIX INC. (South Korea)
• STMicroelectronics (Switzerland)
• Texas Instruments Incorporated (US)

Research Coverage

The report defines, describes, and forecasts the data center chip market based on the following criteria:

• Segmentation: Component, Data Center Size, Application, End-user, and Region.
• Market Dynamics: Drivers, restraints, opportunities, and challenges.
• Competitive Intelligence: Product launches, acquisitions, expansions, contracts, partnerships, and strategic actions taken by key players.

Strategic Insights for Stakeholders

Reasons to Purchase This Report

This report serves as a guide for market leaders and new entrants by providing:

• Closest approximations of revenue numbers for the overall market and its subsegments.
• Insights into the competitive landscape to assist in business positioning and go-to-market strategies.
• An understanding of the market pulse through key drivers, restraints, challenges, and opportunities.

Key Analysis Pointers

• Market Dynamics:
• Drivers: Expansion of data center capacity; surging demand for high data volumes and the need for fast/efficient processing; continuous advancement in machine learning and deep learning; rising focus on parallel computing in AI data centers.
• Restraints: Shortage of skilled professionals; high costs associated with data center GPUs.
• Opportunities: Emergence of sovereign AI; emergence of FPGA-based accelerators.
• Challenges: High energy consumption of data centers; security concerns associated with data centers.
• Product Development & Innovation: Detailed insights into upcoming technologies, R&D activities, and new product/service launches.
• Market Development: Comprehensive analysis of lucrative markets across varied regions.
• Market Diversification: Exhaustive information regarding new products, services, untapped geographies, recent developments, and investments.
• Competitive Assessment: In-depth assessment of market shares, growth strategies, and offerings of leading players, including NVIDIA Corporation (US), Advanced Micro Devices, Inc. (US), Intel Corporation (US), Micron Technology, Inc. (US), and SK HYNIX INC. (South Korea).

• 1 INTRODUCTION 29

  • 1.1 STUDY OBJECTIVES 29

  • 1.2 MARKET DEFINITION 29

  • 1.3 STUDY SCOPE 30

    • 1.3.1 MARKETS COVERED 30

    • 1.3.2 INCLUSIONS AND EXCLUSIONS 31

    • 1.3.3 YEARS CONSIDERED 31

  • 1.4 CURRENCY CONSIDERED 32

  • 1.5 UNIT CONSIDERED 32

  • 1.6 LIMITATIONS 32

  • 1.7 STAKEHOLDERS 32

• 2 RESEARCH METHODOLOGY 33

  • 2.1 RESEARCH APPROACH 33

    • 2.1.1 SECONDARY AND PRIMARY RESEARCH 35

    • 2.1.2 SECONDARY DATA 35

      • 2.1.2.1 List of key secondary sources 36
      • 2.1.2.2 Key data from secondary sources 36

    • 2.1.3 PRIMARY DATA 36

      • 2.1.3.1 Key data from primary sources 37
      • 2.1.3.2 List of primary interview participants 37
      • 2.1.3.3 Breakdown of primaries 38
      • 2.1.3.4 Key industry insights 38

  • 2.2 MARKET SIZE ESTIMATION METHODOLOGY 39

    • 2.2.1 BOTTOM-UP APPROACH 40

      • 2.2.1.1 Approach to arrive at market size using bottom-up analysis (demand side) 40

    • 2.2.2 TOP-DOWN APPROACH 41

      • 2.2.2.1 Approach to arrive at market size using top-down analysis (supply side) 41

  • 2.3 MARKET BREAKDOWN AND DATA TRIANGULATION 42

  • 2.4 RESEARCH ASSUMPTIONS 42

  • 2.5 RESEARCH LIMITATIONS 43

  • 2.6 RISK ANALYSIS 43

• 3 EXECUTIVE SUMMARY 44

• 4 PREMIUM INSIGHTS 47

  • 4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN DATA CENTER CHIP MARKET 47

  • 4.2 DATA CENTER CHIP MARKET, BY COMPONENT 47

  • 4.3 DATA CENTER CHIP MARKET IN NORTH AMERICA, BY END USER AND COUNTRY 48

  • 4.4 DATA CENTER CHIP MARKET, BY DATA CENTER SIZE 48

  • 4.5 DATA CENTER CHIP MARKET, BY APPLICATION 49

  • 4.6 DATA CENTER CHIP MARKET, BY COUNTRY 49

• 5 MARKET OVERVIEW 50

  • 5.1 INTRODUCTION 50

  • 5.2 MARKET DYNAMICS 50

    • 5.2.1 DRIVERS 51

      • 5.2.1.1 Rapid expansion of data center capacity 51
      • 5.2.1.2 Rising need for low-latency and high-throughput data processing 52
      • 5.2.1.3 Increasing deployment of machine learning and deep learning technologies 52
      • 5.2.1.4 Growing emphasis on parallel computing in AI data centers 53

    • 5.2.2 RESTRAINTS 53

      • 5.2.2.1 Shortage of skilled workforce 54
      • 5.2.2.2 High costs of data center GPUs 54

    • 5.2.3 OPPORTUNITIES 54

      • 5.2.3.1 Emergence of sovereign AI 55
      • 5.2.3.2 Increasing adoption of FPGA-based accelerators 55

    • 5.2.4 CHALLENGES 56

      • 5.2.4.1 High energy consumption in data centers 56
      • 5.2.4.2 Security concerns associated with data center hardware components 56

  • 5.3 TECHNOLOGY ANALYSIS 57

    • 5.3.1 KEY TECHNOLOGIES 57

      • 5.3.1.1 Generative AI 57

    • 5.3.2 COMPLEMENTARY TECHNOLOGIES 57

      • 5.3.2.1 Data center power management and cooling systems 57

    • 5.3.3 ADJACENT TECHNOLOGIES 58

      • 5.3.3.1 Quantum AI 58

  • 5.4 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS 58

  • 5.5 PRICING ANALYSIS 59

    • 5.5.1 INDICATIVE PRICING OF KEY PLAYERS, BY AI PROCESSOR, 2023 59

    • 5.5.2 AVERAGE SELLING PRICE TREND, BY REGION, 2020-2023 60

  • 5.6 VALUE CHAIN ANALYSIS 62

  • 5.7 ECOSYSTEM ANALYSIS 64

  • 5.8 INVESTMENT AND FUNDING SCENARIO 66

  • 5.9 PATENT ANALYSIS 67

  • 5.10 TRADE ANALYSIS 69

    • 5.10.1 IMPORT SCENARIO (HS CODE 854231) 69

    • 5.10.2 EXPORT SCENARIO (HS CODE 854231) 70

  • 5.11 TARIFF AND REGULATORY LANDSCAPE 71

    • 5.11.1 TARIFF ANALYSIS 71

    • 5.11.2 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 72

    • 5.11.3 STANDARDS 75

      • 5.11.3.1 US 76
      • 5.11.3.2 Europe 76
      • 5.11.3.3 China 76
      • 5.11.3.4 Japan 76

  • 5.12 KEY CONFERENCES AND EVENTS, 2024-2025 77

  • 5.13 CASE STUDY ANALYSIS 78

    • 5.13.1 STMICROELECTRONICS DEPLOYS AMD EPYC PROCESSORS TO ENHANCE R&D DATA CENTER PERFORMANCE 78

    • 5.13.2 JOCDN ADOPTS AMD EPYC PROCESSORS TO IMPROVE BROADCAST VIDEO STREAMING CAPABILITIES 78

    • 5.13.3 DBS BANK LEVERAGES DELL SERVERS POWERED BY AMD EPYC PROCESSORS TO TRANSFORM DATA CENTER INFRASTRUCTURE 78

  • 5.14 PORTER’S FIVE FORCES ANALYSIS 79

    • 5.14.1 INTENSITY OF COMPETITIVE RIVALRY 80

    • 5.14.2 BARGAINING POWER OF SUPPLIERS 80

    • 5.14.3 BARGAINING POWER OF BUYERS 80

    • 5.14.4 THREAT OF SUBSTITUTES 80

    • 5.14.5 THREAT OF NEW ENTRANTS 80

  • 5.15 KEY STAKEHOLDERS AND BUYING CRITERIA 81

    • 5.15.1 KEY STAKEHOLDERS IN BUYING PROCESS 81

    • 5.15.2 BUYING CRITERIA 82

  • 5.16 IMPACT OF AI/GEN AI ON DATA CENTER CHIP MARKET 83

• 6 DATA CENTER CHIP MARKET, BY COMPONENT 84

  • 6.1 INTRODUCTION 85

  • 6.2 PROCESSORS 86

    • 6.2.1 AI PROCESSOR 87

    • 6.2.2 GENERAL-PURPOSE COMPUTING PROCESSOR 88

      • 6.2.2.1 GPU 89
        • 6.2.2.1.1 Ability to handle AI workloads and process vast data volumes to boost adoption 89
      • 6.2.2.2 CPU 91
        • 6.2.2.2.1 Rising demand for versatile and general-purpose AI processing to augment market growth 91
      • 6.2.2.3 FPGA 92
        • 6.2.2.3.1 Growing need for flexibility and customization for AI workloads to spur demand 92
      • 6.2.2.4 DOJO & FSD 94
        • 6.2.2.4.1 High demand for high-performance, energy-efficient AI processing in autonomous vehicles to fuel adoption 94
      • 6.2.2.5 Trainium & Inferentia 95
        • 6.2.2.5.1 Ability to train complex AI and deep learning models to drive adoption 95
      • 6.2.2.6 Athena ASIC 95
        • 6.2.2.6.1 Increasing need to handle complex NLP and language-based AI tasks to accelerate market growth 95
      • 6.2.2.7 T-Head 96
        • 6.2.2.7.1 Rising demand for customized, high-performance AI chips across Chinese data centers to stimulate market growth 96
      • 6.2.2.8 MTIA 96
        • 6.2.2.8.1 Meta's expansion into AR, VR, and Metaverse to fuel market growth 96
      • 6.2.2.9 LPU 97
        • 6.2.2.9.1 Increasing need to handle complex NLP and language-based AI tasks to accelerate market growth 97
      • 6.2.2.10 Other ASIC 97

  • 6.3 MEMORY 98

    • 6.3.1 DDR 99

      • 6.3.1.1 Rising adoption of AI-enabled CPUs in data centers to support market growth 99

    • 6.3.2 HBM 100

      • 6.3.2.1 Elevating need for high throughput in data-intensive AI tasks to fuel market growth 100

  • 6.4 NETWORK 100

    • 6.4.1 NIC/NETWORK ADAPTERS 102

      • 6.4.1.1 InfiniBand 104
        • 6.4.1.1.1 Growing utilization of HPC and AI models to minimize latency and maximize throughput to boost segmental growth 104
      • 6.4.1.2 Ethernet 104
        • 6.4.1.2.1 Rising demand for scalable and cost-effective networking solutions to propel growth 104
      • 6.4.1.3 Others 104

    • 6.4.2 INTERCONNECTS 105

      • 6.4.2.1 Growing complexity of AI models requiring high-bandwidth data paths to fuel demand 105

  • 6.5 SENSORS 105

    • 6.5.1 TEMPERATURE SENSOR 105

      • 6.5.1.1 Increased requirement for optimal operational efficiency to drive demand for temperature sensor 105

    • 6.5.2 HUMIDITY SENSOR 106

      • 6.5.2.1 Growing awareness of environmental factors driving adoption of humidity monitoring 106

    • 6.5.3 AIRFLOW SENSOR 106

      • 6.5.3.1 Increasing server racks to drive market for airflow sensor 106

    • 6.5.4 OTHER SENSORS 106

  • 6.6 POWER MANAGEMENT 108

    • 6.6.1 MULTIPHASE CONTROLLER 108

      • 6.6.1.1 Need to manage and optimize performance to drive segmental growth 108

    • 6.6.2 POINT-OF-LOAD (POL) (DC/DC CONVERTER) 108

      • 6.6.2.1 Increasing demand for energy efficiency and high-performance computing to fuel market growth 108

    • 6.6.3 LOW DROPOUT (LDO) 109

      • 6.6.3.1 Ability to maintain stable output voltage to drive demand 109

    • 6.6.4 48V INTERMEDIATE BUS CONVERTER (IBC) 109

      • 6.6.4.1 Helps ensure adequate supply of efficient power management 109

    • 6.6.5 HOT SWAP CONTROLLER/EFUSE 109

      • 6.6.5.1 Increasing demand for low latency in data centers to drive market for hot swap controller 109

    • 6.6.6 POWER SEQUENCER 110

      • 6.6.6.1 Helps regulate power-up sequence of different voltage rails 110

    • 6.6.7 BASEBOARD MANAGEMENT CONTROLLER (BMC) 110

      • 6.6.7.1 Increasing demand for remote monitoring and management of server hardware to drive market 110

  • 6.7 ANALOG & MIXED-SIGNAL ICS 112

    • 6.7.1 MULTICHANNEL ADC/DAC 112

      • 6.7.1.1 Converters used to provide efficient control of data generated from various sensors 112

    • 6.7.2 MULTICHANNEL ADC/DAC 113

      • 6.7.2.1 Helps in high-speed data transfer among other components in data center chip 113

    • 6.7.3 MUX 113

      • 6.7.3.1 Helps in streaming between multiple data center server 113

    • 6.7.4 CURRENT SENSOR AMPLIFIER 113

      • 6.7.4.1 Necessity for monitoring power consumption to drive demand 113

    • 6.7.5 SUPERVISORY ICS 113

      • 6.7.5.1 Need for stabilization of power supply to fuel market growth 113

    • 6.7.6 FAN CONTROLLER 114

      • 6.7.6.1 Increasing scale and performance of data centers creating demand for fan controllers 114

    • 6.7.7 CLOCK IC 114

      • 6.7.7.1 Importance of stable high-speed data transfer to support market growth 114

• 7 DATA CENTER CHIP MARKET, BY DATA CENTER SIZE 117

  • 7.1 INTRODUCTION 118

  • 7.2 SMALL DATA CENTERS 119

    • 7.2.1 NEED FOR EDGE, COMPUTING, COST EFFICIENCY, SCALABILITY, AND RAPID DEPLOYMENT TO DRIVE MARKET 119

  • 7.3 MEDIUM-SIZED DATA CENTERS 120

    • 7.3.1 REDUNDANCY AND HIGH AVAILABILITY FEATURES TO DRIVE DEMAND 120

  • 7.4 LARGE DATA CENTERS 121

    • 7.4.1 NEED FOR MASSIVE DATA PROCESSING, CLOUD COMPUTING, SCALABILITY, AND HIGH AVAILABILITY TO DRIVE MARKET 121

• 8 DATA CENTER CHIP MARKET, BY APPLICATION 123

  • 8.1 INTRODUCTION 124

  • 8.2 GENERATIVE AI 125

    • 8.2.1 RULE-BASED MODELS 127

      • 8.2.1.1 Rising need to detect fraud in finance sector to propel market 127

    • 8.2.2 STATISTICAL MODELS 127

      • 8.2.2.1 Requirement to make accurate predictions from complex data structures to boost segmental growth 127

    • 8.2.3 DEEP LEARNING 128

      • 8.2.3.1 Ability to advance AI technologies to boost demand 128

    • 8.2.4 GENERATIVE ADVERSARIAL NETWORKS (GAN) 129

      • 8.2.4.1 Pressing needs to handle large-scale data to fuel segmental growth 129

    • 8.2.5 AUTOENCODERS 130

      • 8.2.5.1 Ability to compress and restructure data to ensure optimum storage space in data centers to stimulate demand 130

    • 8.2.6 CONVOLUTIONAL NEURAL NETWORKS (CNNS) 130

      • 8.2.6.1 Surging demand for realistic and high-quality images and videos to accelerate market growth 130

    • 8.2.7 TRANSFORMER MODELS 131

      • 8.2.7.1 Increasing utilization in image synthesis and captioning applications to foster segmental growth 131

    • 8.2.8 MACHINE LEARNING 132

      • 8.2.8.1 Rising use in image and speech recognition and predictive analytics to contribute to market growth 132

    • 8.2.9 NATURAL LANGUAGE PROCESSING 132

      • 8.2.9.1 Increasing need for real-time applications to support market growth 132

    • 8.2.10 COMPUTER VISION 133

      • 8.2.10.1 Escalating need for advanced processing capabilities to boost demand 133

  • 8.3 GENERAL-PURPOSE COMPUTING 134

• 9 DATA CENTER CHIP MARKET, BY END USER 135

  • 9.1 INTRODUCTION 136

  • 9.2 CLOUD SERVICE PROVIDERS 137

    • 9.2.1 SURGING AI WORKLOADS AND CLOUD ADOPTION TO STIMULATE MARKET GROWTH 137

  • 9.3 ENTERPRISES 138

    • 9.3.1 ESCALATING USE OF NLP, IMAGE RECOGNITION, AND PREDICTIVE ANALYTICS TO CREATE GROWTH OPPORTUNITIES 138

    • 9.3.2 HEALTHCARE 139

      • 9.3.2.1 Integration of AI in computer-aided drug discovery and development to foster market growth 139

    • 9.3.3 BFSI 140

      • 9.3.3.1 Surging need for fraud detection in financial institutions to boost demand 140

    • 9.3.4 AUTOMOTIVE 141

      • 9.3.4.1 Growing focus on safe and enhanced driving experiences to fuel demand 141

    • 9.3.5 RETAIL & E-COMMERCE 143

      • 9.3.5.1 Increasing use of chatbots and virtual assistants to offer improved customer services to drive market 143

    • 9.3.6 MEDIA & ENTERTAINMENT 144

      • 9.3.6.1 Real-time analysis of viewer preferences and demographic information to augment market growth 144

    • 9.3.7 OTHERS 145

  • 9.4 GOVERNMENT ORGANIZATIONS 146

    • 9.4.1 FOCUS ON AUTOMATING ROUTINE TASKS AND EXTRACTING REAL-TIME INSIGHTS TO SUPPORT MARKET GROWTH 146

• 10 DATA CENTER CHIP MARKET, BY REGION 148

  • 10.1 INTRODUCTION 149

  • 10.2 NORTH AMERICA 150

    • 10.2.1 MACROECONOMIC OUTLOOK FOR NORTH AMERICA 150

    • 10.2.2 US 154

      • 10.2.2.1 Rising demand for digital solutions to drive market 154

    • 10.2.3 CANADA 155

      • 10.2.3.1 Growing digital transformation and 5G services to support market growth 155

    • 10.2.4 MEXICO 155

      • 10.2.4.1 Government-led initiatives to ensure connectivity within urban centers to boost demand 155

  • 10.3 EUROPE 156

    • 10.3.1 MACROECONOMIC OUTLOOK FOR EUROPE 156

    • 10.3.2 GERMANY 160

      • 10.3.2.1 Adoption of industry 4.0 and advancement in technology infrastructure to drive market 160

    • 10.3.3 UK 161

      • 10.3.3.1 Increasing adoption of data centers and HPC by various verticals to support market growth 161

    • 10.3.4 FRANCE 161

      • 10.3.4.1 Federal support to promote data center infrastructure to augment market growth 161

    • 10.3.5 REST OF EUROPE 161

  • 10.4 ASIA PACIFIC 162

    • 10.4.1 MACROECONOMIC OUTLOOK FOR ASIA PACIFIC 162

    • 10.4.2 CHINA 167

      • 10.4.2.1 Rising demand for high-speed data processing to accelerate market growth 167

    • 10.4.3 JAPAN 167

      • 10.4.3.1 Surge in adoption of data-intensive technologies like AI and IoT to drive market 167

    • 10.4.4 INDIA 167

      • 10.4.4.1 Government initiatives to boost AI infrastructure to foster market growth 167

    • 10.4.5 REST OF ASIA PACIFIC 168

  • 10.5 ROW 168

    • 10.5.1 MACROECONOMIC OUTLOOK FOR ROW 168

    • 10.5.2 SOUTH AMERICA 173

      • 10.5.2.1 Strong government support to develop network infrastructure to boost demand 173

    • 10.5.3 MIDDLE EAST & AFRICA 173

      • 10.5.3.1 GCC countries 174
      • 10.5.3.2 Rest of Middle East & Africa 174

• 11 COMPETITIVE LANDSCAPE 175

  • 11.1 OVERVIEW 175

  • 11.2 KEY PLAYERS’ STRATEGIES/RIGHT TO WIN, 2021-2024 175

  • 11.3 REVENUE ANALYSIS, 2021-2023 177

  • 11.4 MARKET SHARE ANALYSIS, 2023 177

  • 11.5 COMPANY VALUATION AND FINANCIAL METRICS, 2024 180

  • 11.6 BRAND/PRODUCT COMPARISON 181

  • 11.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023 182

    • 11.7.1 STARS 182

    • 11.7.2 EMERGING LEADERS 182

    • 11.7.3 PERVASIVE PLAYERS 182

    • 11.7.4 PARTICIPANTS 182

    • 11.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023 184

      • 11.7.5.1 Company footprint 184
      • 11.7.5.2 Region footprint 185
      • 11.7.5.3 Component footprint 186
      • 11.7.5.4 End user footprint 187
      • 11.7.5.5 Application footprint 188

  • 11.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023 189

    • 11.8.1 PROGRESSIVE COMPANIES 189

    • 11.8.2 RESPONSIVE COMPANIES 189

    • 11.8.3 DYNAMIC COMPANIES 189

    • 11.8.4 STARTING BLOCKS 189

    • 11.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023 191

      • 11.8.5.1 Detailed list of key startups/SMEs 191
      • 11.8.5.2 Competitive benchmarking of key startups/SMEs 191

  • 11.9 COMPETITIVE SCENARIO 192

    • 11.9.1 PRODUCT LAUNCHES 192

    • 11.9.2 DEALS 193

    • 11.9.3 OTHER DEVELOPMENTS 194

• 12 COMPANY PROFILES 195

  • 12.1 KEY PLAYERS 195

    • 12.1.1 NVIDIA CORPORATION 195

      • 12.1.1.1 Business overview 195
      • 12.1.1.2 Products/Solutions/Services offered 196
      • 12.1.1.3 Recent developments 198
        • 12.1.1.3.1 Product launches 198
        • 12.1.1.3.2 Deals 199
      • 12.1.1.4 MnM view 200
        • 12.1.1.4.1 Key strengths/Right to win 200
        • 12.1.1.4.2 Strategic choices 200
        • 12.1.1.4.3 Weaknesses/Competitive threats 200

    • 12.1.2 ADVANCED MICRO DEVICES, INC 201

      • 12.1.2.1 Business overview 201
      • 12.1.2.2 Products/Solutions/Services offered 202
      • 12.1.2.3 Recent developments 203
        • 12.1.2.3.1 Product launches 203
        • 12.1.2.3.2 Deals 204
      • 12.1.2.4 MnM view 205
        • 12.1.2.4.1 Key strengths/Right to win 205
        • 12.1.2.4.2 Strategic choices 205
        • 12.1.2.4.3 Weaknesses/Competitive threats 205

    • 12.1.3 INTEL CORPORATION 206

      • 12.1.3.1 Business overview 206
      • 12.1.3.2 Products/Solutions/Services offered 207
      • 12.1.3.3 Recent developments 209
        • 12.1.3.3.1 Product launches 209
        • 12.1.3.3.2 Deals 210
      • 12.1.3.4 MnM view 211
        • 12.1.3.4.1 Key strengths/Right to win 211
        • 12.1.3.4.2 Strategic choices 211
        • 12.1.3.4.3 Weaknesses/Competitive threats 212

    • 12.1.4 SAMSUNG 213

      • 12.1.4.1 Business overview 213
      • 12.1.4.2 Products/Solutions/Services offered 214
      • 12.1.4.3 Recent developments 215
        • 12.1.4.3.1 Product launches 215
        • 12.1.4.3.2 Deals 216
      • 12.1.4.4 MnM view 217
        • 12.1.4.4.1 Key strengths/Right to win 217
        • 12.1.4.4.2 Strategic choices 217
        • 12.1.4.4.3 Weaknesses/Competitive threats 217

    • 12.1.5 SK HYNIX INC 218

      • 12.1.5.1 Business overview 218
      • 12.1.5.2 Products/Solutions/Services offered 219
      • 12.1.5.3 Recent developments 220
        • 12.1.5.3.1 Product launches 220
        • 12.1.5.3.2 Deals 221
        • 12.1.5.3.3 Other developments 221
      • 12.1.5.4 MnM view 221
        • 12.1.5.4.1 Key strengths/Right to win 221
        • 12.1.5.4.2 Strategic choices 221
        • 12.1.5.4.3 Weaknesses/Competitive threats 222

    • 12.1.6 GOOGLE 223

      • 12.1.6.1 Business overview 223
      • 12.1.6.2 Products/Solutions/Services offered 224
      • 12.1.6.3 Recent developments 225
        • 12.1.6.3.1 Product launches 225
        • 12.1.6.3.2 Deals 225

    • 12.1.7 AMAZON WEB SERVICES, INC 226

      • 12.1.7.1 Business overview 226
      • 12.1.7.2 Products/Solutions/Services offered 226
      • 12.1.7.3 Recent developments 227
        • 12.1.7.3.1 Product launches 227
        • 12.1.7.3.2 Deals 227

    • 12.1.8 MONOLITHIC POWER SYSTEMS, INC 229

      • 12.1.8.1 Business overview 229
      • 12.1.8.2 Products/Solutions/Services Offered 230
      • 12.1.8.3 Recent developments 231
        • 12.1.8.3.1 Deals 231

    • 12.1.9 TEXAS INSTRUMENTS INCORPORATED 232

      • 12.1.9.1 Business overview 232
      • 12.1.9.2 Products/Solutions/Services offered 233
      • 12.1.9.3 Recent developments 234
        • 12.1.9.3.1 Other developments 234

    • 12.1.10 MICRON TECHNOLOGY, INC 235

      • 12.1.10.1 Business overview 235
      • 12.1.10.2 Products/Solutions/Services offered 236
      • 12.1.10.3 Recent developments 237
        • 12.1.10.3.1 Product launches 237
        • 12.1.10.3.2 Deals 238

    • 12.1.11 ANALOG DEVICES, INC 239

      • 12.1.11.1 Business overview 239
      • 12.1.11.2 Products/Solutions/Services offered 240
      • 12.1.11.3 Recent developments 241
        • 12.1.11.3.1 Expansions 241

    • 12.1.12 MICROSOFT 242

      • 12.1.12.1 Business overview 242
      • 12.1.12.2 Products/Solutions/Services offered 243
      • 12.1.12.3 Recent developments 244
        • 12.1.12.3.1 Product launches 244
        • 12.1.12.3.2 Deals 244

  • 12.2 OTHER PLAYERS 245

    • 12.2.1 IMAGINATION TECHNOLOGIES 245

    • 12.2.2 GRAPHCORE 246

    • 12.2.3 CEREBRAS SYSTEMS INC 246

    • 12.2.4 GROQ, INC 247

    • 12.2.5 TESLA 248

    • 12.2.6 STMICROELECTRONICS 249

    • 12.2.7 SENSIRION AG 249

    • 12.2.8 AKCP 250

    • 12.2.9 BOSCH SENSORTEC GMBH 251

    • 12.2.10 RENESAS ELECTRONICS CORPORATION 252

    • 12.2.11 INFINEON TECHNOLOGIES AG 253

    • 12.2.12 DIODES INCORPORATED 254

    • 12.2.13 MICROCHIP TECHNOLOGY INC 255

    • 12.2.14 HUAWEI TECHNOLOGIES CO., LTD 256

    • 12.2.15 T-HEAD 257

    • 12.2.16 BLAIZE 258

    • 12.2.17 HAILO TECHNOLOGIES LTD 259

    • 12.2.18 KNERON, INC 260

    • 12.2.19 TENSTORRENT 261

    • 12.2.20 TAALAS 261

    • 12.2.21 SAPEON INC 262

    • 12.2.22 REBELLIONS INC 262

• 13 APPENDIX 263

  • 13.1 DISCUSSION GUIDE 263

  • 13.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 266

  • 13.3 CUSTOMIZATION OPTIONS 268

  • 13.4 RELATED REPORTS 268

  • 13.5 AUTHOR DETAILS 269