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市场调查报告书
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1757447

深度学习晶片组市场：全球产业分析、市场规模、份额、成长、趋势与未来预测（2025-2032）

Deep Learning Chipset Market: Global Industry Analysis, Size, Share, Growth, Trends, and Forecast, 2025 - 2032
出版日期: | 出版商: Persistence Market Research | 英文 250 Pages | 商品交期: 2-5个工作天内

价格
简介目录

Persistence Market Research 最近发布了一份关于全球深度学习晶片组市场的综合报告。该报告对关键市场动态进行了全面评估，包括市场驱动因素、趋势、机会、驱动因素和挑战，并提供了有关市场结构的详细见解。该研究报告提供独家数据和统计数据，概述了 2025 年至 2032 年全球深度学习晶片组市场的预测成长轨迹。

关键见解

  • 深度学习晶片组市场规模（2025年）：67.263亿美元
  • 市场规模预测（以金额为准，2032 年）：36,040,900,000 美元
  • 全球市场成长率（2025-2032年复合年增长率）：27.1%

深度学习晶片组市场：分析范围

深度学习晶片组是动力来源人工智慧 (AI) 系统的重要组成部分，可实现跨行业的即时数据处理、预测分析和机器学习任务。这些晶片组旨在高效执行复杂的数学运算并支援神经网路训练和推理。深度学习晶片组市场服务于广泛的最终用途领域，包括汽车、医疗保健、金融、消费性电子和国防。自然语言处理、自动驾驶和电脑视觉等人工智慧应用的激增，正在加速对高效能晶片组（包括 GPU、FPGA、ASIC 和 NPU）的需求。人工智慧的普及、晶片结构的进步以及边缘运算和资料中心基础设施投资的增加进一步推动了市场成长。

市场成长动力：

全球深度学习晶片市场受多个关键因素驱动，包括各垂直行业对人工智慧解决方案的快速应用，以及对更快处理能力日益增长的需求。自动驾驶汽车、智慧助理和智慧监控系统的兴起，推动了针对深度学习工作负载优化的专用晶片组的需求。 5奈米製程、3D堆迭和异构运算等技术进步，使晶片设计更加高效、紧凑，支援在边缘设备和移动平台上的广泛部署。此外，政府和私营部门对人工智慧研究的投入不断增加，以及旨在实现IT基础设施现代化的战略倡议，也正在推动全球市场的发展动能。

市场限制：

儘管预计深度学习晶片组市场将强劲成长，但它仍面临诸多挑战，包括高昂的开发成本、功耗问题以及精通人工智慧硬体设计的专家短缺。将深度学习硬体整合到旧有系统中的复杂性以及快速的技术创新可能导致产品生命週期缩短，从而给製造商和投资者带来风险。此外，影响半导体生产的供应链中断和地缘政治紧张局势可能会对市场供应和成本稳定性造成限制。克服这些障碍需要建立策略伙伴关係、加大人才培养投入以及製定富有弹性的供应链策略。

市场机会：

深度学习晶片市场蕴含着巨大的成长机会，这得益于人工智慧与家用电器、工业自动化和医疗诊断的融合。智慧摄影机、无人机和穿戴式健康监测器等边缘人工智慧设备的日益普及，为低延迟、高能源效率的晶片开闢了新的发展方向。 5G网路和云端基础设施的扩展进一步支援了即时数据分析，从而推动了数据中心对人工智慧加速器的需求。此外，亚洲和拉丁美洲的新兴市场正在加速人工智慧技术的普及，为晶片供应商开闢了尚未开发的收益来源。量子运算、神经型态晶片和开放原始码硬体平台领域的创新将重塑竞争动态，并开启新的发展机会。

本报告回答的关键问题

  • 推动全球深度学习晶片组市场成长的关键因素有哪些？
  • 哪些类型的晶片组和最终用途正在推动对人工智慧硬体解决方案的需求？
  • 晶片结构的进步如何影响深度学习晶片组市场的竞争格局？
  • 哪些主要企业正在为深度学习晶片组市场做出贡献，他们采取什么策略来维持市场领导地位？
  • 全球深度学习晶片市场有哪些新趋势与未来前景？

目录

第一章执行摘要

第二章 市场概述

  • 市场范围和定义
  • 价值链分析
  • 宏观经济因素
    • 世界GDP展望
    • 全球建设产业概况
    • 全球采矿业概况
  • 预测因子：相关性和影响力
  • COVID-19影响评估
  • PESTLE分析
  • 波特五力分析
  • 地缘政治紧张局势：市场影响
  • 监管和技术格局

第三章 市场动态

  • 驱动程式
  • 限制因素
  • 机会
  • 趋势

第四章 价格趋势分析（2019-2032）

  • 区域定价分析
  • 按细分市场定价
  • 影响价格的因素

第五章 全球深度学习晶片组市场展望：过去（2019-2024）与预测（2025-2032）

  • 主要亮点
  • 全球深度学习晶片组市场展望（按类型）
    • 简介/主要发现
    • 按类型分類的历史市场规模分析（以金额为准，2019-2024）
    • 当前市场规模预测（按类型划分）（以金额为准，2025-2032）
      • 中央处理器（CPU）
      • 图形处理单元 (GPU)
      • 现场可程式闸阵列（FPGA）
      • 专用积体电路（ASIC）
      • 其他（NPU、混合晶片）
    • 市场吸引力分析：按类型
  • 全球深度学习晶片组市场技术展望
    • 简介/主要发现
    • 按技术分類的历史市场规模分析（以金额为准，2019-2024 年）
    • 当前市场规模预测（按技术划分）（以金额为准，2025-2032）
      • 系统晶片(SOC)
      • 系统级封装(SIP)
      • 多晶片模组
    • 市场吸引力分析：按技术

第六章全球深度学习晶片市场区域展望

  • 主要亮点
  • 按地区分類的历史市场规模分析（以金额为准，2019-2024 年）
  • 各地区目前市场规模预测（以金额为准，2025-2032）
    • 北美洲
    • 欧洲
    • 东亚
    • 南亚和大洋洲
    • 拉丁美洲
    • 中东和非洲
  • 市场吸引力分析：按地区

第七章 北美深度学习晶片组市场展望：过去（2019-2024）与预测（2025-2032）

第 8 章欧洲深度学习晶片组市场展望：过去（2019-2024 年）与预测（2025-2032 年）

第九章东亚深度学习晶片组市场展望：过去（2019-2024）与预测（2025-2032）

第 10 章南亚和大洋洲深度学习晶片组市场展望：历史（2019-2024 年）和预测（2025-2032 年）

第 11 章拉丁美洲深度学习晶片组市场展望：历史（2019-2024 年）与预测（2025-2032 年）

第 12 章中东和非洲深度学习晶片组市场展望：历史（2019-2024 年）和预测（2025-2032 年）

第十三章竞争格局

  • 市场占有率分析（2025年）
  • 市场结构
    • 竞争强度图：按市场
    • 竞争仪錶板
  • 公司简介
    • Alphabet Inc.
    • Amazon.Com, Inc.
    • Advanced Micro Devices, Inc.
    • Baidu, Inc.
    • Bitmain Technologies Ltd.
    • Intel Corporation
    • Nvidia Corporation
    • Qualcomm Incorporated
    • Samsung Electronics Co. Ltd.
    • Xilinx, Inc

第十四章 附录

  • 分析方法
  • 分析前提条件
  • 首字母缩写和简称
简介目录
Product Code: PMRREP33373

Persistence Market Research has recently released a comprehensive report on the worldwide market for deep learning chipsets. The report offers a thorough assessment of crucial market dynamics, including drivers, trends, opportunities, and challenges, providing detailed insights into the market structure. This research publication presents exclusive data and statistics outlining the anticipated growth trajectory of the global deep learning chipset market from 2025 to 2032.

Key Insights:

  • Deep Learning Chipset Market Size (2025E): USD 6,726.3 Million
  • Projected Market Value (2032F): USD 36,040.9 Million
  • Global Market Growth Rate (CAGR 2025 to 2032): 27.1%

Deep Learning Chipset Market - Report Scope:

Deep learning chipsets are essential components powering artificial intelligence (AI) systems, enabling real-time data processing, predictive analytics, and machine learning tasks across diverse industries. These chipsets are designed to execute complex mathematical operations efficiently, supporting neural network training and inference. The deep learning chipset market serves a wide array of end-use sectors including automotive, healthcare, finance, consumer electronics, and defense. The surge in AI-powered applications such as natural language processing, autonomous driving, and computer vision is accelerating demand for high-performance chipsets including GPUs, FPGAs, ASICs, and NPUs. Market growth is further driven by increasing AI adoption, advancements in chip architecture, and rising investment in edge computing and data center infrastructure.

Market Growth Drivers:

The global deep learning chipset market is propelled by several key factors, including the rapid proliferation of AI-based solutions across sectors and growing demand for high-speed processing capabilities. The emergence of autonomous vehicles, smart assistants, and intelligent surveillance systems has intensified the need for specialized chipsets optimized for deep learning workloads. Technological advancements such as 5nm fabrication, 3D stacking, and heterogeneous computing enable more efficient and compact chip designs, supporting wider deployment in edge devices and mobile platforms. Furthermore, increasing government and private sector investments in AI research, coupled with strategic initiatives to modernize IT infrastructure, are reinforcing market momentum globally.

Market Restraints:

Despite robust growth prospects, the deep learning chipset market faces challenges such as high development costs, power consumption concerns, and limited availability of skilled professionals for AI hardware design. The complexity of integrating deep learning hardware into legacy systems and the rapid pace of innovation may result in short product lifecycles, creating risks for manufacturers and investors. Additionally, supply chain disruptions and geopolitical tensions affecting semiconductor production can pose constraints on market availability and cost stability. Addressing these barriers requires strategic partnerships, investment in workforce development, and resilient supply chain strategies.

Market Opportunities:

The deep learning chipset market presents substantial growth opportunities fueled by the integration of AI into consumer electronics, industrial automation, and healthcare diagnostics. The rising popularity of edge AI devices such as smart cameras, drones, and wearable health monitors creates new avenues for low-latency, power-efficient chipsets. The expansion of 5G networks and cloud infrastructure further supports real-time data analytics, driving demand for AI accelerators in data centers. Moreover, emerging markets in Asia and Latin America are adopting AI technologies at an accelerating pace, opening up untapped revenue streams for chipset vendors. Innovations in quantum computing, neuromorphic chips, and open-source hardware platforms are poised to redefine competitive dynamics and unlock new possibilities.

Key Questions Answered in the Report:

  • What are the primary factors driving the growth of the deep learning chipset market globally?
  • Which chipset types and end-use applications are propelling demand for AI hardware solutions?
  • How are advancements in chip architecture shaping the competitive landscape of the deep learning chipset market?
  • Who are the key players contributing to the deep learning chipset market, and what strategies are they employing to maintain market leadership?
  • What are the emerging trends and future prospects in the global deep learning chipset market?

Competitive Intelligence and Business Strategy:

These companies invest heavily in R&D to develop high-efficiency chipsets tailored to specialized AI workloads, including natural language processing, image recognition, and autonomous navigation. Strategic collaborations with cloud service providers, AI startups, and academic institutions foster co-development and accelerate time-to-market. Emphasis on software-hardware co-design, open-source frameworks, and robust developer ecosystems further enhances product adoption and customer engagement in this rapidly evolving domain.

Key Companies Profiled:

  • Alphabet Inc.
  • Amazon.Com, Inc.
  • Advanced Micro Devices, Inc.
  • Baidu, Inc.
  • Bitmain Technologies Ltd.
  • Intel Corporation
  • Nvidia Corporation
  • Qualcomm Incorporated
  • Samsung Electronics Co. Ltd.
  • Xilinx, Inc.

Deep Learning Chipset Market Research Segmentation:

The deep learning chipset market encompasses a diverse range of product types, applications, and end-use industries, addressing a broad spectrum of AI-powered solutions.

By Type:

  • Central Processing Units (CPUs)
  • Graphics Processing Units (GPUs)
  • Field Programmable Gate Arrays (FPGAs)
  • Application-Specific Integrated Circuits (ASICs)
  • Others (NPU & Hybrid Chip)

By Technology:

  • System-on-chip (SOC)
  • System-in-package (SIP)
  • Multi-Chip Module

By Region:

  • North America
  • Latin America
  • Europe
  • Asia Pacific
  • Middle East and Africa

Table of Contents

1. Executive Summary

  • 1.1. Global Deep Learning Chipset Market Snapshot 2025 and 2032
  • 1.2. Market Opportunity Assessment, 2025-2032, US$ Mn
  • 1.3. Key Market Trends
  • 1.4. Industry Developments and Key Market Events
  • 1.5. Demand Side and Supply Side Analysis
  • 1.6. PMR Analysis and Recommendations

2. Market Overview

  • 2.1. Market Scope and Definitions
  • 2.2. Value Chain Analysis
  • 2.3. Macro-Economic Factors
    • 2.3.1. Global GDP Outlook
    • 2.3.2. Global Construction Industry Overview
    • 2.3.3. Global Mining Industry Overview
  • 2.4. Forecast Factors - Relevance and Impact
  • 2.5. COVID-19 Impact Assessment
  • 2.6. PESTLE Analysis
  • 2.7. Porter's Five Forces Analysis
  • 2.8. Geopolitical Tensions: Market Impact
  • 2.9. Regulatory and Technology Landscape

3. Market Dynamics

  • 3.1. Drivers
  • 3.2. Restraints
  • 3.3. Opportunities
  • 3.4. Trends

4. Price Trend Analysis, 2019-2032

  • 4.1. Region-wise Price Analysis
  • 4.2. Price by Segments
  • 4.3. Price Impact Factors

5. Global Deep Learning Chipset Market Outlook: Historical (2019-2024) and Forecast (2025-2032)

  • 5.1. Key Highlights
  • 5.2. Global Deep Learning Chipset Market Outlook: Type
    • 5.2.1. Introduction/Key Findings
    • 5.2.2. Historical Market Size (US$ Mn) Analysis by Type, 2019-2024
    • 5.2.3. Current Market Size (US$ Mn) Forecast, by Type, 2025-2032
      • 5.2.3.1. Central Processing Units (CPUs)
      • 5.2.3.2. Graphics Processing Units (GPUs)
      • 5.2.3.3. Field Programmable Gate Arrays (FPGAs)
      • 5.2.3.4. Application-Specific Integrated Circuits (ASICs)
      • 5.2.3.5. Others (NPU & Hybrid Chip)
    • 5.2.4. Market Attractiveness Analysis: Type
  • 5.3. Global Deep Learning Chipset Market Outlook: Technology
    • 5.3.1. Introduction/Key Findings
    • 5.3.2. Historical Market Size (US$ Mn) Analysis by Technology, 2019-2024
    • 5.3.3. Current Market Size (US$ Mn) Forecast, by Technology, 2025-2032
      • 5.3.3.1. System-on-chip (SOC)
      • 5.3.3.2. System-in-package (SIP)
      • 5.3.3.3. Multi-Chip Module
    • 5.3.4. Market Attractiveness Analysis: Technology

6. Global Deep Learning Chipset Market Outlook: Region

  • 6.1. Key Highlights
  • 6.2. Historical Market Size (US$ Mn) Analysis by Region, 2019-2024
  • 6.3. Current Market Size (US$ Mn) Forecast, by Region, 2025-2032
    • 6.3.1. North America
    • 6.3.2. Europe
    • 6.3.3. East Asia
    • 6.3.4. South Asia & Oceania
    • 6.3.5. Latin America
    • 6.3.6. Middle East & Africa
  • 6.4. Market Attractiveness Analysis: Region

7. North America Deep Learning Chipset Market Outlook: Historical (2019-2024) and Forecast (2025-2032)

  • 7.1. Key Highlights
  • 7.2. Pricing Analysis
  • 7.3. North America Market Size (US$ Mn) Forecast, by Country, 2025-2032
    • 7.3.1. U.S.
    • 7.3.2. Canada
  • 7.4. North America Market Size (US$ Mn) Forecast, by Type, 2025-2032
    • 7.4.1. Central Processing Units (CPUs)
    • 7.4.2. Graphics Processing Units (GPUs)
    • 7.4.3. Field Programmable Gate Arrays (FPGAs)
    • 7.4.4. Application-Specific Integrated Circuits (ASICs)
    • 7.4.5. Others (NPU & Hybrid Chip)
  • 7.5. North America Market Size (US$ Mn) Forecast, by Technology, 2025-2032
    • 7.5.1. System-on-chip (SOC)
    • 7.5.2. System-in-package (SIP)
    • 7.5.3. Multi-Chip Module

8. Europe Deep Learning Chipset Market Outlook: Historical (2019-2024) and Forecast (2025-2032)

  • 8.1. Key Highlights
  • 8.2. Pricing Analysis
  • 8.3. Europe Market Size (US$ Mn) Forecast, by Country, 2025-2032
    • 8.3.1. Germany
    • 8.3.2. Italy
    • 8.3.3. France
    • 8.3.4. U.K.
    • 8.3.5. Spain
    • 8.3.6. Russia
    • 8.3.7. Rest of Europe
  • 8.4. Europe Market Size (US$ Mn) Forecast, by Type, 2025-2032
    • 8.4.1. Central Processing Units (CPUs)
    • 8.4.2. Graphics Processing Units (GPUs)
    • 8.4.3. Field Programmable Gate Arrays (FPGAs)
    • 8.4.4. Application-Specific Integrated Circuits (ASICs)
    • 8.4.5. Others (NPU & Hybrid Chip)
  • 8.5. Europe Market Size (US$ Mn) Forecast, by Technology, 2025-2032
    • 8.5.1. System-on-chip (SOC)
    • 8.5.2. System-in-package (SIP)
    • 8.5.3. Multi-Chip Module

9. East Asia Deep Learning Chipset Market Outlook: Historical (2019-2024) and Forecast (2025-2032)

  • 9.1. Key Highlights
  • 9.2. Pricing Analysis
  • 9.3. East Asia Market Size (US$ Mn) Forecast, by Country, 2025-2032
    • 9.3.1. China
    • 9.3.2. Japan
    • 9.3.3. South Korea
  • 9.4. East Asia Market Size (US$ Mn) Forecast, by Type, 2025-2032
    • 9.4.1. Central Processing Units (CPUs)
    • 9.4.2. Graphics Processing Units (GPUs)
    • 9.4.3. Field Programmable Gate Arrays (FPGAs)
    • 9.4.4. Application-Specific Integrated Circuits (ASICs)
    • 9.4.5. Others (NPU & Hybrid Chip)
  • 9.5. East Asia Market Size (US$ Mn) Forecast, by Technology, 2025-2032
    • 9.5.1. System-on-chip (SOC)
    • 9.5.2. System-in-package (SIP)
    • 9.5.3. Multi-Chip Module

10. South Asia & Oceania Deep Learning Chipset Market Outlook: Historical (2019-2024) and Forecast (2025-2032)

  • 10.1. Key Highlights
  • 10.2. Pricing Analysis
  • 10.3. South Asia & Oceania Market Size (US$ Mn) Forecast, by Country, 2025-2032
    • 10.3.1. India
    • 10.3.2. Southeast Asia
    • 10.3.3. ANZ
    • 10.3.4. Rest of SAO
  • 10.4. South Asia & Oceania Market Size (US$ Mn) Forecast, by Type, 2025-2032
    • 10.4.1. Central Processing Units (CPUs)
    • 10.4.2. Graphics Processing Units (GPUs)
    • 10.4.3. Field Programmable Gate Arrays (FPGAs)
    • 10.4.4. Application-Specific Integrated Circuits (ASICs)
    • 10.4.5. Others (NPU & Hybrid Chip)
  • 10.5. South Asia & Oceania Market Size (US$ Mn) Forecast, by Technology, 2025-2032
    • 10.5.1. System-on-chip (SOC)
    • 10.5.2. System-in-package (SIP)
    • 10.5.3. Multi-Chip Module

11. Latin America Deep Learning Chipset Market Outlook: Historical (2019-2024) and Forecast (2025-2032)

  • 11.1. Key Highlights
  • 11.2. Pricing Analysis
  • 11.3. Latin America Market Size (US$ Mn) Forecast, by Country, 2025-2032
    • 11.3.1. Brazil
    • 11.3.2. Mexico
    • 11.3.3. Rest of LATAM
  • 11.4. Latin America Market Size (US$ Mn) Forecast, by Type, 2025-2032
    • 11.4.1. Central Processing Units (CPUs)
    • 11.4.2. Graphics Processing Units (GPUs)
    • 11.4.3. Field Programmable Gate Arrays (FPGAs)
    • 11.4.4. Application-Specific Integrated Circuits (ASICs)
    • 11.4.5. Others (NPU & Hybrid Chip)
  • 11.5. Latin America Market Size (US$ Mn) Forecast, by Technology, 2025-2032
    • 11.5.1. System-on-chip (SOC)
    • 11.5.2. System-in-package (SIP)
    • 11.5.3. Multi-Chip Module

12. Middle East & Africa Deep Learning Chipset Market Outlook: Historical (2019-2024) and Forecast (2025-2032)

  • 12.1. Key Highlights
  • 12.2. Pricing Analysis
  • 12.3. Middle East & Africa Market Size (US$ Mn) Forecast, by Country, 2025-2032
    • 12.3.1. GCC Countries
    • 12.3.2. South Africa
    • 12.3.3. Northern Africa
    • 12.3.4. Rest of MEA
  • 12.4. Middle East & Africa Market Size (US$ Mn) Forecast, by Type, 2025-2032
    • 12.4.1. Central Processing Units (CPUs)
    • 12.4.2. Graphics Processing Units (GPUs)
    • 12.4.3. Field Programmable Gate Arrays (FPGAs)
    • 12.4.4. Application-Specific Integrated Circuits (ASICs)
    • 12.4.5. Others (NPU & Hybrid Chip)
  • 12.5. Middle East & Africa Market Size (US$ Mn) Forecast, by Technology, 2025-2032
    • 12.5.1. System-on-chip (SOC)
    • 12.5.2. System-in-package (SIP)
    • 12.5.3. Multi-Chip Module

13. Competition Landscape

  • 13.1. Market Share Analysis, 2025
  • 13.2. Market Structure
    • 13.2.1. Competition Intensity Mapping
    • 13.2.2. Competition Dashboard
  • 13.3. Company Profiles
    • 13.3.1. Alphabet Inc.
      • 13.3.1.1. Company Overview
      • 13.3.1.2. Product Portfolio/Offerings
      • 13.3.1.3. Key Financials
      • 13.3.1.4. SWOT Analysis
      • 13.3.1.5. Company Strategy and Key Developments
    • 13.3.2. Amazon.Com, Inc.
    • 13.3.3. Advanced Micro Devices, Inc.
    • 13.3.4. Baidu, Inc.
    • 13.3.5. Bitmain Technologies Ltd.
    • 13.3.6. Intel Corporation
    • 13.3.7. Nvidia Corporation
    • 13.3.8. Qualcomm Incorporated
    • 13.3.9. Samsung Electronics Co. Ltd.
    • 13.3.10. Xilinx, Inc

14. Appendix

  • 14.1. Research Methodology
  • 14.2. Research Assumptions
  • 14.3. Acronyms and Abbreviations