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1757447

深度學習晶片組市場：全球產業分析、市場規模、佔有率、成長、趨勢與未來預測（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個工作天內

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簡介目錄

Persistence Market Research 最近發布了一份關於全球深度學習晶片組市場的綜合報告。該報告對關鍵市場動態進行了全面評估，包括市場促進因素、趨勢、機會、促進因素和挑戰，並提供了有關市場結構的詳細見解。該研究報告提供獨家數據和統計數據，概述了 2025 年至 2032 年全球深度學習晶片組市場的預測成長軌跡。

關鍵見解

  • 深度學習晶片組市場規模（2025年）：67.263億美元
  • 市場規模預測（以金額為準，2032 年）：36,040,900,000 美元
  • 全球市場成長率（2025-2032年複合年成長率）：27.1%

深度學習晶片組市場：分析範圍

深度學習晶片組是動力來源人工智慧 (AI) 系統的重要組成部分，可實現跨行業的即時數據處理、預測分析和機器學習任務。這些晶片組旨在高效執行複雜的數學運算並支援神經網路訓練和推理。深度學習晶片組市場服務於廣泛的最終用途領域，包括汽車、醫療保健、金融、消費性電子和國防。自然語言處理、自動駕駛和電腦視覺等人工智慧應用的激增，正在加速對高效能晶片組（包括 GPU、FPGA、ASIC 和 NPU）的需求。人工智慧的普及、晶片結構的進步以及邊緣運算和資料中心基礎設施投資的增加進一步推動了市場成長。

市場成長動力：

全球深度學習晶片市場受多個關鍵因素驅動，包括各垂直行業對人工智慧解決方案的快速應用，以及對更快處理能力日益成長的需求。自動駕駛汽車、智慧助理和智慧監控系統的興起，推動了針對深度學習工作負載最佳化的專用晶片組的需求。 5奈米製程、3D堆疊和異構運算等技術進步，使晶片設計更加高效、緊湊，支援在邊緣設備和移動平台上的廣泛部署。此外，政府和私營部門對人工智慧研究的投入不斷增加，以及旨在實現IT基礎設施現代化的戰略舉措，也正在推動全球市場的發展動能。

市場限制：

儘管預計深度學習晶片組市場將強勁成長，但它仍面臨諸多挑戰，包括高昂的開發成本、功耗問題以及精通人工智慧硬體設計的專家短缺。將深度學習硬體整合到舊有系統中的複雜性以及快速的技術創新可能導致產品生命週期縮短，從而給製造商和投資者帶來風險。此外，影響半導體生產的供應鏈中斷和地緣政治緊張局勢可能會對市場供應和成本穩定性造成限制。克服這些障礙需要建立策略夥伴關係、加大人才培養投入以及製定富有彈性的供應鏈策略。

市場機會：

深度學習晶片市場蘊含著巨大的成長機會，這得益於人工智慧與家用電器、工業自動化和醫療診斷的融合。智慧攝影機、無人機和穿戴式健康監測器等邊緣人工智慧設備的日益普及，為低延遲、高能源效率的晶片開闢了新的發展方向。 5G網路和雲端基礎設施的擴展進一步支援了即時數據分析，從而推動了資料中心對人工智慧加速器的需求。此外，亞洲和拉丁美洲的新興市場正在加速人工智慧技術的普及，為晶片供應商開闢了尚未開發的收益來源。量子運算、神經型態晶片和開放原始碼硬體平台領域的創新將重塑競爭動態，並開啟新的發展機會。

本報告回答的關鍵問題

  • 推動全球深度學習晶片組市場成長的關鍵因素有哪些？
  • 哪些類型的晶片組和最終用途正在推動對人工智慧硬體解決方案的需求？
  • 晶片結構的進步如何影響深度學習晶片組市場的競爭格局？
  • 哪些主要企業正在為深度學習晶片組市場做出貢獻，他們採取什麼策略來維持市場領導地位？
  • 全球深度學習晶片市場有哪些新趨勢與未來前景？

目錄

第1章執行摘要

第2章 市場概述

  • 市場範圍和定義
  • 價值鏈分析
  • 宏觀經濟因素
    • 世界GDP展望
    • 全球建設產業概況
    • 全球採礦業概況
  • 預測因子：相關性和影響力
  • COVID-19影響評估
  • PESTLE分析
  • 波特五力分析
  • 地緣政治緊張局勢：市場影響
  • 監管和技術格局

第3章 市場動態

  • 驅動程式
  • 限制因素
  • 機會
  • 趨勢

第4章 價格趨勢分析（2019-2032）

  • 區域定價分析
  • 按細分市場定價
  • 影響價格的因素

第5章 全球深度學習晶片組市場展望：過去（2019-2024）與預測（2025-2032）

  • 主要亮點
  • 全球深度學習晶片組市場展望（按類型）
    • 簡介/主要發現
    • 按類型分類的歷史市場規模分析（以金額為準，2019-2024）
    • 當前市場規模預測（按類型分類）（以金額為準，2025-2032）
      • 中央處理器（CPU）
      • 圖形處理單元 (GPU)
      • 現場可程式閘陣列（FPGA）
      • 專用積體電路（ASIC）
      • 其他（NPU、混合晶片）
    • 市場吸引力分析：按類型
  • 全球深度學習晶片組市場技術展望
    • 簡介/主要發現
    • 按技術分類的歷史市場規模分析（以金額為準，2019-2024 年）
    • 當前市場規模預測（按技術分類）（以金額為準，2025-2032）
      • 系統晶片(SOC)
      • 系統級封裝(SIP)
      • 多晶片模組
    • 市場吸引力分析：按技術

第6章全球深度學習晶片市場區域展望

  • 主要亮點
  • 按地區分類的歷史市場規模分析（以金額為準，2019-2024 年）
  • 各地區目前市場規模預測（以金額為準，2025-2032）
    • 北美洲
    • 歐洲
    • 東亞
    • 南亞和大洋洲
    • 拉丁美洲
    • 中東和非洲
  • 市場吸引力分析：按地區

第7章 北美深度學習晶片組市場展望：過去（2019-2024）與預測（2025-2032）

第 8 章歐洲深度學習晶片組市場展望：過去（2019-2024 年）與預測（2025-2032 年）

第9章東亞深度學習晶片組市場展望：過去（2019-2024）與預測（2025-2032）

第 10 章南亞和大洋洲深度學習晶片組市場展望：歷史（2019-2024 年）和預測（2025-2032 年）

第 11 章拉丁美洲深度學習晶片組市場展望：歷史（2019-2024 年）與預測（2025-2032 年）

第 12 章中東和非洲深度學習晶片組市場展望：歷史（2019-2024 年）和預測（2025-2032 年）

第13章競爭格局

  • 市場佔有率分析（2025年）
  • 市場結構
    • 競爭強度圖：按市場
    • 競爭儀錶板
  • 公司簡介
    • 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14章 附錄

  • 分析方法
  • 分析前提條件
  • 首字母縮寫和簡稱
簡介目錄
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