Deep Learning Processor Market Size, Share, Opportunities, COVID-19 Impact, And Trends By Chip Type (GPU, ASIC, CPU, FPGA), By Technology (System-On-Chip (SIC), System-IN-Package (SIP), Multi-Chip Module, Others ), By End-User Industry (Consumer Electronics, Communication & Technology ,Retail, Healthcare, Automotive, Others), And By Geography - Forecasts From 2022 To 2027

  • Published : Oct 2022
  • Report Code : KSI061611686
  • Pages : 142

The global deep learning processor market is projected to grow at a CAGR of 20.04% during the forecast period, reaching a market size of US$7.321 billion in 2027 from US$2.038 billion in 2020. Deep learning is a subset of machine learning, which is another subset of artificial intelligence.

The market for deep learning processors is growing owing to factors such as the growing volume of big data along with the increasing popularity of artificial intelligence and machine learning. Various industries are using AI technology, which is also driving the market growth of deep learning processors. The increasing amount of data generated nowadays from all technical sources is growing the requirement for faster and more advanced deep learning processors for faster analysis. The shifting trend towards quantum computing provides a great opportunity for the expansion of the deep learning processor market during the next five years. Increasing investments in smart homes and smart city projects in various countries will also lead to a surge in the adoption of deep learning processors, thus positively impacting the market growth in the near future. Other factors that offer growth potential for the deep learning processor market in the near future include rising investments in AI startups and R&D in smart robotics.

However, the lack of a skilled workforce is limiting the market growth of the deep learning processor market. A worker with the ability to process or carry out complex algorithms for AI development is required to manage deep learning software and its applications. Furthermore, managing AI and automated systems can be challenging at times. To get the most out of deep learning, exceptional software engineering skills and significant experience with distributed and concurrent programming, as well as debugging with communications protocols, are required.

The global deep-learning processor market is segmented by chip type, technology, end-user industry, and geography. By chip type, the market is segmented into ASIC, CPU, GPU and FPGA. On the basis of technology, the market is segmented by System-In-Package (SIP), Multi-Chip Module, System-On-Chip (SIC), and others. The market is further segmented by the end-user industry into consumer electronics, communication and technology, retail, healthcare, automotive, and others.

Chip-type GPU has a sizable share of the market

GPU (graphics processing units) account for a significant market share by chip type. It's becoming more popular for gaming and video viewing. However, as technology advances, the GPU is increasingly being used for high-resolution images and artificial intelligence (AI). The use of low-power technology is also increasing demand. The deep learning processor segment also consists of application-specific integrated circuits (ASICs) microprocessor units (CPUs), and field-programmable gate arrays (FPGAs). The increasing use of the quantum computing system is making the CPU chip segment grow at a substantial CAGR during the forecast period. Quantum computing is highly used these days by big multinational and information technology companies owing to their ability to solve complex algorithms in the fastest time. This positively impacts the market growth of deep-learning chips. The FPGAs chip market is growing as it makes configuration faster and with developing technology every year, customers need to update according to the current trend making them go for FPGA chips for faster change. To carry out specific tasks according to the requirements of the industry, companies are using ASIC chips for better performance and efficiency.

By technology, System-On-Chip has a sizable share of the market

The growing market for smartphones and tablets is increasing the demand for System-On-Chip processors in the market. A System-On-Chip includes a central processing unit, memory, input/output ports, and secondary storage – all on a single substrate or microchip, the size of a coin, which is perfectly suitable for smartphones. Smartphones and tablets are enabled with a System-on-chip to provide for better performance and faster processing of multi-task activities. The increasing use of 3D development is growing the market for System-In-package.

By end-user industry, Consumer Electronics is one of the important segments

A deep learning processor is widely used across the consumer electronics industry. The increasing advancement in technology is building the market for better devices with improved applications. The increasing use of artificial intelligence and machine learning, across this sector is growing the market for deep learning processors. Companies are using machine learning chips in smartphones to improve their features and maximise capabilities, like a faster processor and improved multi-tasking ability. Artificial intelligence applications are increasingly being embedded within smartphones and tablets to improve user interfaces and customer experiences, driving up demand for deep learning processors.  New devices are coming with advanced technologies for industries like healthcare and communication & technology, which are heavily using deep learning processors for faster work and higher efficiency. The retail industry will witness a decent CAGR between 2020 and 2027 owing to the booming e-commerce industry.  The rising application of deep learning processors in this industry is to improve customer experience by using artificial intelligence and augmented reality, which, in turn, is fueling the market growth of deep learning processors. 

North America is the major regional market

The global deep learning processor market is divided into five regions: North America, South America, Europe, the Middle East and Africa, and the Asia Pacific. North America accounted for the largest market share in 2020 and will continue its dominance throughout the forecast period. This dominance is majorly attributed to the early adoption of advanced technologies supported by the presence of major market players in the region. Rising investments in R&D to develop a wider range of applications of artificial intelligence in the U.S. are also bolstering market growth in this region. The APAC and European regional markets for deep learning processors will witness a significant market growth rate during the next five years.

Market Players and Competitive Intelligence

The competitive intelligence section covers major market players, their market shares, growth strategies, products, financials, and recent investments, among others. Key industry participants profiled as part of this section are NVIDIA Corporation, Microsoft, Arm Limited, Samsung, Alphabet, Qualcomm, Graphcore, Advanced Micro Devices, Adapteva, eSilicon Corporation, and Intel Corporation among others.

Recent development and expansion

  • Intel Corp. introduced its second-generation Habana AI, deep learning processors, in May 2022, delivering high performance and efficiency. The new chips are the Habana Gaudi2 and Habana Greco, which use 7-nanometer technology. It will provide customers with a wide range of solution options—from cloud to edge—to address the growing number and complexity of AI workloads.
  • In February 2022, AlphaICs announced the availability of engineering samples of the Gluon-Deep Learning Co-Processor' For Vision AI, an advanced edge inference chip that enables customers to add AI capability to existing X86 / ARM-based systems, resulting in significant cost savings. It has the best fps/watt performance for the classification and detection of Neural Networks on the market.
  • In August 2021, IBM introduced the On-Chip Accelerated Artificial Intelligence Processor. A new chip design enables the use of deep learning inference on high-value transactions, with the goal of greatly improving the ability to detect fraud, among other applications.

Covid 19 impact on Deep Learning Processor Market

Covid 19 had a significant impact on the manufacturing and industrial sectors, as deep learning processor production facilities were halted due to global restrictions and lockdowns. The pandemic also disrupted the supply chain, making raw materials and aircraft appliances difficult to obtain. As a result, market demand decreased and sales decreased.

Deep Learning Processor Market Scope:

 

Report Metric Details
 Market Size Value in 2020  US$2.038 billion
 Market Size Value in 2027  US$7.321 billion
 Growth Rate  CAGR of 20.04% from 2020 to 2027
 Base Year  2020
 Forecast Period  2022–2027
 Forecast Unit (Value)  USD Billion
 Segments Covered  Chip Type, Technology, End-User Industry, And Geography
 Regions Covered  North America, South America, Europe, Middle East and Africa, Asia Pacific
 Companies Covered ARM Limited, NVIDIA Corporation, Microsoft, Samsung, Alphabet, Qualcomm, Graphcore, Advanced Micro Devices, Adapteva, eSilicon Corporation, Intel Corporation
 Customization Scope  Free report customization with purchase

 

Market Segmentation

  • By Chip Type
    • GPU
    • ASIC
    • CPU
    • FPGA
  • By Technology
    • System-On-Chip (SIC)
    • System-IN-Package (SIP)
    • Multi-Chip Module
    • Others
  • By End-User Industry
    • Consumer Electronics
    • Communication & Technology
    • Retail
    • Healthcare
    • Automotive
    • Others
  • By Geography
    • North America
      • USA
      • Canada
      • Mexico
    • South America
      • Brazil
      • Argentina
      • Others
    • Europe
      • Germany
      • France
      • United Kingdom
      • Spain
      • Others
    • Middle East and Africa
      • Saudi Arabia
      • Israel
      • UAE
      • Others
    • Asia Pacific
      • China
      • Japan
      • South Korea
      • India
      • Thailand
      • Taiwan
      • Indonesia
      • Others

Frequently Asked Questions (FAQs)

The global deep learning processor market is projected to reach a total market size of US$7.321 billion by 2027.
The deep learning processor market is projected to grow at a CAGR of 20.04% during the forecast period.
Deep Learning Processor Market was valued at US$2.038 billion in 2020.
The deep learning processor market is growing owing to factors such as the growing volume of big data along with the increasing popularity of artificial intelligence and machine learning.
North America accounted for the major share of the deep learning processor market and will continue its dominance throughout the forecast period.

1. Introduction

1.1. Market Overview

1.2. Covid 19 Scenario

1.3. Market Definition

1.4. Market Segmentation

 

2. Research Methodology

2.1. Research Data

2.2. Assumptions

 

3. Executive Summary

3.1. Research Highlights

 

4. Market Dynamics

4.1. Market Drivers

4.2. Market Restraints

4.3. Porters Five Forces Analysis

4.3.1. Bargaining Power of Suppliers

4.3.2. Bargaining Power of Buyers

4.3.3. Threat of New Entrants

4.3.4. Threat of Substitutes

4.3.5. Competitive Rivalry in the Industry

4.4. Industry Value Chain Analysis

 

5. Global Deep Learning Processor Market Analysis, By Chip Type

5.1. Introduction

5.2. GPU

5.3. ASIC

5.4. CPU

5.5. FPGA

 

6. Global Deep Learning Processor Market Analysis, By Technology

6.1. Introduction

6.2. System-On-Chip (SIC)

6.3. System-IN-Package (SIP)

6.4. Multi-Chip Module

6.5. Others

 

7. Global Deep Learning Processor Market Analysis, By End-User industry

7.1. Introduction

7.2. Consumer Electronics

7.3. Communication & Technology

7.4. Retail

7.5. Healthcare

7.6. Automotive

7.7. Others

 

8. Global Deep Learning Processor Market Analysis, By Geography

8.1. Introduction

8.2. North America

8.3. North America

8.3.1. USA

8.3.2. Canada

8.3.3. Mexico

8.4. South America

8.4.1. Brazil

8.4.2. Argentina

8.4.3. Others

8.5. Europe

8.5.1. Germany

8.5.2. France

8.5.3. United Kingdom

8.5.4. Spain

8.5.5. Others

8.6. Middle East and Africa

8.6.1. Saudi Arabia

8.6.2. Israel

8.6.3. UAE

8.6.4. Others

8.7. Asia Pacific

8.7.1. China

8.7.2. Japan

8.7.3. South Korea

8.7.4. India

8.7.5. Thailand

8.7.6. Taiwan

8.7.7. Indonesia 

8.7.8. Others

 

9. Competitive Environment and Analysis

9.1. Major Players and Strategy Analysis

9.2. Emerging Players and Market Lucrativeness

9.3. Mergers, Acquisitions, Agreements, and Collaborations

9.4. Vendor Competitiveness Matrix

 

10. Company Profiles

10.1. ARM Limited

10.2. NVIDIA Corporation

10.3. Microsoft

10.4. Samsung

10.5. Alphabet

10.6. Qualcomm

10.7. Graphcore

10.8. Advanced Micro Devices

10.9. Adapteva

10.10. eSilicon Corporation

10.11. Intel Corporation


ARM Limited

NVIDIA Corporation

Microsoft

Samsung

Alphabet

Qualcomm

Graphcore

Advanced Micro Devices

Adapteva

eSilicon Corporation

Intel Corporation