Deep Learning Chipset Market by Type (Field Programmable Gate Arrays (FPGAs), Graphics Processing Units (GPUs), Central Processing Units (CPUs), Application Specific Integrated Circuits (ASICs)); by Architecture (Neuromorphic Architecture-Based Chips, Von Neumann Architecture-Based Chips); by Power Consumption (High (>100 W), Medium (5-100 W), Low (<5 W)); by Compute Capacity (High (> 1TFlops), Low (< 1TFlops)); by Application Domain (Training, Interference); by Vertical (Aerospace, Medical, Military & Defense, Automotive, Industrial, Consumer, Others); by Regional outlook (U.S., Rest of North America, France, UK, Germany, Spain, Italy, Rest of Europe, China, Japan, India, Southeast Asia, Rest of Asia Pacific, GCC Countries, Southern Africa, Rest of MEA, Brazil, Rest of Latin America) – Global Insights, Growth, Size, Comparative Analysis, Trends and Forecast, 2018 - 2026

Report ID :AMI-52 | Category : Information And Communication Technology | Published Date :June, 2018 | Pages : 293 | Format :PDF
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Industry Trends

Deep learning is a fast-growing machine learning method that extracts information by crunching through millions of pieces of data to detect and rank the most important aspects from the data. Deep learning has emerged as one of the most important computing models as organizations ranging from startups to large corporations seek to spur future growth, using these futuristic tools.

The deep learning chipset market, in terms of revenue, which was estimated at US$ 723 million in 2017, is expected to reach US$ 4,170.9 million by 2022.

Deep Learning Chipset Market, By Power Consumption, 2017 & 2022 (US$ Million)

Deep Learning Chipset Market

The deep learning chipset market is led by graphics processing units (GPUs) and central processing units (CPUs), but the expanded role of other chipset types including application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), and other emerging chipsets is expected during the forecast period. The deep learning segment of the Artificial Intelligence (AI) business has primarily been focused on software solutions. However, that’s changing now, with the arrival of microchips specifically designed to run deep learning algorithms. The AI system not only consists of software, it also requires high hardware functionality to support the calculations. Therefore, many companies are investing in developing their own chip designed to support AI development. This increased investment is driving the chipset market globally. Along with increased investments, the use of graphics processing unit (GPU) together with a CPU resulting in accelerated deep learning, analytics, and engineering applications is also a major driving force.

However, according to industry experts, the current deep learning technology lacks abstraction and reasoning abilities. Such technological limitations of deep learning are expected to limit the growth of deep learning chipset market in near future, but multiple deep learning companies are continuously investing in research and development to overcome these limitations.

Deep learning Chipset Market, By Type

On the basis of type, graphics processing units (GPUs) segment is expected to be the most attractive segment of global market. Almost all machine learning involving the artificial neural network (ANN) approach uses a combination of standard GPU chips (graphics processing units) and CPU chips (central processing units) in large data centers. However, a graphics processing unit enables to render images more rapidly than a central processing unit because of its parallel processing architecture, which permits it to perform several calculations at the same time. This has enabled GPUs to occupy the largest market share in terms of revenue in the year 2017.

Deep Learning Chipset Market, By Region

On the basis of geography, North America is currently leading the market and is projected to be in the leading position for the next few years owing to the wide adoption of deep learning technology. The growth of the market in North America is attributed to the presence of leading players, high government funding and strong technical base. However, the Asia Pacific deep learning chipset market is expected to be the fastest-growing regional market due to increasing spending on artificial intelligence and cognitive computing technologies.

Competitive Landscape

The report provides both, qualitative and quantitative research of the market, as well as provides worthy insights into the rational scenario and favored development methods adopted by the key contenders. The report also offers extensive research on the key players in this market and detailed insights on the competitiveness of these players. The key business strategies such as mergers & acquisitions (M&A), affiliations, collaborations, and contracts adopted by the major players are also recognized and analyzed in the report. For each company, the deep learning chipset market report recognizes their manufacturing base, competitors, product/service type, application and specification, pricing, and gross margin.

Some of the primary market participants are Amazon Web Services, Inc., ARM Limited, CEVA Inc., Facebook, Google LLC., Graphcore, IBM Corporation, Intel Corporation, Nvidia Corporation, Qualcomm Technologies, Inc., Teradeep Inc., and Xilinx Inc. amongst others.

Global Deep Learning Chipset Industry Background

Deep Learning Chipset Market

Deep Learning Chipset Market

1.    Introduction

1.1.   Market Scope

1.2.   Market Segmentation

1.3.   Methodology

1.4.   Assumptions

2.    Deep Learning Chipset Market Snapshot

3.    Executive Summary: Deep Learning Chipset Market

4.    Qualitative Analysis: Deep Learning Chipset Market

4.1.   Introduction

4.1.1.   Product Definition

4.1.2.   Industry Development

4.2.   Market Dynamics

4.2.1.   Drivers

4.2.2.   Restraints

4.2.3.   Opportunities

4.3.   Trends in Market

5.    Global Deep Learning Chipset Market Analysis and Forecasts, 2018 – 2026

5.1.   Overview

5.1.1.   Global Market Revenue (US$ Mn) and Forecasts

5.2.   Global Market Revenue (US$ Mn) and Forecasts, By Type

5.2.1.   Field Programmable Gate Arrays (FPGAs)

5.2.1.1.    Definition

5.2.1.2.    Market Penetration

5.2.1.3.    Market Revenue Expected to Increase by 2026

5.2.1.4.    Compound Annual Growth Rate (CAGR)

5.2.2.   Graphic Processing Units (GPUs)

5.2.2.1.    Definition

5.2.2.2.    Market Penetration

5.2.2.3.    Market Revenue Expected to Increase by 2026

5.2.2.4.    Compound Annual Growth Rate (CAGR)

5.2.3.   Central Processing Units (CPUs)

5.2.3.1.    Definition

5.2.3.2.    Market Penetration

5.2.3.3.    Market Revenue Expected to Increase by 2026

5.2.3.4.    Compound Annual Growth Rate (CAGR)

5.2.4.   Application Specific Integrated Circuits (ASICs)

5.2.4.1.    Definition

5.2.4.2.    Market Penetration

5.2.4.3.    Market Revenue Expected to Increase by 2026

5.2.4.4.    Compound Annual Growth Rate (CAGR)

5.3.   Key Segment for Channeling Investments

5.3.1.   By Type

6.    Global Deep Learning Chipset Market Analysis and Forecasts, 2018 – 2026

6.1.   Overview

6.2.   Global Market Revenue (US$ Mn) and Forecasts, By Architecture

6.2.1.   Von Neumann Architecture-Based Chips

6.2.1.1.    Definition

6.2.1.2.    Market Penetration

6.2.1.3.    Market Revenue Expected to Increase by 2026

6.2.1.4.    Compound Annual Growth Rate (CAGR)

6.2.2.   Neuromorphic Architecture-Based Chips

6.2.2.1.    Definition

6.2.2.2.    Market Penetration

6.2.2.3.    Market Revenue Expected to Increase by 2026

6.2.2.4.    Compound Annual Growth Rate (CAGR)

6.3.   Key Segment for Channeling Investments

6.3.1.   By Architecture

7.    Global Deep Learning Chipset Market Analysis and Forecasts, 2018 – 2026

7.1.   Overview

7.2.   Global Market Revenue (US$ Mn) and Forecasts, By Power Consumption

7.2.1.   High (>100 W)

7.2.1.1.    Definition

7.2.1.2.    Market Penetration

7.2.1.3.    Market Revenue Expected to Increase by 2026

7.2.1.4.    Compound Annual Growth Rate (CAGR)

7.2.2.   Medium (5-100 W)

7.2.2.1.    Definition

7.2.2.2.    Market Penetration

7.2.2.3.    Market Revenue Expected to Increase by 2026

7.2.2.4.    Compound Annual Growth Rate (CAGR)

7.2.3.   Low (< 5 W)

7.2.3.1.    Definition

7.2.3.2.    Market Penetration

7.2.3.3.    Market Revenue Expected to Increase by 2026

7.2.3.4.    Compound Annual Growth Rate (CAGR)

7.3.   Key Segment for Channeling Investments

7.3.1.   By Power Consumption

8.    Global Deep Learning Chipset Market Analysis and Forecasts, 2018 – 2026

8.1.   Overview

8.2.   Global Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

8.2.1.   High (>1TFlops)

8.2.1.1.    Definition

8.2.1.2.    Market Penetration

8.2.1.3.    Market Revenue Expected to Increase by 2026

8.2.1.4.    Compound Annual Growth Rate (CAGR)

8.2.2.   Low (<1TFlops)

8.2.2.1.    Definition

8.2.2.2.    Market Penetration

8.2.2.3.    Market Revenue Expected to Increase by 2026

8.2.2.4.    Compound Annual Growth Rate (CAGR)

8.3.   Key Segment for Channeling Investments

8.3.1.   By Compute Capacity

9.    Global Deep Learning Chipset Market Analysis and Forecasts, 2018 – 2026

9.1.   Overview

9.2.   Global Market Revenue (US$ Mn) and Forecasts, By Application Domain

9.2.1.   Training

9.2.1.1.    Definition

9.2.1.2.    Market Penetration

9.2.1.3.    Market Revenue Expected to Increase by 2026

9.2.1.4.    Compound Annual Growth Rate (CAGR)

9.2.2.   Interference

9.2.2.1.    Definition

9.2.2.2.    Market Penetration

9.2.2.3.    Market Revenue Expected to Increase by 2026

9.2.2.4.    Compound Annual Growth Rate (CAGR)

9.3.   Key Segment for Channeling Investments

9.3.1.   By Application Domain

10. Global Deep Learning Chipset Market Analysis and Forecasts, 2018 – 2026

10.1. Overview

10.2. Global Market Revenue (US$ Mn) and Forecasts, By Vertical

10.2.1. Consumer

10.2.1.1.  Definition

10.2.1.2.  Market Penetration

10.2.1.3.  Market Revenue Expected to Increase by 2026

10.2.1.4.  Compound Annual Growth Rate (CAGR)

10.2.2. Industrial

10.2.2.1.  Definition

10.2.2.2.  Market Penetration

10.2.2.3.  Market Revenue Expected to Increase by 2026

10.2.2.4.  Compound Annual Growth Rate (CAGR)

10.2.3. Automotive

10.2.3.1.  Definition

10.2.3.2.  Market Penetration

10.2.3.3.  Market Revenue Expected to Increase by 2026

10.2.3.4.  Compound Annual Growth Rate (CAGR)

10.2.4. Military and Defense

10.2.4.1.  Definition

10.2.4.2.  Market Penetration

10.2.4.3.  Market Revenue Expected to Increase by 2026

10.2.4.4.  Compound Annual Growth Rate (CAGR)

10.2.5. Medical

10.2.5.1.  Definition

10.2.5.2.  Market Penetration

10.2.5.3.  Market Revenue Expected to Increase by 2026

10.2.5.4.  Compound Annual Growth Rate (CAGR)

10.2.6. Aerospace

10.2.6.1.  Definition

10.2.6.2.  Market Penetration

10.2.6.3.  Market Revenue Expected to Increase by 2026

10.2.6.4.  Compound Annual Growth Rate (CAGR)

10.2.7. Others

10.2.7.1.  Definition

10.2.7.2.  Market Penetration

10.2.7.3.  Market Revenue Expected to Increase by 2026

10.2.7.4.  Compound Annual Growth Rate (CAGR)

10.3. Key Segment for Channeling Investments

10.3.1. By Vertical

11. North America Deep Learning Chipset Market Analysis and Forecasts, 2018 – 2026

11.1. Overview

11.1.1. North America Market Revenue (US$ Mn)

11.2. North America Market Revenue (US$ Mn) and Forecasts, By Type

11.2.1. Field Programmable Gate Arrays (FPGAs)

11.2.2. Graphic Processing Units (GPUs)

11.2.3. Central Processing Units (CPUs)

11.2.4. Application Specific Integrated Circuits (ASICs)

11.3. North America Market Revenue (US$ Mn) and Forecasts, By Architecture

11.3.1. Von Neumann Architecture-Based Chips

11.3.2. Neuromorphic Architecture-Based Chips

11.4. North America Market Revenue (US$ Mn) and Forecasts, By Power Consumption

11.4.1. High (>100 W)

11.4.2. Medium (5-100 W)

11.4.3. Low (< 5 W)

11.5. North America Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

11.5.1. High (>1TFlops)

11.5.2. Low (<1TFlops)

11.6. North America Market Revenue (US$ Mn) and Forecasts, By Application Domain

11.6.1. Training

11.6.2. Interference

11.7. North America Market Revenue (US$ Mn) and Forecasts, By Vertical

11.7.1. Consumer

11.7.2. Industrial

11.7.3. Automotive

11.7.4. Military and Defense

11.7.5. Medical

11.7.6. Aerospace

11.7.7. Others

11.8. North America Market Revenue (US$ Mn) and Forecasts, By Country

11.8.1. U.S.

11.8.1.1.  U.S. Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

11.8.1.1.1.  Field Programmable Gate Arrays (FPGAs)

11.8.1.1.2.  Graphic Processing Units (GPUs)

11.8.1.1.3.  Central Processing Units (CPUs)

11.8.1.1.4.  Application Specific Integrated Circuits (ASICs)

11.8.1.2.  U.S. Market Revenue (US$ Mn) and Forecasts, By Architecture

11.8.1.2.1.  Von Neumann Architecture-Based Chips

11.8.1.2.2.  Neuromorphic Architecture-Based Chips

11.8.1.3.  U.S. Market Revenue (US$ Mn) and Forecasts, By Power Consumption

11.8.1.3.1.  High (>100 W)

11.8.1.3.2.  Medium (5-100 W)

11.8.1.3.3.  Low (< 5 W)

11.8.1.4.  U.S. Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

11.8.1.4.1.  High (>1TFlops)

11.8.1.4.2.  Low (<1TFlops)

11.8.1.5.  U.S. Market Revenue (US$ Mn) and Forecasts, By Application Domain

11.8.1.5.1.  Training

11.8.1.5.2.  Interference

11.8.1.6.  U.S. Market Revenue (US$ Mn) and Forecasts, By Vertical

11.8.1.6.1.  Consumer

11.8.1.6.2.  Industrial

11.8.1.6.3.  Automotive

11.8.1.6.4.  Military and Defense

11.8.1.6.5.  Medical

11.8.1.6.6.  Aerospace

11.8.1.6.7.  Others

11.8.2. Rest of North America

11.8.2.1.  Rest of North America Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

11.8.2.1.1.  Field Programmable Gate Arrays (FPGAs)

11.8.2.1.2.  Graphic Processing Units (GPUs)

11.8.2.1.3.  Central Processing Units (CPUs)

11.8.2.1.4.  Application Specific Integrated Circuits (ASICs)

11.8.2.2.  Rest of North America Market Revenue (US$ Mn) and Forecasts, By Architecture

11.8.2.2.1.  Von Neumann Architecture-Based Chips

11.8.2.2.2.  Neuromorphic Architecture-Based Chips

11.8.2.3.  Rest of North America Market Revenue (US$ Mn) and Forecasts, By Power Consumption

11.8.2.3.1.  High (>100 W)

11.8.2.3.2.  Medium (5-100 W)

11.8.2.3.3.  Low (< 5 W)

11.8.2.4.  Rest of North America Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

11.8.2.4.1.  High (>1TFlops)

11.8.2.4.2.  Low (<1TFlops)

11.8.2.5.  Rest of North America Market Revenue (US$ Mn) and Forecasts, By Application Domain

11.8.2.5.1.  Training

11.8.2.5.2.  Interference

11.8.2.6.  Rest of North America Market Revenue (US$ Mn) and Forecasts, By Vertical

11.8.2.6.1.  Consumer

11.8.2.6.2.  Industrial

11.8.2.6.3.  Automotive

11.8.2.6.4.  Military and Defense

11.8.2.6.5.  Medical

11.8.2.6.6.  Aerospace

11.8.2.6.7.  Others

11.9. Key Segment for Channeling Investments

11.9.1. By Country

11.9.2. By Type

11.9.3. By Architecture

11.9.4. By Power Consumption

11.9.5. By Compute Capacity

11.9.6. By Application Domain

11.9.7. By Vertical

12. Europe Deep Learning Chipset Market Analysis and Forecasts, 2018 – 2026

12.1. Overview

12.1.1. Europe Market Revenue (US$ Mn)

12.2. Europe Market Revenue (US$ Mn) and Forecasts, By Type

12.2.1. Field Programmable Gate Arrays (FPGAs)

12.2.2. Graphic Processing Units (GPUs)

12.2.3. Central Processing Units (CPUs)

12.2.4. Application Specific Integrated Circuits (ASICs)

12.3. Europe Market Revenue (US$ Mn) and Forecasts, By Architecture

12.3.1. Von Neumann Architecture-Based Chips

12.3.2. Neuromorphic Architecture-Based Chips

12.4. Europe Market Revenue (US$ Mn) and Forecasts, By Power Consumption

12.4.1. High (>100 W)

12.4.2. Medium (5-100 W)

12.4.3. Low (< 5 W)

12.5. Europe Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

12.5.1. High (>1TFlops)

12.5.2. Low (<1TFlops)

12.6. Europe Market Revenue (US$ Mn) and Forecasts, By Application Domain

12.6.1. Training

12.6.2. Interference

12.7. Europe Market Revenue (US$ Mn) and Forecasts, By Vertical

12.7.1. Consumer

12.7.2. Industrial

12.7.3. Automotive

12.7.4. Military and Defense

12.7.5. Medical

12.7.6. Aerospace

12.7.7. Others

12.8. Europe Market Revenue (US$ Mn) and Forecasts, By Country

12.8.1. France

12.8.1.1.  France Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

12.8.1.1.1.  Field Programmable Gate Arrays (FPGAs)

12.8.1.1.2.  Graphic Processing Units (GPUs)

12.8.1.1.3.  Central Processing Units (CPUs)

12.8.1.1.4.  Application Specific Integrated Circuits (ASICs)

12.8.1.2.  France Market Revenue (US$ Mn) and Forecasts, By Architecture

12.8.1.2.1.  Von Neumann Architecture-Based Chips

12.8.1.2.2.  Neuromorphic Architecture-Based Chips

12.8.1.3.  France Market Revenue (US$ Mn) and Forecasts, By Power Consumption

12.8.1.3.1.  High (>100 W)

12.8.1.3.2.  Medium (5-100 W)

12.8.1.3.3.  Low (< 5 W)

12.8.1.4.  France Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

12.8.1.4.1.  High (>1TFlops)

12.8.1.4.2.  Low (<1TFlops)

12.8.1.5.  France Market Revenue (US$ Mn) and Forecasts, By Application Domain

12.8.1.5.1.  Training

12.8.1.5.2.  Interference

12.8.1.6.  France Market Revenue (US$ Mn) and Forecasts, By Vertical

12.8.1.6.1.  Consumer

12.8.1.6.2.  Industrial

12.8.1.6.3.  Automotive

12.8.1.6.4.  Military and Defense

12.8.1.6.5.  Medical

12.8.1.6.6.  Aerospace

12.8.1.6.7.  Others

12.8.2. The UK

12.8.2.1.  The UK Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

12.8.2.1.1.  Field Programmable Gate Arrays (FPGAs)

12.8.2.1.2.  Graphic Processing Units (GPUs)

12.8.2.1.3.  Central Processing Units (CPUs)

12.8.2.1.4.  Application Specific Integrated Circuits (ASICs)

12.8.2.2.  The UK Market Revenue (US$ Mn) and Forecasts, By Architecture

12.8.2.2.1.  Von Neumann Architecture-Based Chips

12.8.2.2.2.  Neuromorphic Architecture-Based Chips

12.8.2.3.  The UK Market Revenue (US$ Mn) and Forecasts, By Power Consumption

12.8.2.3.1.  High (>100 W)

12.8.2.3.2.  Medium (5-100 W)

12.8.2.3.3.  Low (< 5 W)

12.8.2.4.  The UK Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

12.8.2.4.1.  High (>1TFlops)

12.8.2.4.2.  Low (<1TFlops)

12.8.2.5.  The UK Market Revenue (US$ Mn) and Forecasts, By Application Domain

12.8.2.5.1.  Training

12.8.2.5.2.  Interference

12.8.2.6.  The UK Market Revenue (US$ Mn) and Forecasts, By Vertical

12.8.2.6.1.  Consumer

12.8.2.6.2.  Industrial

12.8.2.6.3.  Automotive

12.8.2.6.4.  Military and Defense

12.8.2.6.5.  Medical

12.8.2.6.6.  Aerospace

12.8.2.6.7.  Others

12.8.3. Spain

12.8.3.1.  Spain Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

12.8.3.1.1.  Field Programmable Gate Arrays (FPGAs)

12.8.3.1.2.  Graphic Processing Units (GPUs)

12.8.3.1.3.  Central Processing Units (CPUs)

12.8.3.1.4.  Application Specific Integrated Circuits (ASICs)

12.8.3.2.  Spain Market Revenue (US$ Mn) and Forecasts, By Architecture

12.8.3.2.1.  Von Neumann Architecture-Based Chips

12.8.3.2.2.  Neuromorphic Architecture-Based Chips

12.8.3.3.  Spain Market Revenue (US$ Mn) and Forecasts, By Power Consumption

12.8.3.3.1.  High (>100 W)

12.8.3.3.2.  Medium (5-100 W)

12.8.3.3.3.  Low (< 5 W)

12.8.3.4.  Spain Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

12.8.3.4.1.  High (>1TFlops)

12.8.3.4.2.  Low (<1TFlops)

12.8.3.5.  Spain Market Revenue (US$ Mn) and Forecasts, By Application Domain

12.8.3.5.1.  Training

12.8.3.5.2.  Interference

12.8.3.6.  Spain Market Revenue (US$ Mn) and Forecasts, By Vertical

12.8.3.6.1.  Consumer

12.8.3.6.2.  Industrial

12.8.3.6.3.  Automotive

12.8.3.6.4.  Military and Defense

12.8.3.6.5.  Medical

12.8.3.6.6.  Aerospace

12.8.3.6.7.  Others

12.8.4. Germany

12.8.4.1.  Germany Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

12.8.4.1.1.  Field Programmable Gate Arrays (FPGAs)

12.8.4.1.2.  Graphic Processing Units (GPUs)

12.8.4.1.3.  Central Processing Units (CPUs)

12.8.4.1.4.  Application Specific Integrated Circuits (ASICs)

12.8.4.2.  Germany Market Revenue (US$ Mn) and Forecasts, By Architecture

12.8.4.2.1.  Von Neumann Architecture-Based Chips

12.8.4.2.2.  Neuromorphic Architecture-Based Chips

12.8.4.3.  Germany Market Revenue (US$ Mn) and Forecasts, By Power Consumption

12.8.4.3.1.  High (>100 W)

12.8.4.3.2.  Medium (5-100 W)

12.8.4.3.3.  Low (< 5 W)

12.8.4.4.  Germany Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

12.8.4.4.1.  High (>1TFlops)

12.8.4.4.2.  Low (<1TFlops)

12.8.4.5.  Germany Market Revenue (US$ Mn) and Forecasts, By Application Domain

12.8.4.5.1.  Training

12.8.4.5.2.  Interference

12.8.4.6.  Germany Market Revenue (US$ Mn) and Forecasts, By Vertical

12.8.4.6.1.  Consumer

12.8.4.6.2.  Industrial

12.8.4.6.3.  Automotive

12.8.4.6.4.  Military and Defense

12.8.4.6.5.  Medical

12.8.4.6.6.  Aerospace

12.8.4.6.7.  Others

12.8.5. Italy

12.8.5.1.  Italy Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

12.8.5.1.1.  Field Programmable Gate Arrays (FPGAs)

12.8.5.1.2.  Graphic Processing Units (GPUs)

12.8.5.1.3.  Central Processing Units (CPUs)

12.8.5.1.4.  Application Specific Integrated Circuits (ASICs)

12.8.5.2.  Italy Market Revenue (US$ Mn) and Forecasts, By Architecture

12.8.5.2.1.  Von Neumann Architecture-Based Chips

12.8.5.2.2.  Neuromorphic Architecture-Based Chips

12.8.5.3.  Italy Market Revenue (US$ Mn) and Forecasts, By Power Consumption

12.8.5.3.1.  High (>100 W)

12.8.5.3.2.  Medium (5-100 W)

12.8.5.3.3.  Low (< 5 W)

12.8.5.4.  Italy Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

12.8.5.4.1.  High (>1TFlops)

12.8.5.4.2.  Low (<1TFlops)

12.8.5.5.  Italy Market Revenue (US$ Mn) and Forecasts, By Application Domain

12.8.5.5.1.  Training

12.8.5.5.2.  Interference

12.8.5.6.  Italy Market Revenue (US$ Mn) and Forecasts, By Vertical

12.8.5.6.1.  Consumer

12.8.5.6.2.  Industrial

12.8.5.6.3.  Automotive

12.8.5.6.4.  Military and Defense

12.8.5.6.5.  Medical

12.8.5.6.6.  Aerospace

12.8.5.6.7.  Others

12.8.6. Rest of Europe

12.8.6.1.  Rest of Europe Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

12.8.6.1.1.  Field Programmable Gate Arrays (FPGAs)

12.8.6.1.2.  Graphic Processing Units (GPUs)

12.8.6.1.3.  Central Processing Units (CPUs)

12.8.6.1.4.  Application Specific Integrated Circuits (ASICs)

12.8.6.2.  Rest of Europe Market Revenue (US$ Mn) and Forecasts, By Architecture

12.8.6.2.1.  Von Neumann Architecture-Based Chips

12.8.6.2.2.  Neuromorphic Architecture-Based Chips

12.8.6.3.  Rest of Europe Market Revenue (US$ Mn) and Forecasts, By Power Consumption

12.8.6.3.1.  High (>100 W)

12.8.6.3.2.  Medium (5-100 W)

12.8.6.3.3.  Low (< 5 W)

12.8.6.4.  Rest of Europe Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

12.8.6.4.1.  High (>1TFlops)

12.8.6.4.2.  Low (<1TFlops)

12.8.6.5.  Rest of Europe Market Revenue (US$ Mn) and Forecasts, By Application Domain

12.8.6.5.1.  Training

12.8.6.5.2.  Interference

12.8.6.6.  Rest of Europe Market Revenue (US$ Mn) and Forecasts, By Vertical

12.8.6.6.1.  Consumer

12.8.6.6.2.  Industrial

12.8.6.6.3.  Automotive

12.8.6.6.4.  Military and Defense

12.8.6.6.5.  Medical

12.8.6.6.6.  Aerospace

12.8.6.6.7.  Others

12.9. Key Segment for Channeling Investments

12.9.1. By Country

12.9.2. By Type

12.9.3. By Architecture

12.9.4. By Power Consumption

12.9.5. By Compute Capacity

12.9.6. By Application Domain

12.9.7. By Vertical

13. Asia Pacific Deep Learning Chipset Market Analysis and Forecasts, 2018 – 2026

13.1. Overview

13.1.1. Asia Pacific Market Revenue (US$ Mn)

13.2. Asia Pacific Market Revenue (US$ Mn) and Forecasts, By Type

13.2.1. Field Programmable Gate Arrays (FPGAs)

13.2.2. Graphic Processing Units (GPUs)

13.2.3. Central Processing Units (CPUs)

13.2.4. Application Specific Integrated Circuits (ASICs)

13.3. Asia Pacific Market Revenue (US$ Mn) and Forecasts, By Architecture

13.3.1. Von Neumann Architecture-Based Chips

13.3.2. Neuromorphic Architecture-Based Chips

13.4. Asia Pacific Market Revenue (US$ Mn) and Forecasts, By Power Consumption

13.4.1. High (>100 W)

13.4.2. Medium (5-100 W)

13.4.3. Low (< 5 W)

13.5. Asia Pacific Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

13.5.1. High (>1TFlops)

13.5.2. Low (<1TFlops)

13.6. Asia Pacific Market Revenue (US$ Mn) and Forecasts, By Application Domain

13.6.1. Training

13.6.2. Interference

13.7. Asia Pacific Market Revenue (US$ Mn) and Forecasts, By Vertical

13.7.1. Consumer

13.7.2. Industrial

13.7.3. Automotive

13.7.4. Military and Defense

13.7.5. Medical

13.7.6. Aerospace

13.7.7. Others

13.8. Asia Pacific Market Revenue (US$ Mn) and Forecasts, By Country

13.8.1. China

13.8.1.1.  China Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

13.8.1.1.1.  Field Programmable Gate Arrays (FPGAs)

13.8.1.1.2.  Graphic Processing Units (GPUs)

13.8.1.1.3.  Central Processing Units (CPUs)

13.8.1.1.4.  Application Specific Integrated Circuits (ASICs)

13.8.1.2.  China Market Revenue (US$ Mn) and Forecasts, By Architecture

13.8.1.2.1.  Von Neumann Architecture-Based Chips

13.8.1.2.2.  Neuromorphic Architecture-Based Chips

13.8.1.3.  China Market Revenue (US$ Mn) and Forecasts, By Power Consumption

13.8.1.3.1.  High (>100 W)

13.8.1.3.2.  Medium (5-100 W)

13.8.1.3.3.  Low (< 5 W)

13.8.1.4.  China Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

13.8.1.4.1.  High (>1TFlops)

13.8.1.4.2.  Low (<1TFlops)

13.8.1.5.  China Market Revenue (US$ Mn) and Forecasts, By Application Domain

13.8.1.5.1.  Training

13.8.1.5.2.  Interference

13.8.1.6.  China Market Revenue (US$ Mn) and Forecasts, By Vertical

13.8.1.6.1.  Consumer

13.8.1.6.2.  Industrial

13.8.1.6.3.  Automotive

13.8.1.6.4.  Military and Defense

13.8.1.6.5.  Medical

13.8.1.6.6.  Aerospace

13.8.1.6.7.  Others

13.8.2. Japan

13.8.2.1.  Japan Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

13.8.2.1.1.  Field Programmable Gate Arrays (FPGAs)

13.8.2.1.2.  Graphic Processing Units (GPUs)

13.8.2.1.3.  Central Processing Units (CPUs)

13.8.2.1.4.  Application Specific Integrated Circuits (ASICs)

13.8.2.2.  Japan Market Revenue (US$ Mn) and Forecasts, By Architecture

13.8.2.2.1.  Von Neumann Architecture-Based Chips

13.8.2.2.2.  Neuromorphic Architecture-Based Chips

13.8.2.3.  Japan Market Revenue (US$ Mn) and Forecasts, By Power Consumption

13.8.2.3.1.  High (>100 W)

13.8.2.3.2.  Medium (5-100 W)

13.8.2.3.3.  Low (< 5 W)

13.8.2.4.  Japan Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

13.8.2.4.1.  High (>1TFlops)

13.8.2.4.2.  Low (<1TFlops)

13.8.2.5.  Japan Market Revenue (US$ Mn) and Forecasts, By Application Domain

13.8.2.5.1.  Training

13.8.2.5.2.  Interference

13.8.2.6.  Japan Market Revenue (US$ Mn) and Forecasts, By Vertical

13.8.2.6.1.  Consumer

13.8.2.6.2.  Industrial

13.8.2.6.3.  Automotive

13.8.2.6.4.  Military and Defense

13.8.2.6.5.  Medical

13.8.2.6.6.  Aerospace

13.8.2.6.7.  Others

13.8.3. India

13.8.3.1.  India Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

13.8.3.1.1.  Field Programmable Gate Arrays (FPGAs)

13.8.3.1.2.  Graphic Processing Units (GPUs)

13.8.3.1.3.  Central Processing Units (CPUs)

13.8.3.1.4.  Application Specific Integrated Circuits (ASICs)

13.8.3.2.  India Market Revenue (US$ Mn) and Forecasts, By Architecture

13.8.3.2.1.  Von Neumann Architecture-Based Chips

13.8.3.2.2.  Neuromorphic Architecture-Based Chips

13.8.3.3.  India Market Revenue (US$ Mn) and Forecasts, By Power Consumption

13.8.3.3.1.  High (>100 W)

13.8.3.3.2.  Medium (5-100 W)

13.8.3.3.3.  Low (< 5 W)

13.8.3.4.  India Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

13.8.3.4.1.  High (>1TFlops)

13.8.3.4.2.  Low (<1TFlops)

13.8.3.5.  India Market Revenue (US$ Mn) and Forecasts, By Application Domain

13.8.3.5.1.  Training

13.8.3.5.2.  Interference

13.8.3.6.  India Market Revenue (US$ Mn) and Forecasts, By Vertical

13.8.3.6.1.  Consumer

13.8.3.6.2.  Industrial

13.8.3.6.3.  Automotive

13.8.3.6.4.  Military and Defense

13.8.3.6.5.  Medical

13.8.3.6.6.  Aerospace

13.8.3.6.7.  Others

13.8.4. Southeast Asia

13.8.4.1.  Southeast Asia Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

13.8.4.1.1.  Field Programmable Gate Arrays (FPGAs)

13.8.4.1.2.  Graphic Processing Units (GPUs)

13.8.4.1.3.  Central Processing Units (CPUs)

13.8.4.1.4.  Application Specific Integrated Circuits (ASICs)

13.8.4.2.  Southeast Asia Market Revenue (US$ Mn) and Forecasts, By Architecture

13.8.4.2.1.  Von Neumann Architecture-Based Chips

13.8.4.2.2.  Neuromorphic Architecture-Based Chips

13.8.4.3.  Southeast Asia Market Revenue (US$ Mn) and Forecasts, By Power Consumption

13.8.4.3.1.  High (>100 W)

13.8.4.3.2.  Medium (5-100 W)

13.8.4.3.3.  Low (< 5 W)

13.8.4.4.  Southeast Asia Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

13.8.4.4.1.  High (>1TFlops)

13.8.4.4.2.  Low (<1TFlops)

13.8.4.5.  Southeast Asia Market Revenue (US$ Mn) and Forecasts, By Application Domain

13.8.4.5.1.  Training

13.8.4.5.2.  Interference

13.8.4.6.  Southeast Asia Market Revenue (US$ Mn) and Forecasts, By Vertical

13.8.4.6.1.  Consumer

13.8.4.6.2.  Industrial

13.8.4.6.3.  Automotive

13.8.4.6.4.  Military and Defense

13.8.4.6.5.  Medical

13.8.4.6.6.  Aerospace

13.8.4.6.7.  Others

13.8.5. Rest of Asia Pacific

13.8.5.1.  Rest of Asia Pacific Market Revenue (US$ Mn) and Forecasts, By Type

13.8.5.1.1.  Field Programmable Gate Arrays (FPGAs)

13.8.5.1.2.  Graphic Processing Units (GPUs)

13.8.5.1.3.  Central Processing Units (CPUs)

13.8.5.1.4.  Application Specific Integrated Circuits (ASICs)

13.8.5.2.  Rest of Asia Pacific Market Revenue (US$ Mn) and Forecasts, By Architecture

13.8.5.2.1.  Von Neumann Architecture-Based Chips

13.8.5.2.2.  Neuromorphic Architecture-Based Chips

13.8.5.3.  Rest of Asia Pacific Market Revenue (US$ Mn) and Forecasts, By Power Consumption

13.8.5.3.1.  High (>100 W)

13.8.5.3.2.  Medium (5-100 W)

13.8.5.3.3.  Low (< 5 W)

13.8.5.4.  Rest of Asia Pacific Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

13.8.5.4.1.  High (>1TFlops)

13.8.5.4.2.  Low (<1TFlops)

13.8.5.5.  Rest of Asia Pacific Market Revenue (US$ Mn) and Forecasts, By Application Domain

13.8.5.5.1.  Training

13.8.5.5.2.  Interference

13.8.5.6.  Rest of Asia Pacific Market Revenue (US$ Mn) and Forecasts, By Vertical

13.8.5.6.1.  Consumer

13.8.5.6.2.  Industrial

13.8.5.6.3.  Automotive

13.8.5.6.4.  Military and Defense

13.8.5.6.5.  Medical

13.8.5.6.6.  Aerospace

13.8.5.6.7.  Others

13.9. Key Segment for Channeling Investments

13.9.1. By Country

13.9.2. By Type

13.9.3. By Architecture

13.9.4. By Power Consumption

13.9.5. By Compute Capacity

13.9.6. By Application Domain

13.9.7. By Vertical

14. Middle East and Africa Deep Learning Chipset Market Analysis and Forecasts, 2018 – 2026

14.1. Overview

14.1.1. Middle East and Africa Market Revenue (US$ Mn)

14.2. Middle East and Africa Market Revenue (US$ Mn) and Forecasts, By Type

14.2.1. Field Programmable Gate Arrays (FPGAs)

14.2.2. Graphic Processing Units (GPUs)

14.2.3. Central Processing Units (CPUs)

14.2.4. Application Specific Integrated Circuits (ASICs)

14.3. Middle East and Africa Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Architecture

14.3.1. Von Neumann Architecture-Based Chips

14.3.2. Neuromorphic Architecture-Based Chips

14.4. Middle East and Africa Market Revenue (US$ Mn) and Forecasts, By Power Consumption

14.4.1. High (>100 W)

14.4.2. Medium (5-100 W)

14.4.3. Low (< 5 W)

14.5. Middle East and Africa Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

14.5.1. High (>1TFlops)

14.5.2. Low (<1TFlops)

14.6. Middle East and Africa Market Revenue (US$ Mn) and Forecasts, By Application Domain

14.6.1. Training

14.6.2. Interference

14.7. Middle East and Africa Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Vertical

14.7.1. Consumer

14.7.2. Industrial

14.7.3. Automotive

14.7.4. Military and Defense

14.7.5. Medical

14.7.6. Aerospace

14.7.7. Others

14.8. Middle East and Africa Market Revenue (US$ Mn) and Forecasts, By Country

14.8.1. GCC Countries

14.8.1.1.  GCC Countries Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

14.8.1.1.1.  Field Programmable Gate Arrays (FPGAs)

14.8.1.1.2.  Graphic Processing Units (GPUs)

14.8.1.1.3.  Central Processing Units (CPUs)

14.8.1.1.4.  Application Specific Integrated Circuits (ASICs)

14.8.1.2.  GCC Countries Market Revenue (US$ Mn) and Forecasts, By Architecture

14.8.1.2.1.  Von Neumann Architecture-Based Chips

14.8.1.2.2.  Neuromorphic Architecture-Based Chips

14.8.1.3.  GCC Countries Market Revenue (US$ Mn) and Forecasts, By Power Consumption

14.8.1.3.1.  High (>100 W)

14.8.1.3.2.  Medium (5-100 W)

14.8.1.3.3.  Low (< 5 W)

14.8.1.4.  GCC Countries Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

14.8.1.4.1.  High (>1TFlops)

14.8.1.4.2.  Low (<1TFlops)

14.8.1.5.  GCC Countries Market Revenue (US$ Mn) and Forecasts, By Application Domain

14.8.1.5.1.  Training

14.8.1.5.2.  Interference

14.8.1.6.  GCC Countries Market Revenue (US$ Mn) and Forecasts, By Vertical

14.8.1.6.1.  Consumer

14.8.1.6.2.  Industrial

14.8.1.6.3.  Automotive

14.8.1.6.4.  Military and Defense

14.8.1.6.5.  Medical

14.8.1.6.6.  Aerospace

14.8.1.6.7.  Others

14.8.2. Southern Africa

14.8.2.1.  Southern Africa Market Revenue (US$ Mn) and Forecasts, By Type

14.8.2.1.1.  Field Programmable Gate Arrays (FPGAs)

14.8.2.1.2.  Graphic Processing Units (GPUs)

14.8.2.1.3.  Central Processing Units (CPUs)

14.8.2.1.4.  Application Specific Integrated Circuits (ASICs)

14.8.2.2.  Southern Africa Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Architecture

14.8.2.2.1.  Von Neumann Architecture-Based Chips

14.8.2.2.2.  Neuromorphic Architecture-Based Chips

14.8.2.3.  Southern Africa Market Revenue (US$ Mn) and Forecasts, By Power Consumption

14.8.2.3.1.  High (>100 W)

14.8.2.3.2.  Medium (5-100 W)

14.8.2.3.3.  Low (< 5 W)

14.8.2.4.  Southern Africa Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

14.8.2.4.1.  High (>1TFlops)

14.8.2.4.2.  Low (<1TFlops)

14.8.2.5.  Southern Africa Market Revenue (US$ Mn) and Forecasts, By Application Domain

14.8.2.5.1.  Training

14.8.2.5.2.  Interference

14.8.2.6.  Southern Africa Market Revenue (US$ Mn) and Forecasts, By Vertical

14.8.2.6.1.  Consumer

14.8.2.6.2.  Industrial

14.8.2.6.3.  Automotive

14.8.2.6.4.  Military and Defense

14.8.2.6.5.  Medical

14.8.2.6.6.  Aerospace

14.8.2.6.7.  Others

14.8.3. Rest of MEA

14.8.3.1.  Rest of MEA Market Revenue (US$ Mn) and Forecasts, By Type

14.8.3.1.1.  Field Programmable Gate Arrays (FPGAs)

14.8.3.1.2.  Graphic Processing Units (GPUs)

14.8.3.1.3.  Central Processing Units (CPUs)

14.8.3.1.4.  Application Specific Integrated Circuits (ASICs)

14.8.3.2.  Rest of MEA Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Architecture

14.8.3.2.1.  Von Neumann Architecture-Based Chips

14.8.3.2.2.  Neuromorphic Architecture-Based Chips

14.8.3.3.  Rest of MEA Market Revenue (US$ Mn) and Forecasts, By Power Consumption

14.8.3.3.1.  High (>100 W)

14.8.3.3.2.  Medium (5-100 W)

14.8.3.3.3.  Low (< 5 W)

14.8.3.4.  Rest of MEA Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

14.8.3.4.1.  High (>1TFlops)

14.8.3.4.2.  Low (<1TFlops)

14.8.3.5.  Rest of MEA Market Revenue (US$ Mn) and Forecasts, By Application Domain

14.8.3.5.1.  Training

14.8.3.5.2.  Interference

14.8.3.6.  Rest of MEA Market Revenue (US$ Mn) and Forecasts, By Vertical

14.8.3.6.1.  Consumer

14.8.3.6.2.  Industrial

14.8.3.6.3.  Automotive

14.8.3.6.4.  Military and Defense

14.8.3.6.5.  Medical

14.8.3.6.6.  Aerospace

14.8.3.6.7.  Others

14.9. Key Segment for Channeling Investments

14.9.1. By Country

14.9.2. By Type

14.9.3. By Architecture

14.9.4. By Power Consumption

14.9.5. By Compute Capacity

14.9.6. By Application Domain

14.9.7. By Vertical

15. Latin America Deep Learning Chipset Market Analysis and Forecasts, 2018 – 2026

15.1. Overview

15.1.1. Latin America Deep Learning Chipset Market Revenue (US$ Mn)

15.2. Latin America Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

15.2.1. Field Programmable Gate Arrays (FPGAs)

15.2.2. Graphic Processing Units (GPUs)

15.2.3. Central Processing Units (CPUs)

15.2.4. Application Specific Integrated Circuits (ASICs)

15.3. Latin America Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Architecture

15.3.1. Von Neumann Architecture-Based Chips

15.3.2. Neuromorphic Architecture-Based Chips

15.4. Latin America Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Power Consumption

15.4.1. High (>100 W)

15.4.2. Medium (5-100 W)

15.4.3. Low (< 5 W)

15.5. Latin America Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

15.5.1. High (>1TFlops)

15.5.2. Low (<1TFlops)

15.6. Latin America Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Application Domain

15.6.1. Training

15.6.2. Interference

15.7. Latin America Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Vertical

15.7.1. Consumer

15.7.2. Industrial

15.7.3. Automotive

15.7.4. Military and Defense

15.7.5. Medical

15.7.6. Aerospace

15.7.7. Others

15.8. Latin America Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Country

15.8.1. Brazil

15.8.1.1.  Brazil Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

15.8.1.1.1.  Field Programmable Gate Arrays (FPGAs)

15.8.1.1.2.  Graphic Processing Units (GPUs)

15.8.1.1.3.  Central Processing Units (CPUs)

15.8.1.1.4.  Application Specific Integrated Circuits (ASICs)

15.8.1.2.  Brazil Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Architecture

15.8.1.2.1.  Von Neumann Architecture-Based Chips

15.8.1.2.2.  Neuromorphic Architecture-Based Chips

15.8.1.3.  Brazil Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Power Consumption

15.8.1.3.1.  High (>100 W)

15.8.1.3.2.  Medium (5-100 W)

15.8.1.3.3.  Low (< 5 W)

15.8.1.4.  Brazil Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

15.8.1.4.1.  High (>1TFlops)

15.8.1.4.2.  Low (<1TFlops)

15.8.1.5.  Brazil Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Application Domain

15.8.1.5.1.  Training

15.8.1.5.2.  Interference

15.8.1.6.  Brazil Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Vertical

15.8.1.6.1.  Consumer

15.8.1.6.2.  Industrial

15.8.1.6.3.  Automotive

15.8.1.6.4.  Military and Defense

15.8.1.6.5.  Medical

15.8.1.6.6.  Aerospace

15.8.1.6.7.  Others

15.8.2. Rest of Latin America

15.8.2.1.  Rest of Latin America Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Type

15.8.2.1.1.  Field Programmable Gate Arrays (FPGAs)

15.8.2.1.2.  Graphic Processing Units (GPUs)

15.8.2.1.3.  Central Processing Units (CPUs)

15.8.2.1.4.  Application Specific Integrated Circuits (ASICs)

15.8.2.2.  Rest of Latin America Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Architecture

15.8.2.2.1.  Von Neumann Architecture-Based Chips

15.8.2.2.2.  Neuromorphic Architecture-Based Chips

15.8.2.3.  Rest of Latin America Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Power Consumption

15.8.2.3.1.  High (>100 W)

15.8.2.3.2.  Medium (5-100 W)

15.8.2.3.3.  Low (< 5 W)

15.8.2.4.  Rest of Latin America Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Compute Capacity

15.8.2.4.1.  High (>1TFlops)

15.8.2.4.2.  Low (<1TFlops)

15.8.2.5.  Rest of Latin America Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Application Domain

15.8.2.5.1.  Training

15.8.2.5.2.  Interference

15.8.2.6.  Rest of Latin America Deep Learning Chipset Market Revenue (US$ Mn) and Forecasts, By Vertical

15.8.2.6.1.  Consumer

15.8.2.6.2.  Industrial

15.8.2.6.3.  Automotive

15.8.2.6.4.  Military and Defense

15.8.2.6.5.  Medical

15.8.2.6.6.  Aerospace

15.8.2.6.7.  Others

15.9. Key Segment for Channeling Investments

15.9.1. By Country

15.9.2. By Type

15.9.3. By Architecture

15.9.4. By Power Consumption

15.9.5. By Compute Capacity

15.9.6. By Application Domain

15.9.7. By Vertical

16. Competitive Benchmarking

16.1. Player Positioning Analysis

16.2. Global Presence and Growth Strategies

17. Player Profiles

17.1. Amazon Web Services, Inc.

17.1.1. Company Details

17.1.2. Company Overview

17.1.3. Product Offerings

17.1.4. Key Developments

17.1.5. Financial Analysis

17.1.6. SWOT Analysis

17.1.7. Business Strategies

17.2.  Arm Limited

17.2.1. Company Details

17.2.2. Company Overview

17.2.3. Product Offerings

17.2.4. Key Developments

17.2.5. Financial Analysis

17.2.6. SWOT Analysis

17.2.7. Business Strategies

17.3. CEVA, Inc.

17.3.1. Company Details

17.3.2. Company Overview

17.3.3. Product Offerings

17.3.4. Key Developments

17.3.5. Financial Analysis

17.3.6. SWOT Analysis

17.3.7. Business Strategies

17.4. Facebook

17.4.1. Company Details

17.4.2. Company Overview

17.4.3. Product Offerings

17.4.4. Key Developments

17.4.5. Financial Analysis

17.4.6. SWOT Analysis

17.4.7. Business Strategies

17.5. Google LLC

17.5.1. Company Details

17.5.2. Company Overview

17.5.3. Product Offerings

17.5.4. Key Developments

17.5.5. Financial Analysis

17.5.6. SWOT Analysis

17.5.7. Business Strategies

17.6. Graphcore

17.6.1. Company Details

17.6.2. Company Overview

17.6.3. Product Offerings

17.6.4. Key Developments

17.6.5. Financial Analysis

17.6.6. SWOT Analysis

17.6.7. Business Strategies

17.7. IBM Corporation

17.7.1. Company Details

17.7.2. Company Overview

17.7.3. Product Offerings

17.7.4. Key Developments

17.7.5. Financial Analysis

17.7.6. SWOT Analysis

17.7.7. Business Strategies

17.8. Intel Corporation

17.8.1. Company Details

17.8.2. Company Overview

17.8.3. Product Offerings

17.8.4. Key Developments

17.8.5. Financial Analysis

17.8.6. SWOT Analysis

17.8.7. Business Strategies

17.9. NVIDIA Corporation

17.9.1. Company Details

17.9.2. Company Overview

17.9.3. Product Offerings

17.9.4. Key Developments

17.9.5. Financial Analysis

17.9.6. SWOT Analysis

17.9.7. Business Strategies

17.10. Qualcomm Technologies, Inc.

17.10.1.   Company Details

17.10.2.   Company Overview

17.10.3.   Product Offerings

17.10.4.   Key Developments

17.10.5.   Financial Analysis

17.10.6.   SWOT Analysis

17.10.7.   Business Strategies

17.11. TeraDeep Inc.

17.11.1.   Company Details

17.11.2.   Company Overview

17.11.3.   Product Offerings

17.11.4.   Key Developments

17.11.5.   Financial Analysis

17.11.6.   SWOT Analysis

17.11.7.   Business Strategies

17.12. XILINX INC.

17.12.1.   Company Details

17.12.2.   Company Overview

17.12.3.   Product Offerings

17.12.4.   Key Developments

17.12.5.   Financial Analysis

17.12.6.   SWOT Analysis

17.12.7.   Business Strategies

 

Note: This ToC is tentative and can be changed according to the research study conducted during the course of report completion.

At Absolute Markets Insights, we use both top-down and bottom-up approach for calculating the market estimates and market forecast data. We allocate year-on-year growth rate from 2018 to 2026 and reach to the calculations for the global CAGR. Basically for estimation of the products and applications, usually we follow bottom-up approach, where we track the trends in different regions and their countries. We track down the growth factors, restraints, rules & regulations and opportunities for each country  and its region and finally calculate the global numbers. We first track the growth for the U.S. and Rest of North America. With these factors we can estimate the growth and trend for North America, similar approach would be taken for Europe, Asia Pacific, Latin America and Middle East & Africa. Finally, through our home grown model we reach to estimation and forecasting of the global numbers.   

Our research study is mainly implement through a mix of both secondary and primary research. Various sources such as industry magazines, trade journals, and government websites and trade associations are reviewed for gathering precise data. Primary interviews  are conducted to validate the market size derived from secondary research. Industry experts, major manufacturers and distributors are contacted for further validation purpose on the current market penetration and growth trends. 

Prominent participants in our primary research process include:

  • Key Opinion Leaders namely the CEOs, CSOs, VPs, purchasing managers, amongst others
  • Research and development participants, distributors/suppliers and subject matter experts

Secondary Research includes data extracted from paid data sources:

  • Reuters
  • Factiva
  • Bloomberg
  • One Source
  • Hoovers

 

Research Methodology

Methodology

Key Inclusions

Methodology

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