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
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)
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
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 are engaged in building both global as well as country specific reports. As a result, the approach taken for deriving the estimation and forecast for a specific country is a bit unique and different in comparison to the global research studies. In this case, we not only study the concerned market factors & trends prevailing in a particular country (from secondary research) but we also tend to calculate the actual market size & forecast from the revenue generated from the market participants involved in manufacturing or distributing the any concerned product. These companies can also be service providers. For analyzing any country specifically, we do consider the growth factors prevailing under the states/cities/county for the same. For instance, if we are analyzing an industry specific to United States, we primarily need to study about the states present under the same(where the product/service has the highest growth). Similar analysis will be followed by other countries. Our scope of the report changes with different markets.
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
Key Inclusions
