Description:-
Artificial intelligence (AI) technology is progressing at a rapid pace, as is the application of the technology to solve real-world problems. While the market for chipsets to address deep learning training and inference workloads is still a new one, the landscape is changing quickly – in the past year, more than 60 companies of all sizes have announced some sort of deep learning chipset or intellectual property (IP) design. Every prominent name in the technology industry has acknowledged the need for hardware acceleration of AI algorithms and the semiconductor industry has responded by offering a wide range of solutions.
Scope of the Report:
The edge computing market, where AI computation is done on the device, is expected to represent more than three-quarters of the total market opportunity, with the balance being in cloud/data center environments. Mobile phones will be a major driver of the edge market, and other prominent edge categories include automotive, smart cameras, robots, and drones.
The global Deep Learning Chipsets market is valued at xx million USD in 2017 and is expected to reach xx million USD by the end of 2023, growing at a CAGR of xx% between 2017 and 2023.
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The Asia-Pacific will occupy for more market share in following years, especially in China, also fast growing India and Southeast Asia regions.
North America, especially The United States, will still play an important role which cannot be ignored. Any changes from United States might affect the development trend of Deep Learning Chipsets.
Europe also play important roles in global market, with market size of xx million USD in 2017 and will be xx million USD in 2023, with a CAGR of xx%.
This report studies the Deep Learning Chipsets market status and outlook of Global and major regions, from angles of players, countries, product types and end industries; this report analyzes the top players in global market, and splits the Deep Learning Chipsets market by product type and applications/end industries.
Market Segment by Companies, this report covers
Intel
Xilinx
AMD
NVIDIA
ARM
Qualcomm
IBM
Graphcore
BrainChip
Mobileye
Wave Computing
CEVA
Movidius
Nervana Systems
Amazon
Cerebras Systems
Market Segment by Regions, regional analysis covers
North America (United States, Canada and Mexico)
Europe (Germany, France, UK, Russia and Italy)
Asia-Pacific (China, Japan, Korea, India and Southeast Asia)
South America (Brazil, Argentina, Colombia)
Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)
Market Segment by Type, covers
CPUs
GPUs
FPGAs
ASICs
SoC Accelerators
Others
Market Segment by Applications, can be divided into
Automotive
Smart Cameras
Robots
Drones
Mobile Phones
Others
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Table Of Contents – Major Key Points
1 Deep Learning Chipsets Market Overview
1.1 Product Overview and Scope of Deep Learning Chipsets
1.2 Classification of Deep Learning Chipsets by Types
1.2.1 Global Deep Learning Chipsets Revenue Comparison by Types (2017-2023)
1.2.2 Global Deep Learning Chipsets Revenue Market Share by Types in 2017
1.2.3 CPUs
1.2.4 GPUs
1.2.5 FPGAs
1.2.6 ASICs
1.2.7 SoC Accelerators
1.2.8 Others
1.3 Global Deep Learning Chipsets Market by Application
1.3.1 Global Deep Learning Chipsets Market Size and Market Share Comparison by Applications (2013-2023)
1.3.2 Automotive
1.3.3 Smart Cameras
1.3.4 Robots
1.3.5 Drones
1.3.6 Mobile Phones
1.3.7 Others
1.4 Global Deep Learning Chipsets Market by Regions
1.4.1 Global Deep Learning Chipsets Market Size (Million USD) Comparison by Regions (2013-2023)
1.4.1 North America (USA, Canada and Mexico) Deep Learning Chipsets Status and Prospect (2013-2023)
1.4.2 Europe (Germany, France, UK, Russia and Italy) Deep Learning Chipsets Status and Prospect (2013-2023)
1.4.3 Asia-Pacific (China, Japan, Korea, India and Southeast Asia) Deep Learning Chipsets Status and Prospect (2013-2023)
1.4.4 South America (Brazil, Argentina, Colombia) Deep Learning Chipsets Status and Prospect (2013-2023)
1.4.5 Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa) Deep Learning Chipsets Status and Prospect (2013-2023)
1.5 Global Market Size of Deep Learning Chipsets (2013-2023)
2 Manufacturers Profiles
2.1 Google
2.1.1 Business Overview
2.1.2 Deep Learning Chipsets Type and Applications
2.1.2.1 Product A
2.1.2.2 Product B
2.1.3 Google Deep Learning Chipsets Revenue, Gross Margin and Market Share (2016-2017)
2.2 Intel
2.2.1 Business Overview
2.2.2 Deep Learning Chipsets Type and Applications
2.2.2.1 Product A
2.2.2.2 Product B
2.2.3 Intel Deep Learning Chipsets Revenue, Gross Margin and Market Share (2016-2017)
2.3 Xilinx
2.3.1 Business Overview
2.3.2 Deep Learning Chipsets Type and Applications
2.3.2.1 Product A
2.3.2.2 Product B
2.3.3 Xilinx Deep Learning Chipsets Revenue, Gross Margin and Market Share (2016-2017)
2.4 AMD
2.4.1 Business Overview
2.4.2 Deep Learning Chipsets Type and Applications
2.4.2.1 Product A
2.4.2.2 Product B
2.4.3 AMD Deep Learning Chipsets Revenue, Gross Margin and Market Share (2016-2017)
2.5 NVIDIA
2.5.1 Business Overview
2.5.2 Deep Learning Chipsets Type and Applications
2.5.2.1 Product A
2.5.2.2 Product B
2.5.3 NVIDIA Deep Learning Chipsets Revenue, Gross Margin and Market Share (2016-2017)
2.6 ARM
2.6.1 Business Overview
2.6.2 Deep Learning Chipsets Type and Applications
2.6.2.1 Product A
2.6.2.2 Product B
2.6.3 ARM Deep Learning Chipsets Revenue, Gross Margin and Market Share (2016-2017)
2.7 Qualcomm
2.7.1 Business Overview
2.7.2 Deep Learning Chipsets Type and Applications
2.7.2.1 Product A
2.7.2.2 Product B
2.7.3 Qualcomm Deep Learning Chipsets Revenue, Gross Margin and Market Share (2016-2017)
Continued……
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