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Market Research Report

Deep Learning Chipsets - CPUs, GPUs, FPGAs, ASICs, SoC Accelerators, and Other Chipsets for Training and Inference Applications: Global Market Analysis and Forecasts

Published by Tractica Product code 408667
Published Content info 89 Pages; 143 Tables, Charts & Figures
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Deep Learning Chipsets - CPUs, GPUs, FPGAs, ASICs, SoC Accelerators, and Other Chipsets for Training and Inference Applications: Global Market Analysis and Forecasts
Published: May 29, 2018 Content info: 89 Pages; 143 Tables, Charts & Figures
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.

The deep learning chipset market has experienced a dynamic period of evolution during the past year and promises to become even more interesting. Beginning in 2018, many companies will start releasing their new chipsets, after which the market validation will then begin. Tractica expects that 2019 and 2020 will be the years when a ramp-up in deep learning chipset volumes will take place and winners will begin to emerge. Tractica forecasts that the market for deep learning chipsets will increase from $1.6 billion in 2017 to $66.3 billion by 2025. 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.

This Tractica report assesses the industry dynamics, technology issues, and market opportunity surrounding deep learning chipsets including CPUs, GPUs, FPGAs, ASICs, SoC Accelerators, and other chipsets. The report provides market sizing and forecasts for the period from 2016 through 2025, with segmentation by chipset type, compute capacity, power consumption, world region, and inference versus training. The study also includes 19 profiles of key industry players.

Key Questions Addressed:

  • What is the mix of chipset types being used for deep learning today, and how will it change during the next 10 years?
  • Which chipset types are most appropriate for training versus inference applications?
  • What will be the power consumption and compute capacity profiles of chipsets used for various deep learning applications?
  • What is the market opportunity for deep learning chipsets in cloud/data center environments versus edge devices?
  • Which market sectors and industries will drive demand for deep learning chipsets?
  • What is the state of technology development for deep learning chipsets, and who are the key industry players driving innovation?

Who Needs This Report?

  • Semiconductor and component manufacturers
  • Service providers and systems integrators
  • End-user organizations deploying deep learning systems
  • Industry associations
  • Government agencies
  • Investor community
Table of Contents
Product Code: DLC-18

Table of Contents

1. Executive Summary

  • 1.1. Introduction
  • 1.2. Market Overview
  • 1.3. Background
  • 1.4. New Design Starts and Startup Activity
  • 1.5. Market Segmentation
    • 1.5.1. Segmentation by Architecture
    • 1.5.2. Segmentation Based on Training versus Inference
    • 1.5.3. Segmentation Based on Compute Capacity
    • 1.5.4. Segmentation Based on Power Consumption
    • 1.5.5. Segmentation Based on the Market: Enterprise/Data Center
    • 1.5.6. Segmentation Based on the Application: Edge Market
    • 1.5.7. Neuromorphic Chipsets
  • 1.6. Technology Parameters
    • 1.6.1. Performance
    • 1.6.2. Power
    • 1.6.3. Performance per Watt
    • 1.6.4. Programmability
    • 1.6.5. Intellectual Property and Ecosystem
    • 1.6.6. Development Tools
  • 1.7. Market Forecasts

2. Market Issues

  • 2.1. Market Drivers
    • 2.1.1. Availability of Large Datasets
    • 2.1.2. Quality of Results and Growth in Enterprises
    • 2.1.3. Computer Vision Applications
    • 2.1.4. Embedded Devices
    • 2.1.5. Accelerated Computing
  • 2.2. Market Barriers and Challenges
    • 2.2.1. Development Costs
    • 2.2.2. Availability of Expertise
    • 2.2.3. Time to Market
  • 2.3. Key Markets and Applications
    • 2.3.1. Data Center and Enterprise
    • 2.3.2. Consumer
    • 2.3.3. Industrial: Robotics, Drones, and Quality Assurance
    • 2.3.4. Automotive and Transportation
    • 2.3.5. Smart Camera and Surveillance
    • 2.3.6. Mobile Devices and Smartphones
    • 2.3.7. Government and Defense
    • 2.3.8. Other
  • 2.4. Regional Differences

3. Technology Issues

  • 3.1. AI and Deep Learning
  • 3.2. Deep Learning: Key Concepts and Implications for Chipsets
    • 3.2.1. Feedforward Networks versus Recurrent Networks
    • 3.2.2. Convolutional Neural Network
    • 3.2.3. Long Short-Term Memory
    • 3.2.4. Neural Network Zoo
  • 3.3. AI Described in Terms of Mathematical Problems
    • 3.3.1. Classification
    • 3.3.2. Regression
    • 3.3.3. Transcription
    • 3.3.4. Machine Translation
    • 3.3.5. Anomaly Detection
  • 3.4. Training versus Inference
  • 3.5. Supervised versus Unsupervised Training
  • 3.6. Chipsets for Deep Learning
    • 3.6.1. Central Processing Units
    • 3.6.2. Graphics Processing Units
    • 3.6.3. Field Programmable Gate Arrays
    • 3.6.4. Application Specific Integrated Circuits
  • 3.7. System-on-a-Chip Accelerators
  • 3.8. Low Precision, Integer, Fixed Point, and Floating Point Mathematics
  • 3.9. Deep Learning Development Frameworks
  • 3.10. Framework Interoperability
  • 3.11. OpenCL and Compute Unified Device Architecture
  • 3.12. Neuromorphic Processing
  • 3.13. Universities and Research Institutions

4. Key Industry Players

  • 4.1. Google
  • 4.2. Intel
  • 4.3. Xilinx
  • 4.4. AMD
  • 4.5. NVIDIA
  • 4.6. ARM
  • 4.7. Qualcomm
  • 4.8. IBM
  • 4.9. Graphcore
  • 4.10. Groq
  • 4.11. BrainChip
  • 4.12. Mobileye
  • 4.13. Wave Computing
  • 4.14. CEVA
  • 4.15. Movidius
  • 4.16. Nervana Systems
  • 4.17. Amazon
  • 4.18. Cerebras Systems
  • 4.19. Facebook

5. Market Forecasts

  • 5.1. Forecast Methodology and Assumptions
  • 5.2. Overall Market
  • 5.3. Unit Shipments by Chipset Type
  • 5.4. Revenue by Chipset Type
  • 5.5. Revenue by Training versus Inference
  • 5.6. Revenue by Compute Capacity
  • 5.7. Revenue by Power Consumption
  • 5.8. Average Selling Price by Chipset Type
  • 5.9. Revenue by Market Sector
  • 5.10. Central Processing Units
  • 5.11. Graphics Processing Units
  • 5.12. Application-Specific Integrated Circuits
  • 5.13. Field Programmable Gate Arrays
  • 5.14. System-on-a-Chip Accelerators
  • 5.15. Other Chipsets
  • 5.16. Conclusion

6. Company Directory

7. Acronym and Abbreviation List

8. Table of Contents

9. Table of Charts and Figures

10. Scope of Study, Sources and Methodology, Notes

Charts

  • Deep Learning Chipset Revenue by Region, World Markets: 2016-2025
  • Deep Learning Chipset Year-on-Year Revenue Growth Rates, World Markets: 2016-2025
  • Deep Learning Chipset Unit Shipments by Type, World Markets: 2016-2025
  • Deep Learning Chipset Revenue by Type, World Markets: 2016-2025
  • Deep Learning Chipset Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning Chipset Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning Chipset Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning Chipset Revenue by Market Sector, World Markets: 2016-2025
  • Deep Learning Central Processing Unit Shipments and Revenue, World Markets: 2016-2025
  • Deep Learning Graphics Processing Shipments and Revenue, World Markets: 2016-2025
  • Deep Learning Application-Specific Integrated Circuit Unit Shipments and Revenue, World Markets: 2016-2025
  • Deep Learning Field Programmable Gate Array Unit Shipments and Revenue, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Chipset Unit Shipments and Revenue, World Markets: 2016-2025
  • Deep Learning Other Chipset Unit Shipments and Revenue, World Markets: 2016-2025
  • Deep Learning Central Processing Unit Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning Central Processing Unit Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning Central Processing Unit Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning Central Processing Unit Revenue by Market Sector, World Markets: 2016-2025
  • Deep Learning Graphics Processing Unit Revenue by Region, World Markets: 2016-2025
  • Deep Learning Graphics Processing Unit Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning Graphics Processing Unit Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning Graphics Processing Unit Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning Graphics Processing Unit Revenue by Market Sector, World Markets: 2016-2025
  • Deep Learning Field Programmable Gate Array Revenue by Region, World Markets: 2016-2025
  • Deep Learning Field Programmable Gate Array Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning Field Programmable Gate Array Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning Field Programmable Gate Array Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning Field Programmable Gate Array Revenue by Market Sector, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Revenue by Region, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Revenue by Market Sector, World Markets: 2016-2025
  • Deep Learning Chipset Enterprise Sector Revenue by Region, World Markets: 2016-2025
  • Deep Learning Other Chipset Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning Other Chipset Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning Other Chipset Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning Other Chipset Revenue by Market Sector, World Markets: 2016-2025
  • Deep Learning Chipset Enterprise Sector Revenue by Type, World Markets: 2016-2025
  • Deep Learning Chipset Enterprise Sector Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning Chipset Enterprise Sector Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning Chipset Enterprise Sector Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning Chipset Edge Sector Revenue by Region, World Markets: 2016-2025
  • Deep Learning Chipset Edge Sector Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning Chipset Edge Sector Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning Chipset Edge Sector Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning Chipset Edge Sector Revenue by Device Category, World Markets: 2016-2025

Figures

  • Performance Requirement for Popular Neural Networks
  • Evolution of Artificial Intelligence
  • Number of Companies Working with NVIDIA on Deep Learning
  • System Considerations When Choosing a Hardware Platform
  • Suitability of Different Chipsets for Training and Inference
  • CNN Algorithms Shown to Increase Accuracy of Vehicle Detection
  • Diagram Depicting Various Technologies in AI
  • Feedforward Network versus Recurrent Neural Network
  • A Convolutional Neural Network Used for Image Recognition
  • Neural Network Zoo
  • Training versus Inference Illustrated
  • Intel's Strategy for Incorporating AI
  • Xeon CPU Training Time versus NVIDIA V100 GPU Training Time
  • Google's Tensor Processing Unit
  • Popularity of Open-Source Deep Network Repositories in GitHub
  • Neural Network Exchange Format Explained
  • Graphcore's Poplar Software Framework

Tables

  • Deep Learning Chipset Revenue by Region, World Markets: 2016-2025
  • Deep Learning Chipset Year-on-Year Revenue Growth Rates, World Markets: 2016-2025
  • Deep Learning Chipset Revenue by Type, World Markets: 2016-2025
  • Deep Learning Chipset Unit Shipments by Type, World Markets: 2016-2025
  • Deep Learning Chipset Revenue by Market Sector, World Markets: 2016-2025
  • Deep Learning Chipset Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning Chipset Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning Chipset Revenue, Inference versus Training, World Markets: 2016-2025
  • Total Deep Learning Central Processing Unit Revenue, World Markets: 2016-2025
  • Deep Learning Central Processing Unit Revenue by Type, World Markets: 2016-2025
  • Deep Learning Enterprise Central Processing Unit Average Selling Price, World Markets: 2016-2025
  • Deep Learning Enterprise Central Processing Unit Shipments, World Markets: 2016-2025
  • Deep Learning Central Processing Unit Revenue by Region, World Markets: 2016-2025
  • Deep Learning Central Processing Unit Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning Central Processing Unit Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning Central Processing Unit Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning Central Processing Unit Revenue by Market Sector, World Markets: 2016-2025
  • Total Deep Learning Graphics Processing Unit Revenue, World Markets: 2016-2025
  • Deep Learning Graphics Processing Unit Revenue by Type, World Markets: 2016-2025
  • Deep Learning Graphics Processing Unit Average Selling Price, World Markets: 2016-2025
  • Deep Learning Graphics Processing Unit Shipments, World Markets: 2016-2025
  • Deep Learning Graphics Processing Unit Revenue by Region, World Markets: 2016-2025
  • Deep Learning Graphics Processing Unit Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning Graphics Processing Unit Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning Graphics Processing Unit Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning Graphics Processing Unit Revenue by Market Sector, World Markets: 2016-2025
  • Deep Learning Field Programmable Gate Array Revenue, World Markets: 2016-2025
  • Deep Learning Field Programmable Gate Array Revenue by Type, World Markets: 2016-2025
  • Deep Learning Field Programmable Gate Array Average Selling Price, World Markets: 2016-2025
  • Deep Learning Field Programmable Gate Array Unit Shipments, World Markets: 2016-2025
  • Deep Learning Field Programmable Gate Array Revenue by Region, World Markets: 2016-2025
  • Deep Learning Field Programmable Gate Array Revenue by Region, World Markets: 2016-2025
  • Deep Learning Field Programmable Gate Array Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning Field Programmable Gate Array Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning Field Programmable Gate Array Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning Application-Specific Integrated Circuit Revenue, World Markets: 2016-2025
  • Deep Learning Application-Specific Integrated Circuit Revenue by Type, World Markets: 2016-2025
  • Deep Learning Application-Specific Integrated Circuit Average Selling Price, World Markets: 2016-2025
  • Deep Learning Application-Specific Integrated Circuit Unit Shipments, World Markets: 2016-2025
  • Deep Learning Application-Specific Integrated Circuit Revenue by Region, World Markets: 2016-2025
  • Deep Learning Application-Specific Integrated Circuit Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning Application-Specific Integrated Circuit Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning Application-Specific Integrated Circuit Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning Application-Specific Integrated Circuit Revenue by Market Sector, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Revenue, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Revenue by Type, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Average Selling Price, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Unit Shipments, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Revenue by Region, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Revenue by Market Sector, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Revenue, World Markets: 2016-2025
  • Deep Learning System-on-a-Chip Accelerator Revenue by Type, World Markets: 2016-2025
  • Deep Learning Other Chipset Average Selling Price, World Markets: 2016-2025
  • Deep Learning Other Chipset Unit Shipments, World Markets: 2016-2025
  • Deep Learning Other Chipset Revenue by Region, World Markets: 2016-2025
  • Deep Learning Other Chipset Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning Other Chipset Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning Other Chipset Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning Other Chipset Revenue by Market Sector, World Markets: 2016-2025
  • Deep Learning Chipset Enterprise Sector Revenue by Region, World Markets: 2016-2025
  • Deep Learning Chipset Enterprise Sector Year-on-Year Revenue Growth Rates, World Markets: 2016-2025
  • Deep Learning Chipset Enterprise Sector Revenue by Type, World Markets: 2016-2025
  • Deep Learning Chipset Enterprise Sector Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning Chipset Enterprise Sector Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning Chipset Enterprise Sector Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning Chipset Edge Sector Revenue by Region, World Markets: 2016-2025
  • Deep Learning Chipset Edge Sector Revenue by Region, World Markets: 2016-2025
  • Deep Learning Chipset Edge Sector Year-on-Year Revenue Growth Rates, World Markets: 2016-2025
  • Deep Learning Chipset Edge Sector Revenue by Type, World Markets: 2016-2025
  • Deep Learning Chipset Edge Sector Revenue by Power Consumption, World Markets: 2016-2025
  • Deep Learning Chipset Edge Sector Revenue by Compute Capacity, World Markets: 2016-2025
  • Deep Learning Chipset Edge Sector Revenue, Inference versus Training, World Markets: 2016-2025
  • Deep Learning Chipset Edge Sector Revenue by Device Category, World Markets: 2016-2025
  • Key Players in Different Deep Learning Chipsets
  • Comparison of Deep Learning Chipset Parameters
  • Overview of Deep Learning Frameworks
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