SPRACZ2 August   2022 TDA4VM , TDA4VM-Q1

ADVANCE INFORMATION  

  1.   Abstract
  2. 1Introduction
    1. 1.1 Vision Analytics
    2. 1.2 End Equipments
    3. 1.3 Deep learning: State-of-the-art
  3. 2Embedded edge AI system: Design considerations
    1. 2.1 Processors for edge AI: Technology landscape
    2. 2.2 Edge AI with TI: Energy-efficient and Practical AI
      1. 2.2.1 TDA4VM processor architecture
        1. 2.2.1.1 Development platform
    3. 2.3 Software programming
  4. 3Industry standard performance and power benchmarking
    1. 3.1 MLPerf models
    2. 3.2 Performance and efficiency benchmarking
    3. 3.3 Comparison against other SoC Architectures
      1. 3.3.1 Benchmarking against GPU-based architectures
      2. 3.3.2 Benchmarking against FPGA based SoCs
      3. 3.3.3 Summary of competitive benchmarking
  5. 4Conclusion
  6.   Revision History
  7. 5References

1 Introduction

The world population today is 7.8 billion and is on the constant rise with an estimate of 10 billion by 2050 [1]. The growing population needs necessities such as food, clothing and ever-increasing comforts and tools - safely and securely. There is constant technology innovation across all markets - consumer, industrial and automotive to meet these needs. New technologies that we all got used to have made the data generation more affordable and more fun. Think about the number of pictures taken with smart phones and the amount of data being generated from various sensors and edge devices in buildings and factories. All this data is propelling end-to-end automation in factories and buildings to drive productivity to produce more goods and services. This exponentially increases the data that has to be managed - processed, analyzed to take corrective actions. For example, a smart factory could have more than 50,000 sensors and generate several petabytes a day. Even a standard office building will generate hundreds of gigabytes of data. Most of this data will be stored, managed, analyzed and kept right where it was produced, at the edge driven by security, real-time performance and reliability