Framework for creating performance model of AI algorithms for early architecture exploration

EasyChair Preprint 1377

Abstract

We are now living in an age of AI enabled smart homes, autonomous vehicles, and chatbots. Researchers are coming up with complex AI algorithms that are useful in various areas like speech and image recognition, even surpassing human accuracy. Increased complexity, growing competition and splurge in demand of AI enabled devices constantly put pressure on vendors to improve the chip performance and deliver the product as early as possible. System designers tend to use simulation techniques to quickly analyze and improve their model before implementing it in silicon. But till now these simulation techniques have not been leveraged for the AI domain. This paper proposes a novel framework to leverage Virtual Prototyping for early design exploration of power and performance targeting AI centric designs.

Keyphrases: AI, Artificial Intelligence, CNNs, Simulation techniques, Synopsys Platform Architect, Virtual Prototyping, abstract model, machine learning, neural networks, performance model, smart devices

@booklet{EasyChair:1377,
  author    = {Amit Dudeja and Amit Tara and Amit Garg and Tushar Jain},
  title     = {Framework for creating performance model of AI algorithms for early architecture exploration},
  howpublished = {EasyChair Preprint 1377},
  year      = {EasyChair, 2019}}