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Summary form only given. The complete presentation was not made available for publication as part of the conference proceedings. Hardware acceleration for Artificial Intelligence (AI) is now a very competitive and rapidly evolving market. In this tutorial, we will start by covering the basics of deep learning. We will proceed to give an overview of the new and exciting field of using AI chips to accelerate deep learning computations. It will cover the critical and special characteristics and the architecture of the most popular AI chips. Next we will summarize the features of the AI chips from design-for-test (DFT) perspective and introduce the DFT technologies that can help testing AI chips and speeding up time-to-market. Finally, we will present a few case studies on how DFT is implemented on the real AI chips.
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Huang et al. (2019) studied this question.