Education Class B2

Title: Neural Networks and Accelerator Co-Design

Instructor: Dr. Nicolas J Fraser, Xilinx

Abstract: Machine learning algorithms have been gradually displacing traditional programming techniques across multiple domains, including domains that require low-latency and high-throughput, such as telecommunications and networking. Neural networks designed for these applications may require specialised accelerators in order meet the constraints of their deployment environment. During this talk, we will discuss various forms of specialisations that have been leveraged by the industry with their impact on potential applications, flexibility, performance and efficiency. Furthermore, we will discuss how the specialization in hardware architectures can be automated through end-to-end tool flows.

Bio: Nicholas J. Fraser received the PhD degree at The University of Sydney, Australia in 2020. Currently he’s a research scientist at Xilinx Research Labs, Dublin, Ireland. His main research interests include: training of reduced precision neural networks, software / hardware co-design of neural network topologies / accelerators, and audio signal processing.