Luba Tang

Luba Tang is the founder and CEO of Skymizer Taiwan Inc., which is in the business of providing system software to IC design teams. Skymizer’s system software solutions enable AI-on-Chip design houses to automate AI application development, improve system performance, and optimize inference accuracy. Luba Tang’s research interests include electronic system level (ESL) design, system software, and neural networks. He had focused on iterative compilers, ahead-of-time compilers, link-time optimization, neural network compilation, and neural network optimization. His most recent work focuses on exploiting various types of parallelism from different accelerators in a hyper-scale system-on-chip.

From Hyperscale Models to Heterogeneous SoCs: Industrializing Neural Network Deployment with ONNC

Large language models (LLMs) have become an increasingly prominent feature in various computing platforms, such as data centers, smartphones, and microcontrollers. As such, their potential applications in both human-to-machine interfaces (HMIs) and machine-to-machine interfaces (M2MI) have been extensively studied and discussed. However, implementing hyper-scale LLMs on heterogeneous multicore System-on-Chips (SoCs) poses significant challenges. In this talk, we will discuss the key challenges, including issues related to hardware/software interfaces, verification, and SoC architecture exploration. At the end of this talk, we will propose a practical workflow and corresponding solutions we’ve applied in many cases. And see how our standard tool – ONNC – is used in the workflow.