Cloud native EDA tools & pre-optimized hardware platforms
Macrotrends in innovation are leveraging both software and chips to create the next round of world-changing products. Unlocking the vast potential offered by this innovation model is daunting however. Systemic complexity across all disciplines from silicon to software must be addressed in a holistic way to achieve success. AI applications change over months while chip design can take years, adding to the challenges. Talent shortages also create headwinds. And as more system companies engage in chip design, these headwinds can have a profound impact on the pace of innovation.
Complex chip and system design must be easier to achieve in less time. Sassine Ghazi will discuss several developing strategies that use AI and machine learning techniques to dramatically reduce design time and design risk, opening the opportunity for substantial increases in the pace of innovation.
Approximately one year ago, Samsung confirmed the world’s first use of AI to design a mobile processor chip. Since then, AI-driven design has been adopted across the industry at a phenomenal pace, accelerating silicon innovations to market in automotive, high-performance computing, consumer electronics, and other applications. Will this pace of innovation ultimately lead to self-designed silicon? In this sequel to the Day-1 Keynote – Enter the Era of Autonomous Design: Personalizing Chips for 1,000X More Powerful AI Compute, we will be looking at real-world examples of using AI to design chips, and reporting on the industry’s path to autonomous design.