VLSI Physical Design for Industrial Server Processors and AI Acceleratorszie

The complexity of modern logic and physical synthesis tools leads to a vast design space that is difficult even for experienced human designers to navigate. Fortunately, machine learning approaches and cloud computing environments are well suited for tackling complex parameter tuning problems like those seen in VLSI design flows. This talk discusses design flow tuning approaches utilized for optimizing IBM server chips over the last several processor generations. A holistic approach is proposed that blends online and offline machine learning techniques for industrial design flow tuning. This talk also focuses on recent work at IBM for AI acceleration using custom hardware. The broader effort spanning the hardware/software stack is reviewed. Specific focus is given to AI chip design, ASIC design flow tuning, and potential new directions for design flow tuning research.