Using ML In EDA

Machine learning is becoming essential for designing chips due to the growing volume of data stemming from increasing density and complexity. Nick Ni, director of product marketing for AI at Xilinx, examines why machine learning is gaining traction at advanced nodes, where it’s being used today and how it will be used in the future, how quality of results compare with and without ML, and what... » read more

Roadblocks For ML in EDA

Is EDA a suitable space for utilizing machine learning (ML)? The answer depends on a number of factors, including where exactly it is being applied, how much support there is from the industry, and whether there are demonstrable advantages. Exactly where ML will play a role has yet to be decided. Replacing existing heuristics with machine learning, for example, would require an industry-wide... » read more

SLX Multi-Objective Optimization (MOPT)

Technologies such as autonomous cars and 5G communication are seeing a rapid increase in the number of processing elements (PE) per platform. Where software professionals were used to programming one, two or a handful of cores, the game has now changed. Intel’s Many Integrated Core Architecture [3] contains up to 78 cores, Nvidia Tegra XI[2] has up to 260 cores and Adapteva’s Epiphany-V[1] ... » read more

Tech Talk: Applying Machine Learning

Norman Chang, chief technologist at ANSYS, talks about real applications of machine learning for mechanical, fluid dynamics and chip-package-system design. » read more