AI chip design used to optimize Samsung’s latest mobile products

AI chip design used to optimize Samsung’s latest mobile products

Market news |
By Rich Pell

Synopsys’ AI-based system ( autonomously achieved the highest frequency and lowest power consumption for Samsung’s advanced mobile designs, says the company.

“For decades, autonomous chip design existed only in science fiction,” says Aart de Geus, chairman and co-CEO, Synopsys. “This pivotal moment in semiconductor history will breathe new life into Moore’s law. We congratulate Samsung on this remarkable achievement, and we look forward to catalyzing its next 1000x.”

The AI-designed product will be manufactured on Samsung’s advanced manufacturing process. To achieve the high-performance and low-power market requirements in a timely manner, Samsung used (Design Space Optimization AI) driving the Synopsys Fusion Compiler RTL-to-GDSII solution. uses reinforcement learning, an AI technology similar to that used in self-driving vehicles, to achieve better performance, power and area (PPA). Applied at every stage of design implementation, pushed operating frequency over 100 MHz beyond target and considerably reduced overall power consumption – all while saving Samsung weeks of manual design effort.

An early development partner of Synopsys’ autonomous design technology, Samsung began deploying to multiple projects in the fall of 2020.

Thomas Cho, EVP of Infrastructure & Design Technology Center, System LSI Business, Samsung Electronics says, “This is a remarkable milestone for our program to successfully introduce AI into the chip design process in collaboration with Synopsys. Not only have we demonstrated that AI can help us achieve PPA targets for even the most demanding process technologies, but through our partnership we have established an ultra-high-productivity design system that is consistently delivering impressive results.” introduces a novel approach to searching vast problem spaces of chip design for optimal solutions, enabled by the latest advancements in AI and machine learning. Traditional design space exploration has been a very labor-intensive effort, typically requiring months of experimentation, guided by past experiences and institutional knowledge. In today’s hypercompetitive markets, say the companies, a better design solution means faster software performance, extended hours of battery life and a more personalized user experience.

Using AI technology, can autonomously search design spaces for better solutions, massively scaling the exploration of choices in chip design workflows, while automating a high volume of less consequential decisions., says the company, unleashes architectural innovation with AI-grade productivity, opening a new growth trajectory for the semiconductor industry and paving a path to 1000x more powerful silicon applications.

Karl Freund, principal analyst at Cambrian AI Research adds, “This breakthrough marks the beginning of a journey where AI applications and reinforcement learning will help architects with physical design and even logic design.”


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