Moortec;s sensors provide a key component to Synopsys’ new Silicon Lifecycle Management (SLM) platform. Data from these environmental sensors is critical in being able to properly understand chip performance activity and will enable the SLM platform’s analytics engines to drive more detailed and precise optimisations at each stage of the semiconductor lifecycle, starting with design implementation, and progressing through manufacturing, production test, bring-up and culminating with in-field operation.
The terms of the deal, which are not material to Synopsys’ financials, are not being disclosed.
“We continue to deliver on our roadmap of innovation to provide silicon lifecycle optimization solutions that address the evolving needs of the dynamic semiconductor industry,” said Sassine Ghazi, chief operating officer of Synopsys. “This acquisition accelerates the expansion of our SLM platform by providing our customers with a comprehensive data-analytics-driven solution for devices at the most advanced process nodes.”
In-chip monitoring is now essential at advanced process nodes as it enables mission critical management of increasingly variable physical and functional conditions in real-time, thereby increasing performance and reliability. Moortec brings to Synopsys the industry’s most advanced and comprehensive range of in-chip PVT sensors and control subsystems. Moortec’s technology has been adopted by many of the world’s largest fabless and IDM companies, and has been used on hundreds of chip designs on all popular process nodes down to 5nm.
The integration of Moortec’s sensor technology into the Synopsys SLM platform will not only provide real-time in-chip feedback, data from these sensors will now be extracted and fed to the platform’s analytics engines. The environmental data provided by these sensors is an essential part of fully understanding complex activities within the chip. Combining this information with data from other structural and functional monitors provide the rich data needed to derive the greatest optimizations throughout the lifecycle.