It will do this by using the Adaptive Body Bias (ABB) feature of its 22FDX platform which gives designers significantly more precision when fine-tuning the transistor threshold voltage of a circuit, enabling them to more effectively optimise the performance, energy efficiency, area, and reliability of a chip to meet the needs of a specific application.
GF customers working in IoT, wearables, hearables, RF, and edge computing are using ABB to further boost the efficiency of their designs by utilizing the 22FDX platform’s ultra-low power and low leakage capabilities.
The ABB feature is being used by GF to extend the value, high performance, ultra-low power, and broad integration capabilities of its 22FDX platform. To date, GF’s 22FDX platform has realized $4.5 billion in design wins, with more than 350 million chips shipped to customers around the world.
“With its best-in-class performance, power consumption, and broad feature integration capability, GF’s differentiated 22FDX platform is clearly the solution of choice for designers and innovators working in IoT, wearables, Edge AI, and other exciting applications,” said Mike Hogan, senior vice president and general manager of Automotive, Industrial and Multi-market at GF. “Empowering these customers to take advantage of the platform’s body biasing, and further increase the performance, efficiency, and battery life of their devices, is another example of how GF is enabling the industry to advance the frontier of connectivity toward a fully realized, global IoT.”
This wider use of ABB features is made possible and supported by GF’s strong ecosystem of IP and EDA tool partners, and body bias features are included in the 22FDX process design kit (PDK).
“GF’s ecosystem partners play a critical role in enabling designers to seamlessly and effectively implement ABB in their chips,” said Mike Cadigan, senior vice president of Customer Design Enablement at GF. “Through innovative IP and EDA tool support, GF’s ecosystem partners have created block IPs and end-to-end enablement flows for ABB, as well as static body bias, across a range of applications.”
