GF-Dolphin 22FDX Turnkey Adaptive Body Bias Solutions Offer Big Energy Savings, Faster TTM. Design Kits Q2/19.

GlobalFoundries and Dolphin Integration are collaborating on the development of a series of adaptive body bias (ABB) solutions to improve the energy efficiency and reliability of SoCs on GF’s 22nm FD-SOI (22FDX®) process technology for a wide range of high-growth applications such as 5G, IoT and automotive. The goal of the IP is to accelerate energy-efficient SoC designs and push the boundaries of single-chip integration. The design kits with turnkey ABB solutions will be available starting in Q2 2019.

As part of the collaboration, Dolphin and GF are working together to develop a series of off-the-shelf ABB solutions for accelerating and easing body bias* implementation on SoC designs. ABB is a unique feature of FD-SOI that enables designers to leverage forward and reverse body bias techniques to dynamically compensate for process, supply voltage, temperature (PVT) variations and aging effects to achieve additional performance, power, area and cost improvements beyond those from scaling alone.

The ABB solutions in development by GF and Dolphin consist of self-contained IPs embedding the body bias voltage regulation, PVT and aging monitors and control loop as well as complete design methodologies to fully leverage the benefits of corner tightening. GF says its 22FDX technology offers the industry’s lowest static and dynamic power consumption. With automated transistor body biasing adjustment, Dolphin Integration can achieve up to 7x energy efficiency with power supply as low as 0.4V on 22FDX designs.

“We have been working with GF for more than two years on advanced and configurable power management IPs for low power and energy efficient applications,” said Philippe Berger, CEO of Dolphin Integration. “Through our ongoing collaboration with GF, we are focused on creating turnkey IP solutions that allow designers to realize the full benefit of FD-SOI for any SoC design in 22FDX.”

“In order to simplify our client designs and shorten their time-to-market, GF and our ecosystem partners are helping to pave the way to future performance standards in 5G, IoT and automotive,” said Mark Ireland, vice president of ecosystem partnerships at GF. “With the support of silicon IP providers like Dolphin Integration, new power, performance and reliability design infrastructures will be available to customers to fully leverage the benefits of GF’s 22FDX technology.”

As STMicroelectronics Fellow and Professor Andreia Cathelin has beautifully noted, “Body biasing is not an obligation. It’s an opportunity.” And GF/Dolphin clearly aim to make that opportunity a much easier and more powerful one to take advantage of.

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*A note on terminology: the terms back bias and body bias are used interchangeably. Likewise the terms adaptive and dynamic when used in the FD-SOI context. Here is a quick explanation of how it works, from an ST paper from several years ago:

Back-biasing consists of applying a voltage just under the BOX of target transistors. Doing so changes the electrostatic control of the transistors and shifts their threshold voltage VT, to either get more drive current (hence higher performance) at the expense of increased leakage current (forward back-bias, FBB) or cut leakage current at the expense of reduced performance. While back-bias in planar FD is somewhat similar to body-bias that can be implemented in bulk CMOS technology, it offers a number of key advantages in terms of level and efficiency of the bias that can be applied. Back-biasing can be utilized in a dynamic way, on a block-by-block basis. It can be used to boost performance during the limited periods of time when maximum peak performance is required from that block. It can also be used to cut leakage during the periods of time when limited performance is not an issue. In other words, back-bias offers a new and efficient knob on the speed/power trade-off.

For another good discussion of body biasing in FD-SOI, you might want to check out The Return Of Body Biasing by Semiconductor Engineering’s Ann Steffora Mutschler from a couple years ago.