This paper presents the implementation details and silicon results of a 3 GHz dual-core ARM Cortex TM -A9 (A9) manufactured in the 28 nm planar Ultra-Thin Box and Body Fully-Depleted CMOS (UTBB FD-SOI) technology. The implementation is based on a fully synthesizable standard design flow. The design exploits the important flexibility provided by the FD-SOI technology, notably a wide Dynamic Voltage and Frequency Scaling (DVFS) range, from 0.52 V to 1.37 V, and Forward Body Bias (FBB) techniques up to 1.3 V. Detailed explanations of the body-biasing techniques specific to this technology are largely presented, in the context of a multi- VT co-integration, which enable this energy efficient silicon implementation. The system integrates all the advanced IPs for energy efficiency as well as the body bias generator and a fast (μs range) dynamic body bias management capability. The measured dual core CPU maximum operation frequency is 3 GHz (for 1.37 V) and it can be operated down to 300 MHz (for 0.52 V) in full continuous DVFS. The obtained relative performance, with respect to an equivalent planar 28 nm bulk CMOS chip, shows an improvement of +237% at 0.6 V, or +544% at 0.61 V with 1.3 V FBB.

A 3 GHz Dual Core Processor ARM Cortex TM -A9 in 28 nm UTBB FD-SOI CMOS With Ultra-Wide Voltage Range and Energy Efficiency Optimization

Novel pervasive devices such as smart surveillance cameras and autonomous micro-UAVs could greatly benefit from the availability of a computing device supporting embedded computer vision at a very low power budget. To this end, we propose PULP (Parallel processing Ultra-Low Power platform), an architecture built on clusters of tightly-coupled OpenRISC ISA cores, with advanced techniques for fast performance and energy scalability that exploit the capabilities of the STMicroelectronics UTBB FD-SOI 28nm technology. We show that PULP performance can be scaled over a 1x-354x range, with a peak theoretical energy efficiency of 211 GOPS/W. We present performance results for several demanding kernels from the image processing and vision domain, with post-layout power modeling: a motion detection application that can run at an efficiency up to 192 GOPS/W (90 % of the theoretical peak); a ConvNet-based detector for smart surveillance that can be switched between 0.7 and 27fps operating modes, scaling energy consumption per frame between 1.2 and 12mJ on a 320 ×240 image; and FAST + Lucas-Kanade optical flow on a 128 ×128 image at the ultra-low energy budget of 14 μJ per frame at 60fps.

PULP: A Ultra-Low Power Parallel Accelerator for Energy-Efficient and Flexible Embedded Vision

The most important application of ICs, today, is most probably the lnternet-of-Things It involves sensor nodes and communications at the lowest-possible power levels Similar low power levels are required for the next-generation smart-phones as images and video become increasing requirements, in phone, body-worn, and automotive applications Whatever technology is used, portability requires reduced power consumption

1.3 Analog CMOS from 5 micrometer to 5 nanometer

Ultra-low power operation and extreme energy efficiency are strong requirements for a number of high-growth application areas, such as E-health, Internet of Things, and wearable Human–Computer Interfaces. A promising approach to achieve up to one order of magnitude of improvement in energy efficiency over current generation of integrated circuits is near-threshold computing. However, frequency degradation due to aggressive voltage scaling may not be acceptable across all performance-constrained applications. Thread-level parallelism over multiple cores can be used to overcome the performance degradation at low voltage. Moreover, enabling the processors to operate on-demand and over a wide supply voltage and body bias ranges allows to achieve the best possible energy efficiency while satisfying a large spectrum of computational demands. In this work we present the first ever implementation of a 4-core cluster fabricated using conventional-well 28 nm UTBB FD-SOI technology. The multi-core architecture we present in this work is able to operate on a wide range of supply voltages starting from 0.44 V to 1.2 V. In addition, the architecture allows a wide range of body bias to be applied from −1.8 V to 0.9 V. The peak energy efficiency 60 GOPS/W is achieved at 0.5 V supply voltage and 0.5 V forward body bias. Thanks to the extended body bias range of conventional-well FD-SOI technology, high energy efficiency can be guaranteed for a wide range of process and environmental conditions. We demonstrate the ability to compensate for up to 99.7% of chips for process variation with only ±0.2 V of body biasing, and compensate temperature variation in the range −40 °C to 120 °C exploiting −1.1 V to 0.8 V body biasing. When compared to leading-edge near-threshold RISC processors optimized for extremely low power applications, the multi-core architecture we propose has 144× more performance at comparable energy efficiency levels. Even when compared to other low-power processors with comparable performance, including those implemented in 28 nm technology, our platform provides 1.4× to 3.7× better energy efficiency.

A 60 GOPS/W, −1.8 V to 0.9 V body bias ULP cluster in 28 nm UTBB FD-SOI technology

This work demonstrates a RISC-V vector microprocessor implemented in 28 nm FDSOI with fully integrated simultaneous-switching switched-capacitor DC–DC (SC DC–DC) converters and adaptive clocking that generates four on-chip voltages between 0.45 and 1 V using only 1.0 V core and 1.8 V IO voltage inputs. The converters achieve high efficiency at the system level by switching simultaneously to avoid charge-sharing losses and by using an adaptive clock to maximize performance for the resulting voltage ripple. Details about the implementation of the DC–DC switches, DC–DC controller, and adaptive clock are provided, and the sources of conversion loss are analyzed based on measured results. This system pushes the capabilities of dynamic voltage scaling by enabling fast transitions (20 ns), simple packaging (no off-chip passives), low area overhead (16%), high conversion efficiency (80%–86%), and high energy efficiency (26.2 DP GFLOPS/W) for mobile devices.

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A RISC-V Vector Processor With Simultaneous-Switching Switched-Capacitor DC–DC Converters in 28 nm FDSOI

This paper presents the implementation details and silicon results of a 2.6GHz dual-core ARM Cortex A9 manufactured in a 28nm Ultra-Thin Body and BOX FD-SOI technology. The implementation is based on a fully synthesizable standard design flow, and the design exploits the great flexibility provided by FD-SOI technology, notably a wide Dynamic Voltage and Frequency Scaling (DVFS) range, from 0.6V to 1.2V, and forward body bias (FBB) techniques up to 1.3V bias voltage, thus enabling an extremely energy efficient implementation.

2.6GHz ultra-wide voltage range energy efficient dual A9 in 28nm UTBB FD-SOI

A method and system for managing the power supply of a component and of a memory cooperating with the component are disclosed. The component and the memory are powered with a first variable power supply source having a first power supply voltage level greater than a minimum operating voltage of the memory. When a voltage level of the first power supply source drops and reaches a threshold that is greater than or equal to the minimum operating voltage of the memory, the power supply of the memory is toggled to a second power supply source having a second voltage level that is greater than or equal to the minimum operating voltage of the memory.

Method and System for Managing the Power Supply of a Component

A digital circuit includes a scan chain which loads data into and unloads data from the digital circuit. Checking circuitry is coupled to the scan chain and generates a first digital signature based on data indicative of a pre-testing status of the digital circuit as the data is unloaded from the digital circuit via the scan chain. When testing is completed, the data is restored to the digital circuit via the scan chain. The checking circuitry generates a second digital signature as the data is loaded into the digital circuit. The first digital signature is compared to the second digital signature to verify an integrity of the process. A specific data pattern may be loaded into the scan chain as the data is unloaded. An output of the scan chain may be monitored to detect the pattern and an error signal may be generated based on when the pattern is detected.

David Jacquet

Papers

A 3 GHz Dual Core Processor ARM Cortex TM -A9 in 28 nm UTBB FD-SOI CMOS With Ultra-Wide Voltage Range and Energy Efficiency Optimization

2.6GHz ultra-wide voltage range energy efficient dual A9 in 28nm UTBB FD-SOI

Method and System for Managing the Power Supply of a Component

Method, device and article to test digital circuits

Method and device to test digital circuits