This paper presents an ultra-low power batteryless energy harvesting body sensor node (BSN) SoC fabricated in a commercial 130 nm CMOS technology capable of acquiring, processing, and transmitting electrocardiogram (ECG), electromyogram (EMG), and electroencephalogram (EEG) data. This SoC utilizes recent advances in energy harvesting, dynamic power management, low voltage boost circuits, bio-signal front-ends, subthreshold processing, and RF transmitter circuit topologies. The SoC is designed so the integration and interaction of circuit blocks accomplish an integrated, flexible, and reconfigurable wireless BSN SoC capable of autonomous power management and operation from harvested power, thus prolonging the node lifetime indefinitely. The chip performs ECG heart rate extraction and atrial fibrillation detection while only consuming 19 μW, running solely on harvested energy. This chip is the first wireless BSN powered solely from a thermoelectric harvester and/or RF power and has lower power, lower minimum supply voltage (30 mV), and more complete system integration than previously reported wireless BSN SoCs.

A Batteryless 19 $\mu$ W MICS/ISM-Band Energy Harvesting Body Sensor Node SoC for ExG Applications

The discovery of ferroelectricity in oxides that are compatible with modern semiconductor manufacturing processes, such as hafnium oxide, has led to a re-emergence of the ferroelectric field-effect transistor in advanced microelectronics. A ferroelectric field-effect transistor combines a ferroelectric material with a semiconductor in a transistor structure. In doing so, it merges logic and memory functionalities at the single-device level, delivering some of the most pressing hardware-level demands for emerging computing paradigms. Here, we examine the potential of the ferroelectric field-effect transistor technologies in current embedded non-volatile memory applications and future in-memory, biomimetic and alternative computing models. We highlight the material- and device-level challenges involved in high-volume manufacturing in advanced technology nodes (≤10 nm), which are reminiscent of those encountered in the early days of high-K-metal-gate transistor development. We argue that the ferroelectric field-effect transistors can be a key hardware component in the future of computing, providing a new approach to electronics that we term ferroelectronics. This Perspective examines the use of ferroelectric field-effect transistor technologies in current embedded non-volatile memory applications and future in-memory, biomimetic and alternative computing models, arguing that the devices will be a key component in the development of data-centric computing.

The future of ferroelectric field-effect transistor technology

Energy harvesting has been widely investigated as a promising method of providing power for ultra-low-power applications. Such energy sources include solar energy, radio-frequency (RF) radiation, piezoelectricity, thermal gradients, etc. However, the power supplied by these sources is highly unreliable and dependent upon ambient environment factors. Hence, it is necessary to develop specialized systems that are tolerant to this power variation, and also capable of making forward progress on the computation tasks. The simulation platform in this paper is calibrated using measured results from a fabricated nonvolatile processor and used to explore the design space for a nonvolatile processor with different architectures, different input power sources, and policies for maximizing forward progress.

Architecture exploration for ambient energy harvesting nonvolatile processors

Reconfigurable architectures have gained popularity in recent years as they allow the design of energy-efficient accelerators. Fine-grain fabrics (e.g. FPGAs) have traditionally suffered from performance and power inefficiencies due to bit-level reconfigurable abstractions. Both fine-grain and coarse-grain architectures (e.g. CGRAs) traditionally require low level programming and suffer from long compilation times. We address both challenges with Plasticine, a new spatially reconfigurable architecture designed to efficiently execute applications composed of parallel patterns. Parallel patterns have emerged from recent research on parallel programming as powerful, high-level abstractions that can elegantly capture data locality, memory access patterns, and parallelism across a wide range of dense and sparse applications.We motivate Plasticine by first observing key application characteristics captured by parallel patterns that are amenable to hardware acceleration, such as hierarchical parallelism, data locality, memory access patterns, and control flow. Based on these observations, we architect Plasticine as a collection of Pattern Compute Units and Pattern Memory Units. Pattern Compute Units are multi-stage pipelines of reconfigurable SIMD functional units that can efficiently execute nested patterns. Data locality is exploited in Pattern Memory Units using banked scratchpad memories and configurable address decoders. Multiple on-chip address generators and scatter-gather engines make efficient use of DRAM bandwidth by supporting a large number of outstanding memory requests, memory coalescing, and burst mode for dense accesses. Plasticine has an area footprint of 113 mm2 in a 28nm process, and consumes a maximum power of 49 W at a 1 GHz clock. Using a cycle-accurate simulator, we demonstrate that Plasticine provides an improvement of up to 76.9x in performance-per-Watt over a conventional FPGA over a wide range of dense and sparse applications.

https://dl.acm.org/doi/pdf/10.1145/3079856.3080256

Plasticine: A Reconfigurable Architecture For Parallel Paterns

Various industry forecasts project that, by 2020, there will be around 50 billion devices connected to the Internet of Things (IoT), helping to engineer new solutions to societal-scale problems such as healthcare, energy conservation, transportation, etc. Most of these devices will be wireless due to the expense, inconvenience, or in some cases, the sheer infeasibility of wiring them. Further, many of them will have stringent size constraints. With no cord for power and limited space for a battery, powering these devices (to achieve several months to possibly years of unattended operation) becomes a daunting challenge. This paper highlights some promising directions for addressing this challenge, focusing on three main building blocks: (a) the design of ultra-low power hardware platforms that integrate computing, sensing, storage, and wireless connectivity in a tiny form factor, (b) the development of intelligent system-level power management techniques, and (c) the use of environmental energy harvesting to make IoT devices self-powered, thus decreasing -- in some cases, even eliminating -- their dependence on batteries. We discuss these building blocks in detail and illustrate case-studies of systems that use them judiciously, including the QUBE wireless embedded platform, which exploits the characteristics of emerging non-volatile memory technologies to seamlessly and efficiently enable long-running computations in systems that experience frequent power loss (i.e., intermittently powered systems).

Powering the internet of things

Subthreshold digital circuits minimize energy per operation and are thus ideal for ultralow-power (ULP) applications with low performance requirements. However, a large range of ULP applications continue to face performance constraints at certain times that exceed the capabilities of subthreshold operation. In this paper, we give two different examples to show that designing flexibility into ULP systems across the architecture and circuit levels can meet both the ULP requirements and the performance demands. Specifically, we first present a method that expands on ultradynamic voltage scaling (UDVS) to combine multiple supply voltages with component level power switches to provide more efficient operation at any energy-delay point and low overhead switching between points. This system supports operation across the space from maximum performance, when necessary, to minimum energy, when possible. It thus combines the benefits of single-V DD, multi-V DD, and dynamic voltage scaling (DVS) while improving on them all. Second, we propose that reconfigurable subthreshold circuits can increase applicability for ULP embedded systems. Since ULP devices conventionally require custom circuit design but the manufacturing volume for many ULP applications is low, a subthreshold field programmable gate array (FPGA) offers a cost-effective custom solution with hardware flexibility that makes it applicable across a wide range of applications. We describe the design of a subthreshold FPGA to support ULP operation and identify key challenges to this effort.

Flexible Circuits and Architectures for Ultralow Power

We demonstrate a non-volatile logic (NVL)-based SoC that backs up its working state (all flip-flops) upon receiving a power interrupt, has zero leakage in sleep mode, and needs less than 400ns to restore the system state upon power-up. Without NVL, a chip would either have to keep all flip-flops powered resulting in high standby power, or waste energy and time rebooting after power-up. For energy harvesting applications, NVL is a “must have” because there is no constant power source available to keep flip-flops (FFs) alive, and even when the intermittent power source is available, boot-up code alone may consume all of the harvested energy. For handheld devices with limited cooling and battery capacity, zero-leakage IC's with “instant-on” capability are ideal.

An 8MHz 75µA/MHz zero-leakage non-volatile logic-based Cortex-M0 MCU SoC exhibiting 100% digital state retention at V DD =0V with <400ns wakeup and sleep transitions

This paper examines the impact of technology scaling to 22nm on sub-threshold circuit design and proposes several solutions for sub-threshold circuits in new processes. To maintain energy-efficient sub-threshold operation, we must reduce variation and suppress leakage current. To combat random variation and minimize energy for nodes below 45nm, we show that special strategies are needed for different categories of sub-threshold circuits.

http://www.qed2.com/uploads/3/5/3/7/3537200/calhouniscas09subvt.pdf

Sub-threshold circuit design with shrinking CMOS devices

This paper presents a nonvolatile logic (NVL)-based 32-b microcontroller system-on-chip (SoC) that backs up its working state (all flip-flops) upon receiving a power interrupt, has zero leakage in sleep mode, and needs less than 400 ns to restore the system state upon power-up. Nonvolatile Fe-Cap-based mini-arrays backup the machine state and allow the chip to wake up instantly after a power cycle. Without NVL, a chip would either have to keep all flip-flops powered, resulting in high standby power, or waste energy and time rebooting after power-up. NVL allows systems to use leakier processes to achieve higher performance/lower dynamic power while still having zero leakage in the sleep mode. Optimized system, architecture, and circuit techniques are presented that make NVL practical by adding only 3.6% to the SoC area. Since nonvolatile elements are added to the SoC, reliability and testability have to be key features of the design. This is the first NVL SoC with measured NVL bitcell read signal margin data and extensive test and debug capabilities. The chip is fabricated in a commercial 130-nm low-leakage process and uses a single 1.5-V power supply.

An FRAM-Based Nonvolatile Logic MCU SoC Exhibiting 100% Digital State Retention at ${\rm VDD}=$ 0 V Achieving Zero Leakage With ${ 400-ns Wakeup Time for ULP Applications

Large scale 6T SRAM beyond 65 nm will increasingly rely on assist methods to overcome the functional limitations associated with scaling and the inherent read stability/write margin trade off. The primary focus of the circuit assist methods has been improved read or write margin with less attention given to the implications for performance. In this work, we introduce margin sensitivity and margin/delay analysis tools for assessing the functional effectiveness of the bias based assist methods and show the direct implications on voltage sensitive yield. A margin/delay analysis of bias based circuit assist methods is presented, highlighting the assist impact on the functional metrics, margin and performance. A means of categorizing the assist methods is developed to provide a first order understanding of the underlying mechanisms. The analysis spans four generations of low power technologies to show the trends and long term effectiveness of the circuit assist techniques in future low power bulk technologies.

/pdf/impact-of-circuit-assist-methods-on-margin-and-performance-2e1dwmny8v.pdf

Sudhanshu Khanna

Papers

Flexible Circuits and Architectures for Ultralow Power

An 8MHz 75µA/MHz zero-leakage non-volatile logic-based Cortex-M0 MCU SoC exhibiting 100% digital state retention at V DD =0V with <400ns wakeup and sleep transitions

Sub-threshold circuit design with shrinking CMOS devices

An FRAM-Based Nonvolatile Logic MCU SoC Exhibiting 100% Digital State Retention at ${\rm VDD}=$ 0 V Achieving Zero Leakage With ${ 400-ns Wakeup Time for ULP Applications

Impact of circuit assist methods on margin and performance in 6T SRAM