CORDIC Hardware Acceleration Using DMA-Based ISA Extension

The use of RISC-based embedded processors aimed at low cost and low power is becoming an increasingly popular ecosystem for both hardware and software development. High-performance yet low-power embedded processors may be attained via the use of hardware acceleration and Instruction Set Architecture (ISA) extension. Recent publications of AI have demonstrated the use of Coordinate Rotation Digital Computer (CORDIC) as a dedicated low-power solution for solving nonlinear equations applied to Neural Networks (NN). This paper proposes ISA extension to support floating-point CORDIC, providing efficient hardware acceleration for mathematical functions. A new DMA-based ISA extension approach integrated with a pipeline CORDIC accelerator is proposed. The CORDIC ISA extension is directly interfaced with a standard processor data path, allowing efficient implementation of new trigonometric ALU-based custom instructions. The proposed DMA-based CORDIC accelerator can also be used to perform repeated array calculations, offering a significant speedup over software implementations. The proposed accelerator is evaluated on Intel Cyclone-IV FPGA as an extension to Nios processor. Experimental results show a significant speedup of over three orders of magnitude compared with software implementation, while applied to trigonometric arrays, and outperforms the existing commercial CORDIC hardware accelerator.

A Time-Domain z−1 Circuit with Digital Calibration

This paper presents a novel circuit of a z−1 operation which is suitable, as a basic building block, for time-domain topologies and signal processing. The proposed circuit employs a time register circuit which is based on the capacitor discharging method. The large variation of the capacitor discharging slope over technology process and chip temperature variations which affect the z−1 accuracy is improved using a novel digital calibration loop. The circuit is designed using a 28 nm Samsung FD-SOI process under 1 V supply voltage with 5 MHz sampling frequency. Simulation results validate the theoretical analysis presenting a variation of capacitor voltage discharging slope less than 5% over worst-case process corners for temperature between 0 °C and 100 °C while consuming only 30 μA. Also, the worst-case accuracy of z−1 operation is better than 33 ps for input pulse widths between 5 ns and 45 ns presenting huge improvement compared with the uncalibrated operator.

A Framework for Ultra Low-Power Hardware Accelerators Using NNs for Embedded Time Series Classification

In embedded applications that use neural networks (NNs) for classification tasks, it is important to not only minimize the power consumption of the NN calculation, but of the whole system. Optimization approaches for individual parts exist, such as quantization of the NN or analog calculation of arithmetic operations. However, there is no holistic approach for a complete embedded system design that is generic enough in the design process to be used for different applications, but specific in the hardware implementation to waste no energy for a given application. Therefore, we present a novel framework that allows an end-to-end ASIC implementation of a low-power hardware for time series classification using NNs. This includes a neural architecture search (NAS), which optimizes the NN configuration for accuracy and energy efficiency at the same time. This optimization targets a custom designed hardware architecture that is derived from the key properties of time series classification tasks. Additionally, a hardware generation tool is used that creates a complete system from the definition of the NN. This system uses local multi-level RRAM memory as weight and bias storage to avoid external memory access. Exploiting the non-volatility of these devices, such a system can use a power-down mode to save significant energy during the data acquisition process. Detection of atrial fibrillation (AFib) in electrocardiogram (ECG) data is used as an example for evaluation of the framework. It is shown that a reduction of more than 95% of the energy consumption compared to state-of-the-art solutions is achieved.

LoRaWAN Base Station Improvement for Better Coverage and Capacity

Low Power Wide Area Network (LPWAN) technologies provide long-range and low power consumption for many battery-powered devices used in Internet of Things (IoT). One of the most utilized LPWAN technologies is LoRaWAN (Long Range WAN) with over 700 million connections expected by the year 2023. LoraWAN base stations need to ensure stable and energy-efficient communication without unnecessary repetitions with sufficient range coverage and good capacity. To meet these requirements, a simple and efficient upgrade in the design of LoRaWAN base station is proposed, based on using two or more concentrators. The development steps are outlined in this paper and the evaluation of the enhanced base station is done with a series of measurements conducted in Zagreb, Croatia. Through these measurements we compared received messages and communication parameters on novel and standard base stations. The results showed a significant increase in the probability of successful reception of messages on the novel base station which corresponds to the increase of base station capacity and can be very beneficial for the energy consumption of most LoRaWAN end devices.

FPGA Implementation of Mutual Authentication Protocol for Medication Security System

Medication safety administration is a complicated process involving the information of patients, drugs, and data storage. The sensitive data transmitted through wireless sensor networks (WSNs) from Internet of things (IoT) over an insecure channel is vulnerable to several threats and needs proper attention to be secured from adversaries. Taking medication safety into consideration, this paper presents a secure authentication protocol for wireless medical sensor networks. The XOR scheme-based algorithm is applied to achieve the purposes of data confidentiality. The proposed architecture is realized as hardware in a field-programmable gate array (FPGA) device which acts as a secure edge computing device. The performance of the proposed protocol is evaluated and simulated via Verilog hardware description language. The functionality of the proposed protocol is verified using the Altera Quartus II software tool and implemented in the Altera Cyclone II DE2-70 FPGA development module. Furthermore, the output signals from the FPGA are measured in the 16702A logic analyzer system to demonstrate real-time functional verification.

A Multi-Output Multi-String High-Efficiency WLED Driver Using 40 nm CMOS Technology

In this work, a multi-independent-output, multi-string, high-efficiency, boost-converter-based white LED (WLED) driver architecture is proposed. It utilizes a single inductor main switch with a common maximum duty cycle controller (MDCC) in the feedback loop. A simple pulse skipping controller (PSC) is utilized in each high-side switch of the multiple independent outputs. Despite the presence of multiple independent outputs, a single over-voltage protection (OVP) circuit is used at the output to protect the circuit from any voltage above 27 V. An open circuit in any of the strings is addressed, in addition to the LED’s short-circuit conditions. Excellent current matching between strings is achieved, despite the low ON-resistance (Rdson) of transistors used in the 40 nm process. Most circuits are designed in digital CMOS logic to overcome the extreme process variations in the 40 nm node. Compared to a single output parallel strings topology, a 50% improvement in efficiency is achieved relative to extremely unbalanced strings. Three strings are used in this proposal, but more strings can be supported with the same topology. Each string is driven by a 25 mA current sink. An input voltage of 3.2–4.2 V and an output voltage up to 27 V are supported.

Cost-Effective and Low Power IoT-Based Paper Supply Monitoring System: An Application Modeling Approach

IoT designers face the dual complexity of obtaining good application-level performance and user satisfaction under constraints on computing and power resources. We introduce a new IoT device for paper roll supply management in bathrooms and kitchens, both for homes and businesses, that is extremely cost effective and battery power-efficient. The device can be installed on practically any paper roll dispenser and makes use of existing Wi-Fi infrastructure. Despite Wi-Fi’s reputation as “unsupportive for power saving,” we introduce and experimentally validate a methodology for using Wi-Fi networks with low power utilization, resulting in a system that provides very good management of paper supplies while only requiring battery charging once every 3–4 months. The new device has the potential to provide more households and businesses with real-time, data-driven automated supply chains.

Design of In-Memory Parallel-Prefix Adders

Computational methods in memory array are being researched in many emerging memory technologies to conquer the ‘von Neumann bottleneck’. Resistive RAM (ReRAM) is a non-volatile memory, which supports Boolean logic operation, and adders can be implemented as a sequence of Boolean operations in the memory. While many in-memory adders have recently been proposed, their latency is exorbitant for increasing bit-width (O(n)). Decades of research in computer arithmetic have proven parallel-prefix technique to be the fastest addition technique in conventional CMOS-based binary adders. This work endeavors to move parallel-prefix addition to the memory array to significantly minimize the latency of in-memory addition. Majority logic was chosen as the fundamental logic primitive and parallel-prefix adders synthesized in majority logic were mapped to the memory array using the proposed algorithm. The proposed algorithm can be used to map any parallel-prefix adder to a memory array and mapping is performed in such a way that the latency of addition is minimized. The proposed algorithm enables addition in O(log(n)) latency in the memory array.

A Case Study on Remote Instrumentation of Vibration and Temperature in Bearing Housings

Data collection is one of the most relevant topics of modern automation and industry. It is usually a costly and time-consuming task, especially in continuous processes. Our case study takes place in a sugar cane mill. The required continuous operation of a belt conveyor for bagasse transportation makes it a critical system in the overall production process. Therefore, a predictive maintenance tool is highly applicable here. We identified bearing housings as critical points for data collection intended for prognostics of the conveyor. However, given the number of points, the cost of a commercial solution becomes unfeasible by our company. This paper reports the development of low-cost devices for measurements and wireless transmission of vibration and temperature data from bearing housings. We assessed several sensor options and made decisions based on a cost-suitability commitment, which led to the design of the electronic devices. The devices were tested for correct operation, reliability (99%), and relative measurement errors under 1.2%. From the tests, we conclude that our proposal is appropriate for our case study’s industrial needs and budget restrictions.

Design and Validation of Low-Power Secure and Dependable Elliptic Curve Cryptosystem

The elliptic curve cryptosystem (ECC) has been proven to be vulnerable to non-invasive side-channel analysis attacks, such as timing, power, visible light, electromagnetic emanation, and acoustic analysis attacks. In ECC, the scalar multiplication component is considered to be highly susceptible to side-channel attacks (SCAs) because it consumes the most power and leaks the most information. In this work, we design a robust asynchronous circuit for scalar multiplication that is resistant to state-of-the-art timing, power, and fault analysis attacks. We leverage the genetic algorithm with multi-objective fitness function to generate a standard Boolean logic-based combinational circuit for scalar multiplication. We transform this circuit into a multi-threshold dual-spacer dual-rail delay-insensitive logic (MTD3L) circuit. We then design point-addition and point-doubling circuits using the same procedure. Finally, we integrate these components together into a complete secure and dependable ECC processor. We design and validate the ECC processor using Xilinx ISE 14.7 and implement it in a Xilinx Kintex-7 field-programmable gate array (FPGA).