Hybrid Precision Floating-Point (HPFP) Selection to Optimize Hardware-Constrained Accelerator for CNN Training.

The rapid advancement in AI requires efficient accelerators for training on edge devices, which often face challenges related to the high hardware costs of floating-point arithmetic operations. To tackle these problems, efficient floating-point formats inspired by block floating-point (BFP), such as Microsoft Floating Point (MSFP) and FlexBlock (FB), are emerging. However, they have limited dynamic range and precision for the smaller magnitude values within a block due to the shared exponent.

Analog Convolutional Operator Circuit for Low-Power Mixed-Signal CNN Processing Chip.

In this paper, we propose a compact and low-power mixed-signal approach to implementing convolutional operators that are often responsible for most of the chip area and power consumption of Convolutional Neural Network (CNN) processing chips. The convolutional operators consist of several multiply-and-accumulate (MAC) units. MAC units are the primary components that process convolutional layers and fully connected layers of CNN models.

A Compact and Low-Power SoC Design for Spiking Neural Network Based on Current Multiplier Charge Injector Synapse.

This paper presents a compact analog system-on-chip (SoC) implementation of a spiking neural network (SNN) for low-power Internet of Things (IoT) applications. The low-power implementation of an SNN SoC requires the optimization of not only the SNN model but also the architecture and circuit designs. In this work, the SNN has been constituted from the analog neuron and synaptic circuits, which are designed to optimize both the chip area and power consumption.

Security Requirements and Challenges of 6G Technologies and Applications.

After implementing 5G technology, academia and industry started researching 6th generation wireless network technology (6G). 6G is expected to be implemented around the year 2030. It will offer a significant experience for everyone by enabling hyper-connectivity between people and everything.

Optimal Architecture of Floating-Point Arithmetic for Neural Network Training Processors.

The convergence of artificial intelligence (AI) is one of the critical technologies in the recent fourth industrial revolution. The AIoT (Artificial Intelligence Internet of Things) is expected to be a solution that aids rapid and secure data processing. While the success of AIoT demanded low-power neural network processors, most of the recent research has been focused on accelerator designs only for inference.

Centralized Threshold Key Generation Protocol Based on Shamir Secret Sharing and HMAC Authentication.

Many group key management protocols have been proposed to manage key generation and distribution of vehicular communication. However, most of them suffer from high communication and computation costs due to the complex elliptic curve and bilinear pairing cryptography. Many shared secret protocols have been proposed using polynomial evaluation and interpolation to solve the previous complexity issues.

A Key Management Protocol Based on the Hash Chain Key Generation for Securing LoRaWAN Networks.

Recently, many Low Power Wide Area Network (LPWAN) protocols have been proposed for securing resource-constrained Internet of Things (IoT) devices with negligible power consumption. The Long Range Wide Area Network (LoRaWAN) is a low power communication protocol that supports message authentication, integrity, and encryption using two-session preshared secret keys. However, although the LoRaWAN supports some security functions, it suffers from session key generation and key update problems.

A Low-Power Spiking Neural Network Chip Based on a Compact LIF Neuron and Binary Exponential Charge Injector Synapse Circuits.

To realize a large-scale Spiking Neural Network (SNN) on hardware for mobile applications, area and power optimized electronic circuit design is critical. In this work, an area and power optimized hardware implementation of a large-scale SNN for real time IoT applications is presented. The analog Complementary Metal Oxide Semiconductor (CMOS) implementation incorporates neuron and synaptic circuits optimized for area and power consumption.

Multi-Zone Authentication and Privacy-Preserving Protocol (MAPP) Based On the Bilinear Pairing Cryptography for 5G-V2X.

5G-Vehicle-to-Everything (5G-V2X) supports high-reliability and low latency autonomous services and applications. Proposing an efficient security solution that supports multi-zone broadcast authentication and satisfies the 5G requirement is a critical challenge. In The 3rd Generation Partnership Project (3GPP) Release 16 standard, for Cellular- Vehicle-to-Everything (C-V2X) single-cell communication is suggested to reuse the IEEE1609.

An Ultra-Wide Load Range Voltage Converter Using Proactive Phase Frequency Modulation for IoT Sensors.

Modern sensor nodes have multiple operating states, which causes a conventional voltage converter to perform poorly over a wide load range of the operating states. This paper proposes a voltage converter whose switching frequency and output voltage are proactively adjusted to maintain high conversion efficiency. This allows the converter to exploit a wider frequency range to cover a wide load range.

A Scalable and Secure Group Key Management Method for Secure V2V Communication.

Safety applications based on vehicle-to-everything (V2X) communications can significantly enhance road safety and reduce traffic fatalities. Ensuring the security and privacy of the vehicular network is essential for the widespread adoption of V2X communications for commercial use. V2X safety and service applications require periodic broadcast communications among all the vehicles.

Comparative Experiments of V2X Security Protocol Based on Hash Chain Cryptography.

Vehicle-to-everything (V2X) is the communication technology designed to support road safety for drivers and autonomous driving. The light-weight security solution is crucial to meet the real-time needs of on-board V2X applications. However, most of the recently proposed V2X security protocols-based on the Elliptic Curve Digital Signature Algorithm (ECDSA)-are not efficient enough to support fast processing and reduce the communication overhead between vehicles.

CMOS Capacitive Fingerprint Sensor Based on Differential Sensing Circuit with Noise Cancellation.

In this paper, we introduce a differential sensing technique for CMOS capacitive fingerprint detection. It employs a new capacitive-sensing cell structure with charge sharing detection and readout circuit. The proposed technique also can eliminate the effect of parasitic capacitances by employing parasitic insensitive switched-capacitor structure and so increases the sensitivity even under severe noisy conditions.

Slowest local operators in quantum spin chains.

We numerically construct slowly relaxing local operators in a nonintegrable spin-1/2 chain. Restricting the support of the operator to M consecutive spins along the chain, we exhaustively search for the operator that minimizes the Frobenius norm of the commutator with the Hamiltonian. We first show that the Frobenius norm bounds the time scale of relaxation of the operator at high temperatures.

Thermalization of entanglement.

We explore the dynamics of the entanglement entropy near equilibrium in highly entangled pure states of two quantum-chaotic spin chains undergoing unitary time evolution. We examine the relaxation to equilibrium from initial states with either less or more entanglement entropy than the equilibrium value, as well as the dynamics of the spontaneous fluctuations of the entanglement that occur in equilibrium. For the spin chain with a time-independent Hamiltonian and thus an extensive conserved energy, we find slow relaxation of the entanglement entropy near equilibration.

Modeling of memristive and memcapacitive behaviors in metal-oxide junctions.

Memristive behavior has been clearly addressed through growth and shrinkage of thin filaments in metal-oxide junctions. Capacitance change has also been observed, raising the possibility of using them as memcapacitors. Therefore, this paper proves that metal-oxide junctions can behave as a memcapacitor element by analyzing its characteristics and modeling its memristive and memcapacitive behaviors.

Eigenstate thermalization and representative states on subsystems.

We consider a quantum system A∪B made up of degrees of freedom that can be partitioned into spatially disjoint regions A and B. When the full system is in a pure state in which regions A and B are entangled, the quantum mechanics of region A described without reference to its complement is traditionally assumed to require a reduced density matrix on A. While this is certainly true as an exact matter, we argue that under many interesting circumstances expectation values of typical operators anywhere inside A can be computed from a suitable pure state on A alone, with a controlled error.

Testing whether all eigenstates obey the eigenstate thermalization hypothesis.

We ask whether the eigenstate thermalization hypothesis (ETH) is valid in a strong sense: in the limit of an infinite system, every eigenstate is thermal. We examine expectation values of few-body operators in highly excited many-body eigenstates and search for "outliers," the eigenstates that deviate the most from ETH. We use exact diagonalization of two one-dimensional nonintegrable models: a quantum Ising chain with transverse and longitudinal fields, and hard-core bosons at half-filling with nearest- and next-nearest-neighbor hopping and interaction.

Ballistic spreading of entanglement in a diffusive nonintegrable system.

We study the time evolution of the entanglement entropy of a one-dimensional nonintegrable spin chain, starting from random nonentangled initial pure states. We use exact diagonalization of a nonintegrable quantum Ising chain with transverse and longitudinal fields to obtain the exact quantum dynamics. We show that the entanglement entropy increases linearly with time before finite-size saturation begins, demonstrating a ballistic spreading of the entanglement, while the energy transport in the same system is diffusive.