Memory arrays such as SRAM cells are responsible to the high-power consumption of modern digital systems. This investigation proposed an SRAM utilizing an ultra-low power cell, implemented using the 16-nm FinFET CMOS technology. Voltage supply selection of the static RAM cells is done by gating the wordline (WL) enable. In standby mode, the cell wordline is not activated, where the cell operates on a lower voltage level so that the stored bit status is still retained. On the other hand, the normal mode is activated when the wordline of the cell is enabled. Theoretical derivations, all-PVT-corner post-layout simulations, and measurement results were provided for verification of the functionality and performance. An SRAM of 1-kb capacity is designed based on the propose cell. The on-silicon measurement demonstrates 0.006832 fJ (energy/bit) at 500 MHz clock rate and 0.8 V supply.

This investigation presents a digital logic accelerator (DLA) design of a neural network hardware that utilizes output reuse. The DLA is used in the detection mechanism of underwater objects that was deployed in an underwater vehicle. A modified YoloV3-tiny network was also implemented to detect more than 20 underwater objects. The proposed DLA uses processing units that have parallel architectures of output windows, and output channels. Moreover, a new Inter-Controller is designed to control the direct memory access (DMA) together with a new Reshape module to improve the performance and power efficiency. A detailed description of the design as well as the measurements on silicon are presented. The chip is realized using a typical 180-nm CMOS process. It showed a performance result of 40.96 GOPS and the power consumption is 196.8 mW. The DLA was tested to demonstrate 19.88 frames per second and 40.96 GOPS.

An ultra‐low‐energy SRAM composed of single‐ended cells is demonstrated on silicon in this investigation. More specifically, the supply voltages of cells are gated by wordline (WL) enable, and the voltage mode select (VMS) signals select one of the corresponding supply voltages. A lower voltage is selected to maintain stored bit state when cells are not accessed, lowering the standby power. And when selecting a cell (i.e. WL is enabled) to perform the read or write (R/W) operations, the normal supply voltage is used. A 1‐kb SRAM prototype based on the single‐ended cells with built‐in self‐test (BIST) and power‐delay production (PDP) reduction circuits was realised on silicon using 40‐nm CMOS technology. Theoretical derivations and simulations of all‐PVT‐corner variations are also disclosed to justify low energy performance. Physical measurements of six prototypes on silicon shows that the energy per bit is 1.0 fJ at the 10 MHz system clock.

Physical unclonable functions (PUFs) are increasingly recognized as a key technology for enhancing hardware and the Internet of Things (IoT) security. The IoT devices are often plagued by weak security measures, making them susceptible to various external threats. To address these vulnerabilities, robust and reliable security solutions are critical. This study introduces a highly reliable and low-power PUF application-specific integrated circuit (ASIC) design specifically designed for the IoT security applications. Initially, the proposed design is deployed on a Xilinx ZYNQ 7000 field-programmable gate array (FPGA) board operating at 100 MHz and later designed and fabricated using the Cadence Innovus in the 180-nm CMOS process on silicon. This work presents and evaluates a novel xnor–xor ring oscillator (RO) PUF with a configurable frequency. The design’s performance is analyzed using statistical metrics, including reliability, uniqueness, and uniformity. The xnor–xor RO PUF ASIC demonstrates max reliability of 91.92%, a uniqueness of 49.62%, and a uniformity of 50.19% on silicon.