The Arm PL022 provides an interface for synchronous serial communication with peripheral devices connected to the  SoC via the Advanced Peripheral Bus (APB). It supports a choice of interface operation, Motorola compatible Serial Peripheral Interface (SPI), National Semiconductor Microwire, or Texas Instruments synchronous serial interface. See the Techology page for details. 

We propose the A-Cube design methodology to create medical decision support on the edge. The design and implementation of an atrial fibrillation detector hardware core was selected as a proof-of-concept study. To facilitate the required atrial fibrillation functionality, we adopted an established AI model, based on Long Short-Term Memory (LSTM) technology for hardware implementation. The adaptation was done by varying design parameters such as data window and the number of LSTM units.

Battery storage systems are an important source for powering emerging clean energy applications. The Battery Management System (BMS) is a critical component of modern battery storage, essential for efficient system monitoring, reducing run-time failures, prolonging charge-discharge lifecycle, and preventing battery stress or catastrophic situations. The BMS performs functionalities such as data acquisition and monitoring, battery state estimation, cell equalization, and charge protection, making it computationally intensive to manage large scale battery storage.

To design and verify a simple PLL for use as generator of clock signals in System on Chip design. The desired outcome from this project should be the following:

The resulting IP for these component blocks will be made available to the soclabs community for the upcoming design contest.

The dynamic range processor is a DSP function which does as it says on the tin; it compresses the dynamic range of the incoming signal. This is used most commonly in the music industry for its effects on the perceived loudness of audio. It is also used extensively in hearing aids to compensate for the user’s reduced dynamic range of hearing. In this project a hardware accelerator is developed for the purpose of dynamic range compression of digital audio. This accelerator will be implemented in a mixed-signal infrastructure.

The integration of the DMA350 into the nanosoc re-usable SoC architecture improves the transfer bandwidth on DMA channels within the SoC.  This project integrates the DMA 350 into nanosoc, validates the integration and functionality of the DMA 350, and compares the performance of the DMA 350 to the PL230, the first DMA controller integrated into nanosoc.

Autonomous mobile robots (AMRs) have been proven useful for smart factories and have the potential to revolutionize critical missions, such as disaster rescue. AMRs can perceive the environment, plan for assigned tasks, and act on the plan. Motion control is critical to the robot's action, which is accomplished through trajectory optimization to refine the robot's states using a physics model. However, the high computational complexity of trajectory optimization poses significant challenges for AMRs with limited power and computing resources.

Performing system-level verification on a System-on-Chip (SoC) design is crucial for ensuring the correct function and overall performance of the entire system, rather than individual components. This project is aimed at developing the necessary resources and design flow stages for the verification of the NanoSoC reference design.

With NanoSoC, there are multiple options for performing system-level verification. 

This project focuses on developing a plant growth monitoring system for space exploration missions using the ARM Cortex-M0 microcontroller core. The projects aim to develop a SOC based on ARM M0 core for interactive plant monitoring by interfacing AHB lite, GPIO, timers, and communication protocols such as UART, I2C, SPI, and co-processors.  This project also proposes two co-processors for interactive plant monitoring and control. One AI co-processor for classification and prediction of plant and environmental data.