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Competition 2025
Competition: Collaboration/Education
An Efficient Hardware-based Spike Train Repetition for Energy-constrained Spiking Neural Networks

Spiking Neural Networks (SNNs) require processing a large number of spikes to achieve high classification accuracy. However, this results in frequent memory accesses to fetch synaptic weights, which significantly increases energy dissipation in SNN systems. To address this challenge, we propose a unique technique called the Repetitive Spike Train (RST) method. By exploiting the temporal similarity of spike trains across time steps, RST minimizes redundant spike train updates and reduces memory read/write operations.

Competition 2025
Competition: Hardware Implementation
Aspen annotated die photo

Aspen: A 630 FPS Real-Time Posit-Based Unified Accelerator for Extended Reality Perception Workloads

Aspen is a unified accelerator for deep neural network (DNN)-based extended reality perception workloads. Aspen proposes a mixed-precision quantization scheme using the posit datatype to reduce memory usage while maintaining accuracy, a DNN accelerator for mixed-precision posit datatypes, and efficient data prefetching and data layout to minimize data reorganization. The Aspen system-on-chip has an Arm Cortex-M3 CPU, a mixed-precision posit-based DNN accelerator, and 4 megabytes of SRAM partitioned into eight 512 KB banks, connected through a 128-bit-wide interconnect.

Collaborative
Active Project

Indonesia Collaborative SoC Platform

This program is dedicated to the development of a System on Chip (SoC) platform, specifically designed to support learning and research activities within Indonesian academic institutions. The platform serves as an educational and research tool for students, lecturers, and researchers to gain hands-on experience in digital chip design.

Collaborative
Active Project
AHB Qspi architectural design
dwn @ soclabs

AHB eXcecute in Place (XiP) QSPI

The instruction memory in the first tape out of nanosoc was implemented using SRAM. The benefit was the read bandwidth from this memory was very fast, the downside was on a power-on-reset, all the code was erased as SRAM is volatile memory. An alternative use of non-volatile memory would benefit applications where  deployment of the ASIC does not allow, or simply time is not available for programming the SRAM after every power up. 

Reference Design
Active Project
soclabs nanosoc microcontroller framework - 2024
soclabs

nanosoc - baseline Cortex-M0 microcontroller SoC (2024 update)
A small SoC development framework to support easy integration and evaluation of academic developed research hardware such as a custom accelerators or signal processing sub-systems.
Reference Design
Active Project
TSRI Arm Cortex-M55 AIoT SoC Design Platform

TSRI Arm Cortex-M55 AIoT SoC Design Platform
 What is TSRI Arm Cortex-M55 AIoT SoC Design Platform?

The Arm Cortex-M55 AIoT SoC design platform is an AIoT subsystem that allows custom SoC designers to integrate their hardware circuits and embedded software for differentiation. The platform is developed by TSRI (Taiwan Semiconductor Research Institute) to support academic research on SoC design. It's built on the Arm Corstone-300 reference package, featuring the Cortex-M55 CPU and Ethos-U55 NPU.

Reference Design
Active Project
Imrpoved power domain structure for nanosoc
dwn @ soclabs

nanoSoC Low Power Implementation

As part of plans for continued development of nanoSoC one area that requires improvement is the power structure of system. The first iteration of nanoSoC contained 2 power domains: the accelerator domain and the remainder of the SoC. Both power domains were connected to external pins to allow connection to separate external voltage regulators and power measurement ICs, as implemented in the first version of the nanoSoC testboard.

Collaborative
Case Study
A53 simplified testbench
SoClabs

Arm Cortex-A53 processor

There is growing interest within the SoC Labs community for an Arm A-Class SoC that can support a full operating system, undertake more complex compute tasks and enable more complicated software directed research. The Cortex-A53 is Arm's most widely deployed 64-bit Armv8-A processor and can provide these capabilities with power efficiency. 

Collaborative
Request of Collaboration
High Capacity Memory Subsystem Development

This project aims to design and implement a high capacity memory subsystem for Arm A series processor based SoC designs.  The current focus of the project is the design and implementation of a Memory Controller for DDR4 memory. 

Collaborative
Request of Collaboration
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Use of the Synopsys HAPS® FPGA-based prototyping environment

The Synopsys HAPS® System adds additional capabilities to the FPGA-based prototyping environments SoC Labs can use to support projects. The HAPS® system provides a greater amount of logic resources supporting development of larger SoC designs. It can be used to support multiple projects simultaneously. It is used by many semiconductor companies, including arm for their CPU verification. This collaboration project will use the HAPS® system in SoC Labs projects and share with the community experience in utilising such systems.