Use the Tabs below to find information on community projects. Project pages have links to the 'technology' and 'design flow' stages used and ways you can comment on or join a project.
- Projects are key to community hardware design
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As a community hardware design activity we form our collaborations around shared design actions making Projects a core of the SoC Labs community. Projects help us share and reuse hardware and software developments around core Arm IP to help us in our research goals.
- A project, takes technology and uses a design flow to make a SoC.
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A project has a timeframe and uses the two other significant aspects of a SoC development, the selection of technology or IP blocks that make up the SoC and the design flow that is followed from specification through to final instantiation of a system. Any System On Chip usually involves the use of pre-existing IP blocks. A project team can select IP from the technology section of the site during the first stage of a design flow, Architectural Design. Later stages in the design flow support the creation of the novel aspects of the SoC design.
- Projects have a type, either active, complete (case study) or being formulated (request for collaboration)
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Sharing information on projects much earlier than traditional academic collaboration is encouraged. Historically knowledge sharing has been at the end of the research activity, with published papers and results. As well as write up of finished projects ("case study"), ongoing projects under development ("projects") there are projects that are still being formulated ("request for collaboration") listed. We want to encourage people to engage with the project teams, for example, adding a comment to a specific project page or joining a project.
Latest Reference Design Projects
David Flynn
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.
CHI-SHI CHEN
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.
Daniel Newbrook
On-chip SRAM in ASICs can use a significant area, which equates to a significant cost. One solution is to make the memory off-chip. This project explores the use of Arm IP to create an SRAM chiplet design. The benefit is that standard memory chiplets can be fabricated at lower cost and used across multiple projects, miminising silicon area to the unique project needs.
Latest Collaborative Projects
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.
Trio Adiono
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.
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.
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.
Srimanth Tenneti
Latest Competition Projects
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.
The Anh Nguyen
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.
Project Overview:
Our innovative SoC design for precision agriculture revolutionizes field management by deploying a robust mesh network of sensor-based devices, capable of detailed monitoring and swift response to variations in soil health, erosion, drought, and pest activities. This system not only ensures reliability through its mesh architecture—eliminating single points of failure—but also incorporates diverse sensors for comprehensive data acquisition. It's engineered for energy efficiency to sustain operation throughout an entire crop season, significantly optimizing resource use and reducing waste.