Announcing Zero to Silicon: Build Your Own Spiking Digital Hardware

We are thrilled to announce the development of 'Zero to Silicon', a summer school series designed to take you from zero hardware background to simulating a digital neuromorphic chip. We need volunteers to make it happen!

Hardware can often feel like an impenetrable black box, especially for students, software engineers, and researchers who spend their days entirely in Python. But to truly unlock the energy-efficiency and capabilities of neuromorphic computing, we need more people who understand the entire stack—from biology down to the silicon.

That is why Open Neuromorphic is thrilled to announce that we are beginning development on a massive new community education program: Zero to Silicon (ZTS).

Designed as a free, open-source “Summer School” virtual workshop series, Zero to Silicon will take participants with absolutely no hardware background through a cumulative pipeline: Biological Fundamentals $\rightarrow$ Software Simulation $\rightarrow$ Hardware Deployment.

The Vision: An Artifact-Driven Curriculum

We aren’t just hosting a string of disjointed talks. Zero to Silicon is designed as a cohesive curriculum where every week builds directly on the last.

The format is hybrid: each event opens with a 45-60 minute live lecture streamed via YouTube and LinkedIn, followed immediately by a week-long, hands-on hackathon challenge hosted in our Discord.

Most importantly, the series relies on an Artifact Chain. The homework you produce one week becomes the raw material for the next week’s session. By the end of the series, your artifacts will chain together into a complete working system.

The Aspirational Outline

Here is a look at the curriculum we are striving to build:

  1. Neuroscience Foundations for Neuromorphic Computation: Building the biological vocabulary. We’ll explore what a neuron is as a dynamical system and sketch out the Leaky Integrate-and-Fire (LIF) model on paper.
  2. Prototyping an LIF Neuron in Python: Translating our sketch into code. We will build a raw Python class from scratch to simulate membrane potential, leak, and spike thresholds, and explore tools like snnTorch.
  3. Fundamentals of Digital Logic: The EE 101 crash course. We will translate our Python operations (addition, subtraction, leakage) into digital logic gates, multiplexers, and registers.
  4. Designing the Digital Spiking Chip: Translating our logic map into a formal hardware specification and block diagram blueprint.
  5. Intro to Verilog & Hardware Description: Learning to “speak hardware” by implementing our chip blueprint into synthesizable Verilog modules.
  6. Simulating the Spiking Neuron Chip with Verilator: Setting up a C++ testbench, visualizing waveforms, and ultimately proving that our hardware chip’s spike rate matches our original Python model.

All materials, recordings, and code templates will be released as Open Educational Resources (OER) under a CC-BY-SA license, free for the world to use, share, and cite.

We Need Your Help: Call for Volunteers

This outline is our North Star, but it is entirely aspirational.

As a grassroots, open-source community, the final scope, depth, and pacing of the Zero to Silicon program will scale appropriately with the volunteers who step up to support us. To make this ambitious Summer School a reality, we need passionate individuals to join the team.

We are actively recruiting for three specific roles:

1. Speakers & Subject Matter Experts

Are you an expert in computational neuroscience, digital logic, or hardware description languages? We are looking for engaging speakers to deliver the 45-60 minute live lectures. You will be provided with a “Collaboration Brief” that outlines exactly what foundational concepts need to be covered to ensure your lecture perfectly sets up the students for their weekly Discord coding challenge.

2. Teaching Assistants (Community Guides)

If we have hundreds of learners writing Python and Verilog, we are going to need help reviewing it! We are looking for intermediate-to-advanced community members to act as official ONM Teaching Assistants. You don’t need to prepare lectures; you just need to be present in the Discord during the offline component to help learners troubleshoot broken code, explain concepts, and guide them through the exercises. This is a fantastic way to build your resume and solidify your own knowledge.

3. Curriculum & Material Developers

We need volunteers to help us flesh out the backend of the course. If you love writing documentation, creating coding challenges, or drafting educational slide decks, we need your help building the problem statements, Verilog templates, and reference code that the speakers and TAs will utilize.

How to Get Involved

If you are excited about making neuromorphic hardware accessible to everyone and want to help us build this program, we want to hear from you today!

  • Join the Conversation: Hop into the Open Neuromorphic Discord and drop a message in the #proposals-contributions channel.
  • Email Us: Reach out directly at contact@open-neuromorphic.org with your background and how you’d like to help.
  • Check Open Roles: Keep an eye on our <a href="{{ with site.GetPage “volunteer-opportunities” }}{{ .RelPermalink }}{{ end }}">Volunteer Opportunities page as we post specific needs for the program.

Zero to Silicon is a massive undertaking, but by working together, we can bridge the gap between software and hardware and accelerate the entire neuromorphic field. Let’s build something amazing.

About the Authors

Effiong Blessing

Effiong Blessing

Secretary of Open Neuromorphic and leader within Project Phaser. Focused on communications, community engagement, and educational pipelines.
Justin Riddiough

Justin Riddiough

Strategic digital solutions partner and open-source advocate. As Vice-Chair of the ONM Executive Committee, Justin focuses on building robust digital infrastructure and fostering community growth.
Alexandre Marcireau

Alexandre Marcireau

Software developer in neuromorphic computing, recognized for his contributions to the Faery event processing library for event-based camera data.

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