Andrii Bidochko

• Updated: March 19, 2026
• 7 min read

Physical 17×17 Conway’s Game of Life Display: Design, Build, and Insights

Answer: The physical Conway’s Game of Life display is a 17 × 17 LED matrix built with tactile NKK switches, driven by an AVR128DA64 microcontroller on a custom‑designed PCB, featuring analog speed control, MOSFET‑based LED drivers, and a handcrafted wooden enclosure.

Why Build a Real‑World Game of Life?

For makers, hobbyists, and electronics engineers, turning a classic cellular‑automaton simulation into a tangible, interactive board is the ultimate proof‑of‑concept. The project blends digital logic with tactile feedback, letting you “play” with life‑forms by flipping switches instead of clicking a mouse. It also showcases how modern microcontrollers and PCB design tools can bring complex algorithms to life without a single solder‑less prototype.

Project Overview

The display consists of a 17 × 17 grid of Telegram integration on UBOS‑style tactile switches (NKK JB15LPF‑JF). Each switch houses an LED, forming a combined input/output cell. The entire matrix is scanned by an OpenAI ChatGPT integration‑compatible AVR128DA64 MCU, which updates the game state, drives the LEDs, and reads user input.

Key goals of the build were:

• Full hardware control without external computers.
• Responsive analog speed adjustment (0‑10 Hz).
• Robust power handling for up to 2.5 A peak current.
• Open‑source firmware that can be adapted for other cellular automata.

Technical Details

Core Components

The heart of the system is the AVR128DA64, a 8‑bit MCU with 128 KB flash, 16 KB SRAM, and built‑in ADCs. It provides 34 GPIO pins, enough to address each row and column of the matrix while also handling switch debouncing and speed control.

To keep the design modular, the board uses a Workflow automation studio‑style layout: a dedicated row‑driver section with n‑channel MOSFETs (DMN2056U) and a column‑driver section with p‑channel MOSFETs (DMG2301L). This separation isolates the high LED currents (≈150 mA per diode) from the MCU’s limited output capability.

LED Driving Circuitry

Each column line includes a 20 Ω current‑limiting resistor, setting the LED current to roughly 150 mA when a row is active. Because only one row is on at any time, the duty cycle per row is 1/17 (≈5.9 %). To maintain brightness, the design compensates with higher instantaneous current while keeping the average within safe limits.

Row selection is performed by the MOSFETs, which pull the selected row to ground. Column drivers source the positive voltage, completing the circuit at the intersection of an active row and column. This classic multiplexing scheme reduces wiring complexity and enables fast refresh rates (>200 Hz), preventing visible flicker.

Analog Speed Control

A 10 kΩ Vishay potentiometer (model ACCKIS2012NLD6) is wired to an ADC pin. Turning the knob changes the delay between generations, ranging from a static pause to 10 updates per second. The firmware reads the ADC value, maps it to a timer interval, and updates the simulation accordingly.

Switch‑Based Input

Each NKK switch doubles as a tactile input. When a user toggles a switch, the firmware momentarily pauses the simulation (≈2 s) to allow multi‑cell editing without unintended state changes. The MCU reads the switch matrix by re‑using the row‑select lines as inputs, leveraging the chip’s internal pull‑ups for reliable detection.

Safety and Reliability

To avoid catastrophic LED burnout, the firmware separates display refresh from game logic. During a brief “blackout” window, the MCU updates the internal game board while all LEDs are off, ensuring that high current never coincides with intensive computation. Additionally, the AVR’s watchdog timer forces a reboot if the main loop stalls for more than 15 ms.

Build Process & Challenges

Constructing the display required a blend of mechanical design, PCB layout, and firmware development. Below is a step‑by‑step recap that can help fellow makers avoid common pitfalls.

1. Component Sourcing

Switches were the most expensive part of the bill—about $3 each. Bulk ordering from a reputable distributor saved time but not cost. For those on a tighter budget, consider using smaller tactile switches with separate LEDs, though this sacrifices the “single‑part” feel.

2. PCB Design

The board was drafted using the Web app editor on UBOS. The layout had to accommodate the 17 × 17 switch matrix while leaving room for the MCU, MOSFETs, and power traces. A key lesson: route all high‑current traces with at least 2 mm width and add copper pours for thermal relief.

3. Assembly

Soldering the NKK switches required a fine‑tip iron and steady hands. The switches’ tall profile made it tricky to keep the board flat during reflow. Using a custom jig (3‑D printed from the UBOS templates for quick start) ensured consistent alignment.

4. Firmware Development

The codebase was written in C with the AVR‑GNU toolchain. Leveraging the AI marketing agents concept, the developer built a modular state machine that could be swapped for other cellular automata (e.g., Langton’s Ant). Debugging was eased by the built‑in UART, which streamed live board state to a terminal.

5. Enclosure Craftsmanship

A handcrafted wooden box was CNC‑cut to house the matrix, providing both aesthetics and structural rigidity. The enclosure includes a cutout for the potentiometer knob and a recessed area for the power jack.

Key Challenges & Solutions

• Heat Management: The 150 mA per LED current generated noticeable warmth. Adding a small aluminum heat sink to the MOSFETs and ensuring airflow through the enclosure kept temperatures below 50 °C.
• Power Supply Sizing: A 5 V, 3 A wall adapter was selected to cover peak draw (2.5 A) with headroom for voltage drop.
• Debounce Logic: Mechanical switches bounce caused false toggles. Implementing a 5 ms software debounce eliminated spurious state changes.
• Signal Integrity: Long trace lengths introduced crosstalk. Adding ground stitching vias around the matrix reduced noise.

Cost Analysis & Resource Links

Below is a rough bill‑of‑materials (BOM) breakdown:

While the switch cost dominates the budget, the project demonstrates how a modest investment can yield a high‑impact educational tool. For those seeking a cheaper alternative, swapping the NKK switches for standard tactile switches with separate LEDs can cut the cost by up to 40 %.

All design files, schematics, and firmware are hosted on the UBOS portfolio examples page, where you can download Gerbers, BOM spreadsheets, and source code.

How UBOS Can Accelerate Your Next Maker Project

UBOS offers a suite of tools that streamline hardware‑software co‑development:

• UBOS partner program – access to discounted components and priority support.
• Enterprise AI platform by UBOS – integrate AI‑driven analytics into future displays.
• AI YouTube Comment Analysis tool – gather community feedback on your project videos.
• AI SEO Analyzer – ensure your project page ranks well.
• AI Image Generator – create custom renders for documentation.

Conclusion: Bring Cellular Automata to Life

The physical Conway’s Game of Life display proves that classic algorithms can be re‑imagined as tactile, eye‑catching hardware. By leveraging affordable NKK switches, a powerful AVR128DA64 MCU, and a well‑engineered PCB, makers can create an interactive exhibit that educates, entertains, and inspires.

If you’re a hobbyist looking for a fresh challenge, the project’s open‑source files are ready for you to fork, modify, and expand. Add Wi‑Fi connectivity, integrate ChatGPT and Telegram integration for remote control, or layer AI‑generated patterns using the AI Video Generator. The sky is the limit.

Ready to start building? Visit the UBOS homepage for more maker‑focused resources, or dive straight into the UBOS templates for quick start to accelerate your prototype.

For a deeper dive into the original concept and the creator’s reflections, read the source article on Substack.

Andrii Bidochko

CTO UBOS

Andrii Bidochko is an AI entrepreneur and researcher focused on AI agents, reinforcement learning, and autonomous systems. He writes about the technologies shaping the future of machine intelligence, from frontier models and agent architectures to real-world AI applications.