Build The Architecture In Order
The main sequence moves from first principles into a working, spatially reconfigurable machine:
- Cartilage: the complete one-chapter-at-a-time learning path
- Cartilage Core: Browser Fabric, RTL, and a 252-Bit Install
- Cartilage Core public source repository
- Cartilage 2026: Child-Owned Reconfiguration Ports
- Cartilage Visual Language
- Runtime Instantiation In Adjacent Space
- Cellular Automata Machines, 2019-2021
The sequence connects implementation, visual lineage, body roles, nested instantiation, and the cellular-automata work that supplied Cartilage with its spatial vocabulary.
Follow A Circuit Through Space And Time
These five pages focus on installed computation, visible state, long reconfiguration timelines, spatial composition, and the signal surface that exposes MUX behavior.
- Cartilage Verified Ripple2 Adder
- Cartilage PC Stepper Islands
- Cartilage Full-Adder Islands
- Cartilage QuadFlow 525,568-Cycle Timeline
- Cartilage MUX Lanes Signal Surface — visible input, output, and edge behavior across the selector lanes.
One Architecture, Several Views
Cartilage Core provides the compact browser implementation, matching RTL, and exact 252-bit circuit installation. The QuadFlow and QFG pages record earlier large-field machines and their own run paths.
The run pages expose frame counts, source names, output lanes, and expected results. The spatial-design pages reveal mapping vocabulary, cell roles, geometry, and routing intent. Together, they show both what a configuration computes and how Cartilage places that computation in a field.
Use the source-level views to reproduce a mechanism and the visual views to design the next region, route, or body role.
Choose The View That Advances The Work
Run Cartilage Core for the compact mechanism, RTL, and exact circuit image. Continue through the 2026 port architecture, visual-language decoder, runtime instantiation, and cellular-automata roots to understand the system’s evolution. Open a specific run when its circuit, timeline, or placement pattern matches the problem in front of you.