Large active matrices are usually controlled as collections of independent channels. Flow carries the active control state through the complete field instead. The worked example below is the native Rust controller produced by that architecture: it authorizes, checks, routes, and records each exact control action locally, without putting a cloud service inside the control loop.
Time to complete the same worked control cycle. Less is better.
The compiled controller image travels with the edge runtime. Once deployed, sensing, authorization, repair, projection, recursive action, and receipt generation execute locally. A network may deliver a new approved image or collect receipts, but the running controller does not require a live connection.
Execution dependencies: Rust standard library only. No Python, NumPy, network service, cloud runtime, or third-party crate.
| software property | delivered result |
|---|---|
| registered active-matrix fixture | 256×256; every one of 65,536 addresses encoded, decoded, and checked |
| address representation | 26 compatible coordinate words plus one action word |
| controller implementation | standalone native Rust executable |
| edge image | 16,513 bytes |
| command packet | 85 bytes |
| fixed control state | 936 bytes |
| measured process working set | 3.84 MiB on the registered host fixture |
| recursion replay | depths 1–81 byte-identical to the independent reference |
| execution dependencies | standalone Rust; no Python, NumPy, network, cloud, or third-party crate |
The Flow scaling benchmark establishes that recursive full-field transport does not turn a larger address space into a larger control scan. This microfluidic example establishes the other half of the product claim: the same architecture has been reduced to a small, fast, native controller that runs without a cloud connection. The 256×256 fixture is the exhaustive correctness test, not the limit of the logical field.