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Digital twins & sim-to-real

What does it cost to send only a fraction of the outer update, and does error feedback help?

research/sparse-outer-sync

Sending a fraction p of the outer update: unbiased rescaling costs 1/p in noise floor, error feedback costs only 1+αs(1/p−1) at small steps but caps contraction at √(1−p); exact closed form, stability limits, horizon losses.

12 tests

What it found

Each worker transmits a random fraction p of its pseudo-gradient. Rescaling the subset (unbiased) inflates the stationary noise floor by exactly 1/p. Adding a per-worker error-feedback memory gives an exact closed form from a four-dimensional second-moment recursion and costs only 1 + αs(1/p − 1) at small steps, for any number of workers, because the virtual iterate follows uncompressed SGD. The price is speed: the mean dynamics have determinant 1 − p, so the contraction cannot beat √(1 − p) per round; over a 400-round horizon error feedback reaches 0.39, 0.24 and 0.17 of the unbiased loss at p = 0.25, 0.1, 0.03, and the advantage disappears when the horizon is shorter than about 1/p. Stylised: diagonal quadratics, Bernoulli masks, no top-k.

A figure from its own output

Figure produced by research/sparse-outer-sync: small_step_penalty
sparse-outer-sync/experiments/small_step_penalty.svg, written by the project's own experiment code.

Paper, code and results

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Produced with AI assistance (Claude). Results are from the code in this repository and are simulated or stylised unless the abstract says otherwise; nothing here implies affiliation with or endorsement by any lab, researcher or company cited. MIT licensed.