The substrate beneath every module

One runtime that holds the whole problem.

Constellation is not a collection of tools that pass files to each other. It is a single distributed runtime, every simulation, every observation, every closed-loop run shares the same data plane, the same provenance, and the same compute budget.

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Shared Substrate

Three doors into the same room.

Nova-Sim, Nova-Obs, and Nova-Loop are interfaces, not silos. Whatever one module writes, the others can read, with full lineage, no export, no copy.

// data plane

One asset store

Content-addressed, immutable, and global. A calibrated frame produced in Nova-Obs is the exact same object a Nova-Sim experiment graph consumes, referenced by hash, never duplicated.

addressing: BLAKE3 tiers: hot / warm / cold dedup: cluster-wide
// control plane

One scheduler

All work, kernels, pipelines, hypothesis loops, competes in a single placement engine that understands locality, precision, and your remaining budget.

placement: locality-aware preemption: checkpointed fairness: per-grant
// trust plane

One provenance graph

Every artifact records what produced it, with which inputs, under which code. Reproducing a four-year-old result is a query, not an archaeology project.

model: W3C-PROV signing: per-run keys replay: deterministic
Provenance & Compute Budget

Compute you can account for.

A grant is a finite thing. Constellation treats compute as a metered resource attached to a PI and a funding line, so the question "what did this result cost?" always has an exact answer.

STEP 01
Allocate

A budget is bound to a PI and a grant. Quotas in node-hours, fp64-hours, and storage are set per funding line.

STEP 02
Meter

Every run debits the budget in real time. Kernels report exact device occupancy; storage bills against the content-addressed footprint.

STEP 03
Attribute

The provenance graph ties each artifact to the budget that paid for it. Cost rolls up by experiment, by paper, by grant.

STEP 04
Audit

Export a signed cost-and-lineage report for a reviewer or a funding body. Reproducible down to the kernel.

Go deeper

See how the modules talk.

The platform is the floor everything stands on. The next layer up is the three modules, and how each one becomes a face of the same runtime.