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Certification & routing runtime

SparseDSP Relay — certification, routing, and fallback runtime

The runtime that certifies Vector’s output and guarantees a dense fallback.

What it is

Relay wraps Vector with a recall-safe verifier, exact-k routing, and a guaranteed dense fallback. Its certified output is k tuples — not the dense N-spectrum — so it also cuts the bytes that cross the PCIe interconnect on discrete GPUs (and the unified-memory path on GB10). That data-movement win applies to any downstream consumer that can operate on certified sparse tuples instead of the full dense spectrum. Callable via a C ABI + Python SDK.

How it works

Certify, route, fall back

Relay is the runtime around Vector. It decides when the sparse path is trustworthy, certifies the output against dense recall, and routes to the dense baseline whenever certification fails.

Recall-safe verifier

Confirms the sparse output matches dense top-k recall on the same seeds and the same top-k target before it is trusted. Certification is the gate, not an afterthought.

Exact-k routing

Dispatches each call to the sparse path only where it is measured iso-correct, and routes everything else to the dense baseline.

Guaranteed dense fallback

When certification fails — high dynamic range, large k, out-of-envelope — Relay falls back to dense cuFFT, which stays recall-authoritative. No silent overclaim.

Sparse-output data movement

Because the certified payload is k tuples rather than the dense N-spectrum, sparse-aware consumers move far less data across the interconnect. The benefit requires sparse-tuple-compatible consumers.

The data-movement win

Measured

Because the certified payload is k tuples instead of the dense N-spectrum, sparse-aware consumers move far less data across the interconnect.

4–5×
faster end-to-end
vs a fair pinned dense baseline
16–128×
fewer input bytes
sparse producer, structural
iso-correct
vs dense cuFFT + top-k
same seeds, same top-k target
k ≪ N
less data over the interconnect
certified payload, sparse-aware consumers
RTX + GB10
measured on NVIDIA GPUs
NVIDIA RTX 5070 Ti and GB10 / Spark

Routing policy

Where Relay routes sparse, and where it falls back

Relay routes to the sparse path only where it is measured iso-correct. Everywhere else it falls back to dense cuFFT, which stays recall-authoritative.

RegimeStatusPathClaim
Clean / on-grid, k ≤ 300, N ≤ 4Msupportedsparsemeasured iso-correct
Noisy AWGN, bounded dynamic rangesupported when gates passsparse + certificationreview gate: recall ≥ 0.97, precision ≥ 0.99, no p95 regression
Off-grid (0.25 bin)supportedsparsemeasured, bounded
High dynamic rangedense-betterfallbackno sparse claim
k ≥ 500dense-better / opendense fallbackno sparse claim (GPU device-resident path)
N = 8M, k = 300openfallback or caveatnot headlined

Application fit

The broader sparse-output pattern

Relay generalizes a runtime pattern: emit certified k-sized candidate tuples when the sparse path is valid, and route to the dense path when certification fails. Many edge workloads process large sensor, signal, telemetry, or memory-state streams where the useful output is a small candidate set. These are application-fit examples, not measured product claims.

AI-RAN / 5G / 6G

Sparse candidates for sync, random access, pilots, interference, beam and sensing, and telemetry.

Robotics / sensors

Sparse events and regions of interest from high-rate sensor streams.

Industrial edge

Fault frequencies, harmonics, anomalies, and equipment-health events.

AI runtimes

Sparse candidate selection: active pages, MoE router top-k (which experts fire), and retrieval candidates.

Guardrails

Not claimed

  • Not a universal cuFFT replacement.
  • Not a dense-spectrum FFT win.
  • Not controller-side / PIM hardware validation.
  • Not a high-dynamic-range sparse win.
  • Not a k ≥ 500 sparse win on the GPU device-resident path (the CPU sqrtn lane does win at k ≥ 500).
  • Not real-data precision 1.0; real-data precision is signal-bound.
  • Benefit requires sparse-tuple-compatible consumers; not every downstream consumer benefits.
  • The claim is sparse-output path materialization / transfer reduction, not that the original signal never exists.
  • Dense fallback stays authoritative when certification fails.

Relay certifies it. SparseDSP Vector computes it.

See the operator layer that produces the certified sparse output Relay verifies — or request an evaluation packet.