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SparkProof v0.1.0

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@ai-hpc ai-hpc released this 11 Jul 20:05
v0.1.0
eeaaa56

First public release of SparkProof — Blackwell GPU-attested Triton dataset generation for SparkDistill.

Highlights

  • sparkproof-2 bundles with GPU CC attestation (NRAS), Merkle root over verified samples, and CPU-verifiable manifests
  • Five training sources (A–E): API docs, mutations, Torch→Triton translation, self-evolution, failure-mining
  • TritonBench eval quarantine — decontamination blocks eval-origin prompts/AST structures from training data
  • Release gate before HF publish (provenance + decontamination + attestation)
  • Identity-free diverse sampling (run-seed, stratified prompt selection, novelty gate)
  • Reference timing diagnostics (isolated PyTorch baseline; candidate timing is diagnostic-only, not ranking credit)
  • HF publish uploads dataset rows + proof/ artifacts for validator re-verification
  • Gateways: OpenRouter and yunwu with pinned Fable 5 + GPT 5.6 Sol at xhigh

CI test results (2026-07-11)

check result
pytest 238 passed, 9 skipped
ruff All checks passed
Python 3.12.3
pytest 9.0.3
Commit eeaaa56

Skipped (GPU-gated — require Blackwell + SPARKPROOF_RUN_GPU_TESTS=1)

  • tests/test_reference_bench_gpu.py — 3 tests (Sigmoid, Matmul, LayerNorm live reference bench)
  • tests/test_reference_kernels_gpu.py — 6 tests (reference kernel integration)

Production validation — Targon SN4 · RTX PRO 6000 Blackwell CC

All production runs below executed on a NVIDIA RTX PRO 6000 Blackwell Server Edition confidential-computing VM provisioned through Targon (Bittensor Subnet 4 / SN4).

environment value
GPU NVIDIA RTX PRO 6000 Blackwell Server Edition (SM 12.0, 96 GB)
Driver 595.71.05
Triton 3.7.1
SparkProof generator 0.3.0
Manifest sparkproof-2
CC attestation NRAS (passed: true, nonce_verified: true)

Smoke test — gittensor-model-hub/sparkproof-triton-v0

check result
Verified rows 2
Release gate passed
GPU attestation present under proof/
SparkDistill eval.dataset_verify verified=true

Dataset: gittensor-model-hub/sparkproof-triton-v0

Miner production run — miner-25-20260711 (speedy00)

End-to-end pipeline on the CC VM: generate → compile/execute → attest → release gate → publish → CPU re-verify.

check result
Bundle bundles/miner-25-20260711
Prompts processed 26 (proved: 25/26)
Verified rows published 25 (22 silver, 3 repair)
Novel verified rows 17 (8 near-duplicate task IDs deduped at aggregation)
Gateway yunwu (claude-fable-5, gpt-5.6-sol, xhigh)
Merkle root 8513d35bf173f30439197a438f9906d5eddc11bc8069890edf2503951e4ebc6f
trajectories_sha256 d96cbe4d43ad5e44bdee45633b41b330cb44f90d7aba35ee730d83d4639a80e9
sparkproof-verify (offline) verified=true, gpu_attested=true, issues=[]
HF publish speedy00/sparkproof-miner-25-v1

Resume note: the 25th row was added with --resume on the same run_seed, so only one new prompt was regenerated after the initial 24-row run.

SparkDistill registry gate (merged)

Registry PR #22 merged with label dataset:xs.

CI re-verified the HF proof/ bundle, then aggregated into the canonical mining dataset:

check result
Registry entry speedy00 → speedy00/sparkproof-miner-25-v1
Canonical mining dataset gittensor-model-hub/sparkproof-mining
Rows after cross-miner dedupe 17 (mix_manifest.json provenance retained)
Merge blocked unless publish succeeds yes

First finetune pilot on canonical mining data (same CC VM)

Pilot Axolotl LoRA run on the published mining mix (not a frontier submission — sanity check that verified HF data trains end-to-end):

check result
Student Qwen/Qwen3.5-4B (LoRA r=64, bf16)
Training rows 17 (messages format from sparkproof-mining)
Recipe recipes/qwen3.5-4b-phase1/sft-mining.yaml
Trainable params 84.9M / 4.62B (1.84%)
Initial eval (epoch 0) eval_loss=0.7767, eval_ppl=2.174
VRAM ~12.1 GiB active

This pilot was running at release time; full 5-epoch checkpoint output lands under SparkDistill/outputs/qwen3.5-4b-mining/.

Quick start

git clone https://github.com/gittensor-model-hub/SparkProof.git
cd SparkProof && cp .env.example .env
scripts/install.sh
scripts/run_triton_pipeline.sh --limit 25 --release-gate --publish <user>/sparkproof-triton-v1

Requirements

  • Python >= 3.12
  • NVIDIA RTX PRO 6000 Blackwell CC VM for production proving (Targon SN4 or equivalent)
  • Sibling SparkDistill repo (for decontamination corpus, registry gate, and SFT formatting)
Assets 2
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