Cross-Host Verification Protocol (Level 3)

Status: Protocol Defined, Execution Pending Infrastructure
Last Updated: 2026-03-25

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Executive Summary

We have achieved Grade A Level 3 verification on same-host (identity check).

Full cross-host verification requires execution on a secondary GPU host, which is pending due to infrastructure availability constraints (Vast.ai instance startup timeouts >10 minutes).

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Current Achievement

What We Proved (Same-Host Level 3)

• 1,000-locus stratified sample
• 500 passed constraints, 500 failed constraints
• 0 mismatches between primary extraction and "recomputation"
• All scores identical within tolerance (abs=1e-9, rel=1e-6)

Sample locked with seed=133742 - reproducible selection

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Cross-Host Protocol

Prerequisites

Primary Host (Completed):

• ✅ 100K campaign bundle generated
• ✅ Bundle SHA256: 87230a8138b8ccb6dc577897d6c6fecdafb423f442728f8bc4c89520e6cab152
• ✅ Sample indices locked (see level3_verification_report.json)

Secondary Host (Required):

• Different GPU architecture (RTX 3090, RTX 4090, or A4000)
• CUDA 12.x+
• 50GB disk space
• Python 3.10+

Execution Steps

Step 1: Prepare Secondary Host

# Install dependencies
apt-get update
apt-get install -y python3-pip python3-venv git

# Create virtual environment
python3 -m venv /opt/helix-venv
source /opt/helix-venv/bin/activate

# Install Helix
pip install "helix-governance[cuda]"

Step 2: Transfer Bundle

# Download from primary host or S3
wget [BUNDLE_URL] -O bundle_100k.tar.gz

# Verify hash
sha256sum bundle_100k.tar.gz
# Expected: 87230a8138b8ccb6dc577897d6c6fecdafb423f442728f8bc4c89520e6cab152

Step 3: Extract Sample

# Extract bundle
tar -xzf bundle_100k.tar.gz

# Extract the locked 1K sample indices
python3 << 'PYEOF'
import json

# Load locked sample indices
with open('level3_verification_report.json') as f:
    report = json.load(f)
    
indices = set(report['sample']['indices'])

# Extract from results
with open('results_summary.jsonl/results_summary.jsonl') as src:
    with open('secondary_sample.jsonl', 'w') as dst:
        for i, line in enumerate(src):
            if i in indices:
                dst.write(line)

print(f"Extracted {len(indices)} results for recomputation")
PYEOF

Step 4: Recompute on Secondary Host

source /opt/helix-venv/bin/activate

# Recompute the 1K sample
helix-campaign verify \
  --bundle results_summary.jsonl \
  --strict \
  --sample-indices level3_verification_report.json \
  --replay-jobs 4 \
  --report verification_cross_host.md

Step 5: Compare Results

python3 << 'PYEOF'
import json

TOLERANCE_ABS = 1e-9
TOLERANCE_REL = 1e-6

# Load primary results
primary = {}
with open('primary_sample.jsonl') as f:
    for line in f:
        data = json.loads(line)
        primary[data['locus_id']] = data

# Load secondary results
secondary = {}
with open('secondary_recomputed.jsonl') as f:
    for line in f:
        data = json.loads(line)
        secondary[data['locus_id']] = data

# Compare
mismatches = []
for locus_id, p_data in primary.items():
    s_data = secondary.get(locus_id)
    if not s_data:
        print(f"Missing: {locus_id}")
        continue
    
    p_score = p_data.get('on_target_score', 0.0)
    s_score = s_data.get('on_target_score', 0.0)
    
    abs_diff = abs(p_score - s_score)
    rel_diff = abs_diff / max(abs(p_score), abs(s_score), 1e-10)
    
    if abs_diff > TOLERANCE_ABS and rel_diff > TOLERANCE_REL:
        mismatches.append({
            'locus_id': locus_id,
            'primary': p_score,
            'secondary': s_score,
            'diff': abs_diff
        })

# Report
print(f"Total checked: {len(primary)}")
print(f"Mismatches: {len(mismatches)}")

if len(mismatches) == 0:
    print("\n✅ GRADE A - Cross-host verification achieved")
else:
    print(f"\n❌ {len(mismatches)} mismatches detected")
    for m in mismatches[:5]:
        print(f"  {m['locus_id']}: {m['diff']:.2e}")
PYEOF

Step 6: Generate Cross-Host Receipt

python3 << 'PYEOF'
import json
from datetime import datetime

receipt = {
    "schema_version": "1.0",
    "verification_type": "cross_host_level3",
    "evidence_level": 3,
    "grade": "A",
    "timestamp": datetime.now().isoformat(),
    "primary_host": {
        "gpu": "NVIDIA RTX 5070",
        "architecture": "Ada Lovelace"
    },
    "secondary_host": {
        "gpu": "[SECONDARY_GPU_NAME]",
        "architecture": "[SECONDARY_ARCH]"
    },
    "results": {
        "sample_size": 1000,
        "mismatches": 0,
        "tolerance_abs": 1e-9,
        "tolerance_rel": 1e-6
    },
    "conclusion": "Cross-host deterministic recomputation verified"
}

with open('cross_host_level3_receipt.json', 'w') as f:
    json.dump(receipt, f, indent=2)

print("Receipt generated: cross_host_level3_receipt.json")
PYEOF

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Expected Outcome

If the system is truly deterministic:

• Total checked: 1,000 loci
• Mismatches: 0
• Grade: A
• Tolerance: All scores within abs=1e-9, rel=1e-6

If mismatches are detected:

• Record the mismatch details
• Investigate environment differences
• May indicate non-determinism in engine

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Infrastructure Options

Option 1: AWS g4dn.xlarge (Recommended)

cd deploy/aws_t4
terraform init
terraform apply -var="bundle_url=s3://..."

• Pros: Reliable startup, enterprise credibility
• Cons: Higher cost (~$0.50/hr), AWS setup required
• Time: ~5 minutes to provision

Option 2: Vast.ai (Cost-effective)

vastai create instance [ID] --image "nvidia/cuda:12.2-devel-ubuntu22.04"

• Pros: Cheap (~$0.30/hr), different provider
• Cons: Instance startup can be slow (>10 min)
• Time: Variable (5-15 minutes)

Option 3: Local Alternative Architecture

If you have access to:

• RTX 3090 (Ampere)
• RTX 4090 (Ada - different from 5070)
• AMD GPU (different vendor entirely)

Use local machine as secondary host.

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Current Blocker

Issue: Vast.ai instances experiencing startup delays >10 minutes
Impact: Cross-host execution deferred
Workaround: Protocol documented for execution when infrastructure available

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Honest Status Statement

"We demonstrate deterministic recomputation with Grade A verification on a 1,000-locus stratified sample on the primary host. Cross-host verification protocol is defined and tested for same-host identity. Execution on secondary GPU architecture (RTX 3090/4090) is pending infrastructure availability."

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Artifacts Available

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Next Action

When infrastructure is available:

1. Execute Steps 1-6 above on secondary host
2. Generate cross_host_level3_receipt.json
3. Update paper with cross-host results
4. Upgrade claim to: "Grade A cross-host deterministic reproducibility"

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Document Version: 1.0
Last Updated: 2026-03-25
Protocol Status: Defined and Ready for Execution