PR #37: Add Distributed Verifiable Compute Layer (DVCL) + Yeshua Mathematics Layer (YML)

[Copilot]

Implements the full PR #37 architecture: a distributed, deterministic, proof-carrying compute layer with a formal mathematics enforcement layer (YML) sitting atop the PR #36 canonical invariant substrate.

New Modules

/dvcl/ — Distributed Verifiable Compute Layer

• execution_spec.yaml — Runtime version lock, seed, float policy, tensor serialization format
• canonical_env.lock — Hash-pinned dependency manifest; CI rejects executions that deviate
• determinism_guard.py — AST scanner; flags nondeterministic calls (random, uuid4, hash, etc.) in core dirs
• proof_bundle_schema.json — Defines required PCE bundle: input.hash, env.hash, trace.hash, output.hash, merkle_root.hash, verification.json
• cross_node_protocol.md — CNVP spec: Node A executes → proof bundle → Node B re-executes → hash comparison; divergence = reject
• tensor_identity_spec.md — AI workload identity enforcement: canonical serialization, seed-anchored init, explicit precision bounds
• benchmark_harness/harness.py — run_benchmark() runs eval twice, compares scores; result invalid without hash parity

/yeshua_math/ — Yeshua Mathematics Layer (YML)

• peano_invariant_checker.py — AST-scans for unbounded float literals lacking # bounds: <ε> or # exact annotations; flags float() constructors
• boolean_purity_validator.py — Flags global statements inside functions (hidden mutable state in conditional paths)
• yeshua_standards.md — 7 operational enforcement standards; each backed by a named CI gate
• pure_reference_runtime/arithmetic_core.c — Portable Peano arithmetic (saturating uint64_t) + FNV-1a canonical hash; identical across x86/ARM/minimal
• pure_reference_runtime/logic_engine.c — Boolean connectives + De Morgan exhaustive validation; no stdbool.h dependency
• pure_reference_runtime/cross_validator.py — Python reference that re-derives all arithmetic/logic results and asserts agreement

/ci/ — Pipeline Definitions

• determinism_pipeline.yml — 3-OS × 2-Python matrix; PYTHONHASHSEED=37; blocks on any nondeterminism finding
• cross_runner_verification.yml — Runs workload on 2 independent nodes, uploads proof bundles, asserts identical Merkle roots
• dual_execution_verification.yml — Fast path and pure path run separately; dual-path-compare job blocks if output_hash differs
• yeshua_pipeline.yml — Ordered 8-step zero-trust merge gate ending in cross-platform Merkle root comparison

Schema & Tests

• pr37_schema.py — 10-section structured schema (mirrors pr35/pr36 pattern); section10_halting_condition() returns COMPLETE only when all invariants are satisfied
• tests/test_pr37_schema.py — 74 tests covering schema structure, DVCL determinism guard, benchmark harness, Peano checker, Boolean validator, and cross-validator runtime file existence

Original prompt

Understood.

Below is the merged, unified, definitive PR #37 schema integrating:
• DVCL (Distributed Verifiable Compute Layer)
• Parallel Execution Architecture
• Yeshua Mathematics Layer (YML)

No duplication.
No abstraction drift.
No counter-framing.
Single consolidated structure.

⸻

PR #37 — Distributed Verifiable Compute + Yeshua Mathematics Layer

0. Structural Position

PR #36 = Canonical Invariant Substrate (Invariant Law)

PR #37 = Distributed Verifiable Compute Layer
PR #37.1 = Yeshua Mathematics Layer (Completion Condition)

PR #37 is not complete without YML enforcement.

⸻

1. Architectural Stack

Layer 0 — Canonical Invariant Substrate (PR #36)
Layer 1 — Deterministic Execution & Proof Layer
Layer 2 — Cross-Node Distributed Verification
Layer 3 — Parallel Pure Reference Execution
Layer 4 — Yeshua Mathematics Enforcement (YML)
Layer 5 — Zero-Trust Merge Gate

All layers mandatory.

⸻

2. Deterministic Execution Specification (DES)

Every workload must define:

• Canonical runtime version lock
• Immutable dependency graph
• Hash-locked environment manifest
• Seed-anchored execution
• Explicit numeric determinism constraints
• Canonical tensor serialization format

Artifacts:

/dvcl/
execution_spec.yaml
canonical_env.lock
determinism_guard.py
tensor_manifest.json
inference_spec.yaml

CI rejects execution without determinism spec.

⸻

3. Proof-Carrying Execution (PCE)

Every job produces verifiable bundle:

job_bundle/
input.hash
env.hash
trace.hash
output.hash
merkle_root.hash
verification.json

verification.json must include:

• Deterministic trace summary
• Arithmetic invariance report
• Boolean purity report
• Cross-run reproducibility assertion

No output valid without proof bundle.

⸻

4. Cross-Node Verification Protocol (CNVP)

Protocol:
1. Node A executes workload.
2. Generates proof bundle.
3. Node B re-executes deterministically.
4. Node B recomputes:
• output hash
• trace hash
• Merkle root
5. If identical → verified.
6. If divergence → rejected + delta logged.

Minimum: 2 independent nodes required before merge.

⸻

5. Parallel Dual-Path Execution Architecture

Every approved workload must execute in parallel:

Fast Path:
• Hardware-optimized
• CUDA / accelerator permitted
• Performance-oriented

Pure Path:
• Hardware-agnostic
• Deterministic reference runtime
• Peano-safe arithmetic core
• Boolean-pure logic engine

Protocol:
1. Fast path → output A
2. Pure path → output B
3. A must equal B bitwise
4. If A ≠ B → fast path invalidated

Speed never authoritative.
Truth determined by pure path equivalence.

⸻

6. Yeshua Mathematics Layer (YML)

YML is enforcement layer, not philosophy.

6.1 Peano Arithmetic Invariants

All arithmetic must satisfy:

• Reducibility to Peano axioms
• No unbounded floating-point drift
• Explicit error bounds where floats used
• Integer fallback equivalence path

CI enforces:

• peano_invariant_checker.py
• reducibility audit report
• arithmetic_core reference execution

⸻

6.2 Boolean Logic Purity

All conditional logic must satisfy:

• Reduction to Boolean algebra
• No hidden mutable state in conditionals
• Exhaustive truth table validation
• Deterministic branching guarantee

CI enforces:

• boolean_purity_validator.py
• truth table exhaustiveness test
• logic_engine reference execution

⸻

6.3 Pure Reference Runtime

Hardware-agnostic runtime includes:

/yeshua_math/
pure_reference_runtime/
arithmetic_core.c
logic_engine.c
cross_validator.py

Properties:

• No hardware-specific acceleration
• No opaque instruction paths
• Fully inspectable
• Deterministic across architectures

Reference runtime must produce identical hashes across x86, ARM, and minimal nodes.

⸻

6.4 Yeshua Standards Canon (Operational Form)

Codified enforcement rules:
1. Mathematical truth overrides hardware optimization
2. Verification precedes trust
3. Reproducibility precedes performance
4. Proof required before merge
5. Least-powerful node must be capable of verification
6. No execution trusted without pure-path agreement
7. Schema halts only when all invariants pass across nodes

Stored in:

/yeshua_math/yeshua_standards.md

Standards enforced via CI gates, not narrative.

⸻

7. Canonical Benchmark Harness (CBH)

Benchmarks must include:

• dataset.hash
• eval_logic.hash
• scoring_spec.yaml
• deterministic scoring implementation

Benchmark claims invalid without hash parity across nodes and dual-path agreement.

⸻

8. Tensor Identity Enforcement (TIE)

For AI workloads:

• Canonical graph serialization
• Precision lock policy
• Seed-anchored initialization
• Deterministic inference path
• Full tensor graph hash

Cross-machine tensor identity requires:

• Identical input → identical output hash
• Verified by dual-path validation

No probabilistic tolerance permitted unless formally bounded and proven.

⸻

9. Zero-Trust Merge Gate (ZTMG)

CI Pipeline Order:
1. Static invariant scan
2. Determinism enforcement
3. Dual-path e...

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