🎮 Opt-In Community GPU Benchmark & Hardware Receipts Board (CUDA / ROCm / Apple MPS — Share Your Results!)

[xaviercallens]

🔥 Test Your GPU on the HiveMind Season 6/7 Stack (If Interested & Possible)

If you have a consumer GPU (NVIDIA GeForce RTX 20/30/40/50-series 6 GB–24 GB, AMD Radeon RX 6000/7000 via ROCm, or Apple Silicon M1/M2/M3/M4 via MPS, or even a CPU-only dev machine) and want to help benchmark hardware compatibility across the developer community, we have added a safe, opt-in < 1.5 GB peak-VRAM benchmark suite (scripts/run_community_gpu_benchmark.py):

# 1. Pull latest main
git pull origin main

# 2. Run the 5-stage opt-in Community GPU Benchmark
uv run python scripts/run_community_gpu_benchmark.py --contributor-handle <your-github-handle>

# 3. Run the automated pytest suite
uv run pytest tests/test_community_gpu_benchmark.py -v

What It Measures & Verifies on Your Machine

1. Stage 1 (stage1_accelerator): Detects cuda, rocm_hip, apple_mps, or cpu_fallback, and verifies peak allocated VRAM stays strictly within the 6,656 MiB usable 8 GB WDDM budget.
2. Stage 2 (stage2_real_token_and_ef21): Trains a causal-LM LoRA adapter on real UTF-8 Rust code tokens (5.5764 -> 4.8885 nats) and verifies exact $L_2$ error-feedback conservation (ef21_conservation_error_l2 = 0.0) in EF21DiLoCoErrorFeedbackBuffer.
3. Stage 3 (stage3_three_tier_128_moe_and_prefetch): Benchmarks ThreeTierHierarchicalMoERouter (4 × 4 × 8 = 128 experts, 8.0x gating FLOP reduction) and speculative token-tree expert prefetching (prefetch_hit_rate = 1.0).
4. Stage 4 (stage4_zk_opoi_v4_and_insurance): Commits 24 speculative (step, layer) activations into a single 32-byte Merkle root, verifies deterministic challenges, and audits GuildSlashingInsurancePool conservation.
5. Stage 5 (receipt_sha256): Writes artifacts/community_gpu_benchmark_receipt.json signed with SHA-256.

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📋 How to Share Your Result Here

Paste your JSON output (or summary table with device_name, routing_throughput_tokens_per_sec, ef21_conservation_error_l2, and receipt_sha256) as a comment in this discussion! Our 3-Hour Autonomous Community Orchestrator scans this thread, verifies your receipt_sha256, and logs your hardware profile.

⚖️ Non-Monetary Reminder: There is no financial payment (0.00 EUR / 0.00 USD) for running benchmarks or contributing code. All recorded "Points" (PTS / $HIVE) confer solely computing processing benefits (shared Sparse MoE inference and training quota) when the live production HiveMind Swarm is deployed, available, and actively used by a large community.

[xaviercallens]

✅ Baseline Verification Receipt (@xaviercallens)

• Device / Backend: CPU (x86_64) (cpu_fallback)
• Stage 2 (EF21-DiLoCo + Real-Token LoRA): baseline_nll = 5.576401 -> trained_nll = 4.888508 nats | ef21_conservation_error_l2 = 0.0
• Stage 3 (128-Expert 3-Tier MoE + Prefetch): 8.0x gating reduction (16 vs 128 inner products) | 3422.0 tokens/sec | prefetch_hit_rate = 1.0
• Stage 4 (ZK-OPoI v4 Batch & Insurance Pool): Merkle root 64faa780153bb75f... (24 leaves, batch_passed = True, reserve 200.0 $HIVE)
• Non-Monetary Charter: financial_payment_usd_eur = 0.0 (Symbolic compute-reciprocity points only; redeemable for computing processing benefits when the live production HiveMind Swarm is deployed and used by a large community)
• Receipt SHA-256: 2f8ae97fd69be25f4c6036aa4cd2153a2affec9e8df435e38158b69028aed8f9

[xaviercallens]

📚 Project HiveMind Comprehensive Wiki (v1.8.0 — 10-Page Sitemap for Humans & AI Agents)

We have published and updated the 10-Page Project HiveMind Wiki (https://github.com/xaviercallens/HiveMind/wiki) so both human contributors and autonomous AI coding agents (Antigravity, Claude Code, Codex, Cursor, OpenHands) can reference complete architectural specs, Lean 4 formal proofs, GPU benchmark protocols, and the Non-Monetary Compute-Reciprocity Charter (0.00 EUR / USD):

1. 🏠 Wiki Home & 10-Page Sitemap (v1.8.0)
2. 🏛️ Architecture & 5-Layer Stack (EF21-DiLoCo, 128-MoE, TURN ChannelBind, WebGL)
3. 🎮 Consumer GPU Node Setup & Steam Background Overlay (< 1.5s Preemption)
4. 🧬 Sparse MoE Upcycling, 128-Expert 3-Tier Router & Speculative Token-Tree Prefetch
5. 🛡️ Byzantine Defense, ZK-OPoI v4, Guild Insurance Pool & 77 Lean 4 Theorems
6. 🌐 HF Community Hub, Rarest-First Seeding, Guilds & Missions 1–24
7. 🧠 Swarm Strategy Improvements (SI-01..SI-08) & Pareto Optimizer
8. 🗺️ Season 7 (Wave 6) Roadmap, Tasks (HM-S7-01..HM-S7-08) & Non-Monetary Points Charter
9. 🤖 AI Agent & Human Contributor Playbook (3-Hour Autonomous Orchestrator & Quality Gates)
10. ⚡ Opt-In Community GPU Benchmark & Multi-Host WAN GameDay Guide

⚖️ Non-Monetary Compute-Reciprocity Charter (0.00 EUR / USD): There is no financial payment or monetary payout. Points (PTS / $HIVE) confer exclusively reciprocal computing processing benefits (priority distributed Sparse MoE inference & QLoRA training slots) when the live production HiveMind Swarm is deployed and used by a large community.

[xaviercallens]

🚀 New Flagship Multi-MoE & 8-Domain Hugging Face GPU Validation Campaign (Operation Polyglot-Singularity-128)

We have launched Discussion #86 — Operation Polyglot-Singularity-128 (HM-S7-09 & HM-S7-10) to validate the 128-Expert 3-Tier Sparse MoE + EF21-DiLoCo + Reputation-Weighted TIES (SI-04) stack across 8 curated Hugging Face datasets (bigcode/the-stack-v2-dedup, hoskinson-center/proofnet, ASSERT-KTH/DISL-Solidity-Smart-Contracts, SWE-bench/SWE-bench_Verified, ScalingIntelligence/KernelBench, HuggingFaceFW/fineweb-edu, qiaojin/PubMedQA, and MultimodalUniverse/multimodal_universe) on real UTF-8 token cross-entropy (-35.79% mean holdout NLL reduction across 71,928 tokens):

uv run python scripts/run_multi_moe_hf_campaign.py --contributor-handle <your_github_handle> --tier standard

• 📚 Wiki Guide: Opt-In Community GPU Benchmark & Multi-MoE Campaign Wiki
• ⚖️ Non-Monetary Charter (0.00 EUR / 0.00 USD): No financial payment is ever involved; symbolic PTS / $HIVE points confer exclusively reciprocal computing processing benefits when the live production HiveMind Swarm is deployed and used by a large community.