AutoPhi V18-Achievement -- Peak Series #667
Publicly online since 2010 · U.S. patent applications since 2012 · inventions offered since 2014. The work of Christopher Gabriel Brown, independently documented.
AutoPhi V18-Seed Voxel Processor -- Peak Series #667
AutoPhi V18 Peak 667: 21.40 PFLOPS Peta-class | 5nm | 115045 Qubits | Maximum single-die performance
Overview
The AutoPhi V18 Peak 667 is a peta-class quantum-classical hybrid processor built on the 18-seed voxel DNA architecture at 5nm process technology. It delivers 21.40 PFLOPS peak performance with 106.999 TOPS AI acceleration across a 777x777 voxel grid (603,729 total voxels) stacked 108 layers deep (6 stack units of 18). Quantum subsystem: 115,045 qubits at 98.5% fidelity (error rate <1.5%) with 28,761 QEC-protected logical qubits. Clocked at 5.0 GHz with 234.89 TB/s memory bandwidth over 155 nanophotonic channels. Neuromorphic engine: 853.6K spiking neurons for event-driven AI processing. Power envelope: 1.4 kW with 83% reduction vs 130nm baseline. Integrates 8/9 AutoPhi core technologies. Three-chromosome DNA encoding: 128-bit electron strand, 16 quantum instructions (atomic strand), 12 photon opcodes (light strand). Light-trigger initiated.
Key Specifications
| Performance | 21.40 PFLOPS (Peta-class) |
| Process Node | 5nm |
| Clock Speed | 5 GHz |
| AI Acceleration | 106.999 TOPS |
| Quantum Subsystem | 115,045 qubits at 98.5% fidelity (error rate <1.5%) |
| QEC Logical Qubits | 28,761 |
| Memory Bandwidth | 234.89 TB/s |
| Nanophotonic Channels | 155 |
| Neuromorphic Engine | 853.6K spiking neurons |
| Power Envelope | 1.4 kW |
| Power Reduction vs 130nm | 83% |
| Voxel Grid | 777x777 (603729 voxels, 108 layers, 6 stack units of 18) |
| Compute Type | CPU + full-GPU + DPU |
| Form Factor | HPC node |
| LED Power Recycling | 90% |
| EM Cooling Efficiency | 87.3% (zero moving parts) |
| Quantum Battery Layers | 9 |
| DNA Encoding | 128-bit electron strand, 16 quantum instructions, 12 photon opcodes |
| Instruction Set | Red=ADD, Blue=SUB, Green=MUL, Yellow=DIV, Cyan=LOAD, Magenta=STORE, White=BRANCH, UV=QGATE, IR=SYNC, Orange=MEASURE, Violet=ENTANGLE, Lime=NEURON |
Target Markets
- High-performance computing nodes
- large-scale AI inference
- climate modeling
Applications
- Full AI model training
- protein folding
- nuclear simulation
- real-time fraud detection at scale
Pricing & Economics
| AES Tier | AES Tier 3 -- Peak ($2M - $10M) |
| IP Valuation | $2.01B |
| AES COGS | $2.71M |
| AES Sell Price | $9.05M |
| Gross Margin | 70% |
| Revenue Multiple | 30x |
| 5-Year Revenue Projection | $271.44M |
| ROI | 233% |
| Warranty & Support | 5-year premium; 24x7 support; dedicated engineer |
Manufacturing & Fabrication
| Foundry | TSMC N5 / Samsung 5LPE |
| PDK | 5nm PDK (NDA) |
| EDA Flow | Commercial (Synopsys/Cadence) + EUV |
| Readiness | Architecture Ready -- Awaiting 5nm NDA/PDK |
Manufacturing Steps
- Obtain TSMC N5 or Samsung 5LPE PDK under NDA
- Synthesize -> P&R with EUV-aware flow
- DRC/LVS with foundry decks
- Package per FOUNDRY_STANDARDS.md
- Submit via foundry portal
Deliverables
- GDSII (mask layout)
- LEF (library exchange)
- DEF (design exchange)
- Gate-level netlist (Verilog)
- DRC report
- LVS report
- FOUNDRY_HANDOFF_SIMPLE.txt
- RTL (autophi_light_cpu_core.v + autophi_quantum_cpu_core.v + autophi_hybrid_cpu_top.v)
- Synthesis scripts
- P&R configurations
- Manufacturing documentation
- Performance projections
RTL Design Files
autophi_light_cpu_core.vautophi_quantum_cpu_core.vautophi_hybrid_cpu_top.v