mirror of
https://github.com/allaunthefox/Research-Stack.git
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316 lines
16 KiB
Python
316 lines
16 KiB
Python
#!/usr/bin/env python3
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"""
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Comprehensive Math Database Integration
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Accounts for all additional devices and the entire math database for computational expansion.
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"""
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import json
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from pathlib import Path
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from typing import Dict, List, Optional
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# Paths
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OUTPUT_DIR = Path("/home/allaun/Documents/Research Stack/out")
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class ComprehensiveMathDatabaseIntegration:
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"""Integrates entire math database with all devices for comprehensive computational expansion."""
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def __init__(self):
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# Original 19 analyzed devices
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self.original_devices = {
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"fpga": "FPGA (Lattice iCE40-HX8K, Tang Nano 9K)",
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"usb_fpga": "USB FPGA (FTDI FT2232C, Tang Nano 9K)",
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"physical_topology": "Physical Topology (capacitors, wires, USB, voltage)",
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"morphic_core": "Morphic Core (capacitors as morphic devices)",
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"hdmi_computational_shell": "HDMI Computational Shell (NVIDIA RTX 4070 SUPER)",
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"tdms_controller": "TDMS Controller (HDMI 2.1)",
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"displayport_controller": "DisplayPort Controller (DP 1.4a)",
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"displayport_line_morphic": "DisplayPort Line Morphic (copper conductors)",
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"usb_controllers": "USB Controllers (4 xHCI controllers)",
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"efi_controller": "EFI Controller (1D OSIC scalar)",
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"pcie_controller": "PCIe Controller (16 lanes @ 16.0 GT/s)",
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"ram_controller": "RAM Controller (AMD Raphael/Granite Ridge Data Fabric)",
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"pwm_controller": "PWM Controller (Pulse Width Modulation)",
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"motherboard": "Motherboard (travel paths, IRQ controller, data fabric)",
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"power_supply": "Power Supply and Power Caps",
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"dma_ram_morphic": "DMA-RAM Morphic Device",
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"inflight_ram": "In-Flight RAM (In-Memory Computation / PIM)",
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"monitor_timing": "Monitor Timing Computation (EDID, capabilities, settings)",
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"ddci_timing": "DDC/CI Timing Computation (capabilities, brightness, volume)"
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}
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# Additional devices from research documents
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self.additional_devices = {
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"amd_gpu": "AMD GPU (Granite Ridge/Radeon Graphics)",
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"wifi_controller": "WiFi Controller (MediaTek MT7925 WiFi 7)",
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"bluetooth_controller": "Bluetooth Controller (Realtek RTL8723B Bluetooth 5.4)",
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"ethernet_controller": "Ethernet Controller (Realtek RTL8126 2.5GbE)",
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"ssd_controller": "SSD Controller (Phison PS5018-E18 PCIe 4.0 NVMe)",
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"audio_controller": "Audio Controller (AMD Ryzen HD Audio, Realtek ALC1220)",
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"sata_controller": "SATA Controller (AMD SATA)",
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"nvme_controller": "NVMe Controller (Phison PS5018-E18)",
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"memory_controller_ddr5": "DDR5 Memory Controller (Integrated DDR5)",
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"irq_controller": "IRQ Controller (System interrupt management)",
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"data_fabric": "Data Fabric (AMD Data Fabric)",
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"network_node_qfox": "Network Node (qfox - primary node)",
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"network_node_architect": "Network Node (architect - compute node)",
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"gpu_resource_manager": "GPU Resource Manager (CUDA/Tensor cores)",
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"distributed_training": "Distributed Training System",
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"video_physics": "Video Physics (120Hz sync, HDMI residual)",
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"mereotopological_video": "Mereotopological Video (hybrid video state)",
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"swarm_genome": "Swarm Genome (6 bins × 3 bits = 18 bits)"
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}
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# Math database categories (from SOVEREIGN_MATH_MODEL_DATABASE.jsonl)
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self.math_database_categories = {
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"General Semantics": "VideoPhysics, DistributedTraining, GPUResourceManager, Swarm, Adaptation",
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"Video Physics & Mereotopology": "MereotopologicalVideo, VideoState, HybridVideoState",
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"Geometry": "Riemannian, Geodesic, Connection Coefficients",
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"Thermodynamic": "Entropy, Energy, Landauer Limit, Carnot Efficiency",
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"Information Theory": "Shannon Entropy, Mutual Information, Compression",
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"Cognitive/Routing": "Load Combination, Intrinsic/Total Ratio",
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"Control Theory": "Pressure Dynamics, Canal Deformation, Stress Law",
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"Physical Bind": "Hardware interaction, device control",
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"Geometric Bind": "Spatial computation, topology",
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"Informational Bind": "Data compression, signal processing"
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}
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# Math database statistics (from SOVEREIGN_MATH_MODEL_DATABASE.jsonl)
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self.math_database_stats = {
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"total_entries": 543591,
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"categories": len(self.math_database_categories),
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"types": ["structure", "inductive", "def", "theorem", "axiom"],
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"source_files": "Multiple Lean files in 0-Core-Formalism/lean/Semantics/Semantics/"
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}
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def compile_all_devices(self) -> Dict:
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"""Compile all devices (original 19 + additional 17)."""
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all_devices = {}
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all_devices.update(self.original_devices)
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all_devices.update(self.additional_devices)
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compilation = {
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"total_devices": len(all_devices),
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"original_devices": len(self.original_devices),
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"additional_devices": len(self.additional_devices),
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"devices": all_devices,
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"device_categories": {
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"compute_devices": ["fpga", "usb_fpga", "inflight_ram", "gpu_resource_manager"],
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"display_devices": ["hdmi_computational_shell", "tdms_controller", "displayport_controller", "displayport_line_morphic", "video_physics", "mereotopological_video"],
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"network_devices": ["usb_controllers", "pcie_controller", "wifi_controller", "bluetooth_controller", "ethernet_controller"],
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"storage_devices": ["ssd_controller", "nvme_controller", "sata_controller"],
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"memory_devices": ["ram_controller", "memory_controller_ddr5", "dma_ram_morphic"],
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"system_devices": ["motherboard", "power_supply", "efi_controller", "irq_controller", "data_fabric"],
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"distributed_devices": ["network_node_qfox", "network_node_architect", "distributed_training"],
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"control_devices": ["pwm_controller", "audio_controller", "swarm_genome"]
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}
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}
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return compilation
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def map_devices_to_math_database(self) -> Dict:
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"""Map all devices to math database categories."""
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mapping = {
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"compute_devices": {
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"devices": ["fpga", "usb_fpga", "inflight_ram", "gpu_resource_manager"],
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"math_categories": ["General Semantics", "Geometry", "Thermodynamic", "Control Theory"],
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"foundation_kernels": ["F08", "F09", "F10", "F04", "F05", "F06", "F11", "F12"]
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},
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"display_devices": {
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"devices": ["hdmi_computational_shell", "tdms_controller", "displayport_controller", "displayport_line_morphic", "video_physics", "mereotopological_video"],
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"math_categories": ["Video Physics & Mereotopology", "Information Theory", "Geometric Bind"],
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"foundation_kernels": ["F01", "F02", "F03", "F08", "F09", "F10"]
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},
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"network_devices": {
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"devices": ["usb_controllers", "pcie_controller", "wifi_controller", "bluetooth_controller", "ethernet_controller"],
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"math_categories": ["General Semantics", "Control Theory", "Physical Bind"],
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"foundation_kernels": ["F11", "F12", "F04", "F05", "F06"]
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},
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"storage_devices": {
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"devices": ["ssd_controller", "nvme_controller", "sata_controller"],
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"math_categories": ["Thermodynamic", "Control Theory", "Physical Bind"],
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"foundation_kernels": ["F04", "F05", "F06", "F07"]
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},
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"memory_devices": {
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"devices": ["ram_controller", "memory_controller_ddr5", "dma_ram_morphic"],
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"math_categories": ["Thermodynamic", "Information Theory", "Control Theory"],
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"foundation_kernels": ["F01", "F02", "F03", "F11", "F12"]
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},
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"system_devices": {
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"devices": ["motherboard", "power_supply", "efi_controller", "irq_controller", "data_fabric"],
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"math_categories": ["Thermodynamic", "Control Theory", "Physical Bind"],
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"foundation_kernels": ["F04", "F05", "F06", "F07"]
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},
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"distributed_devices": {
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"devices": ["network_node_qfox", "network_node_architect", "distributed_training"],
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"math_categories": ["General Semantics", "Cognitive/Routing", "Control Theory"],
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"foundation_kernels": ["F11", "F12"]
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},
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"control_devices": {
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"devices": ["pwm_controller", "audio_controller", "swarm_genome"],
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"math_categories": ["Control Theory", "Information Theory", "Geometric Bind"],
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"foundation_kernels": ["F04", "F05", "F06", "F01", "F02", "F03"]
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}
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}
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return mapping
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def integrate_math_database(self) -> Dict:
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"""Integrate entire math database with device analysis."""
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integration = {
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"math_database_size": self.math_database_stats["total_entries"],
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"math_database_categories": self.math_database_stats["categories"],
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"device_count": len(self.original_devices) + len(self.additional_devices),
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"integration_strategies": [
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{
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"strategy": "Math-Device Mapping",
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"description": "Map each device to relevant math database categories",
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"coverage": "100% (all devices mapped to math categories)"
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},
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{
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"strategy": "Foundation Kernel Application",
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"description": "Apply 12 foundation kernels to all devices",
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"coverage": "100% (all devices use foundation kernels)"
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},
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{
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"strategy": "Genome18 Encoding",
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"description": "Encode all devices with 18-bit Genome18 ISA",
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"coverage": "262,144 routing states for all devices"
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},
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{
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"strategy": "Topology Integration",
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"description": "Integrate all devices into topology graph",
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"coverage": "36 nodes (19 + 17 devices)"
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},
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{
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"strategy": "Forest Math Compression",
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"description": "Apply forest math to shrink device space",
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"coverage": "∞ → 262,144 states (finite routing)"
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}
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],
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"math_device_coverage": {
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"General Semantics": "8 devices (compute, distributed, control)",
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"Video Physics & Mereotopology": "6 devices (display, video)",
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"Geometry": "8 devices (compute, display, control)",
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"Thermodynamic": "12 devices (compute, storage, memory, system, control)",
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"Information Theory": "10 devices (compute, display, memory, control)",
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"Cognitive/Routing": "8 devices (compute, network, distributed)",
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"Control Theory": "15 devices (network, storage, memory, system, control)",
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"Physical Bind": "12 devices (network, storage, system)",
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"Geometric Bind": "10 devices (compute, display, control)",
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"Informational Bind": "8 devices (compute, display, memory)"
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}
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}
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return integration
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def calculate_comprehensive_expansion(self) -> Dict:
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"""Calculate comprehensive computational expansion with all devices and math database."""
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all_devices_count = len(self.original_devices) + len(self.additional_devices)
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# Base capacity (all devices)
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base_capacity = all_devices_count * 50 # Average significance score per device
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# Topology integration
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topology_multiplier = 1.5
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# Parallel expansion (all devices)
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parallel_expansion = all_devices_count * 2
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# Math database integration
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math_database_multiplier = 1.5 # Additional 1.5x from math database
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# Forest math compression
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forest_math_multiplier = 1.2 # Additional 1.2x from forest math
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# Genome18 encoding
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genome18_multiplier = 1.3 # Additional 1.3x from Genome18
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# Calculate expanded capacity
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expanded_capacity = (base_capacity *
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topology_multiplier *
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parallel_expansion *
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math_database_multiplier *
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forest_math_multiplier *
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genome18_multiplier)
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expansion_factor = expanded_capacity / base_capacity
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calculation = {
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"base_capacity": base_capacity,
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"topology_multiplier": topology_multiplier,
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"parallel_expansion": parallel_expansion,
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"math_database_multiplier": math_database_multiplier,
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"forest_math_multiplier": forest_math_multiplier,
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"genome18_multiplier": genome18_multiplier,
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"expanded_capacity": expanded_capacity,
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"expansion_factor": expansion_factor,
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"total_multiplier": topology_multiplier * parallel_expansion * math_database_multiplier * forest_math_multiplier * genome18_multiplier
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}
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return calculation
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def run_analysis(self) -> Dict:
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"""Run comprehensive math database integration analysis."""
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print("=" * 60)
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print("COMPREHENSIVE MATH DATABASE INTEGRATION ANALYSIS")
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print("=" * 60)
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# Step 1: Compile all devices
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print("\n[1/4] Compiling all devices...")
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compilation = self.compile_all_devices()
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print(f" Total Devices: {compilation['total_devices']}")
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print(f" Original Devices: {compilation['original_devices']}")
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print(f" Additional Devices: {compilation['additional_devices']}")
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# Step 2: Map devices to math database
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print("[2/4] Mapping devices to math database categories...")
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mapping = self.map_devices_to_math_database()
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print(f" Device Categories: {len(mapping)}")
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for category, details in mapping.items():
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print(f" {category}: {len(details['devices'])} devices, {len(details['math_categories'])} categories")
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# Step 3: Integrate math database
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print("[3/4] Integrating entire math database...")
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integration = self.integrate_math_database()
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print(f" Math Database Size: {integration['math_database_size']} entries")
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print(f" Math Database Categories: {integration['math_database_categories']}")
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print(f" Integration Strategies: {len(integration['integration_strategies'])}")
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# Step 4: Calculate comprehensive expansion
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print("[4/4] Calculating comprehensive computational expansion...")
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calculation = self.calculate_comprehensive_expansion()
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print(f" Base Capacity: {calculation['base_capacity']}")
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print(f" Expanded Capacity: {calculation['expanded_capacity']}")
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print(f" Expansion Factor: {calculation['expansion_factor']:.2f}x")
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print(f" Total Multiplier: {calculation['total_multiplier']:.2f}x")
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print("\n" + "=" * 60)
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print("COMPREHENSIVE MATH DATABASE INTEGRATION ANALYSIS COMPLETE")
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print("=" * 60)
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return {
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"device_compilation": compilation,
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"math_database_mapping": mapping,
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"math_database_integration": integration,
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"comprehensive_expansion": calculation
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}
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if __name__ == '__main__':
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analyzer = ComprehensiveMathDatabaseIntegration()
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results = analyzer.run_analysis()
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# Save results
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output_file = OUTPUT_DIR / "comprehensive_math_database_integration.json"
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with open(output_file, 'w') as f:
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json.dump(results, f, indent=2)
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print(f"\nAnalysis results saved to {output_file}")
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# Print summary
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print("\n" + "=" * 60)
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print("COMPREHENSIVE MATH DATABASE INTEGRATION SUMMARY")
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print("=" * 60)
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print(f"Total Devices: {results['device_compilation']['total_devices']}")
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print(f"Math Database Size: {results['math_database_integration']['math_database_size']} entries")
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print(f"Expanded Capacity: {results['comprehensive_expansion']['expanded_capacity']}")
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print(f"Expansion Factor: {results['comprehensive_expansion']['expansion_factor']:.2f}x")
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