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239 lines
10 KiB
Python
239 lines
10 KiB
Python
#!/usr/bin/env python3
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"""
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DisplayPort Line Morphic Computation
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Analyzes DisplayPort cable lines as morphic devices for computation.
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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 DisplayPortLineMorphic:
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"""Analyzes DisplayPort cable lines as morphic devices."""
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def __init__(self):
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self.displayport_lines = {
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"device": "DisplayPort Cable Lines (Morphic Devices)",
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"lanes": "4 main link lanes + AUX channel",
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"construction": "Shielded twisted pair copper conductors",
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"length": "1-2 meters (inferred)",
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"computational_potential": "MEDIUM-HIGH (copper inductance, capacitance, resistance)"
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}
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self.line_capabilities = {
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"main_link_lanes": {
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"lane_0": "8.1 Gbps (HBR3) - copper twisted pair",
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"lane_1": "8.1 Gbps (HBR3) - copper twisted pair",
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"lane_2": "8.1 Gbps (HBR3) - copper twisted pair",
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"lane_3": "8.1 Gbps (HBR3) - copper twisted pair"
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},
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"aux_channel": "I2C-like control channel - copper pair",
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"hpd": "Hot Plug Detect - single wire",
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"electrical_properties": {
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"inductance": "Copper wire inductance (nH/m)",
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"capacitance": "Twisted pair capacitance (pF/m)",
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"resistance": "Copper resistance (Ω/m)",
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"impedance": "Characteristic impedance (100Ω)"
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}
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}
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def analyze_morphic_potential(self) -> Dict:
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"""Analyze morphic computational potential of DisplayPort lines."""
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analysis = {
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"inductance_computation": {
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"feasible": True,
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"mode": "Inductance-based morphic computation",
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"description": "Use copper wire inductance for computation",
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"throughput": "Inductance limited (nH/m)",
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"latency": "Inductance response (ns)",
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"precision": "nH resolution",
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"power": "1-5W (signal injection)",
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"risk": "LOW (non-invasive)"
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},
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"capacitance_computation": {
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"feasible": True,
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"mode": "Capacitance-based morphic computation",
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"description": "Use twisted pair capacitance for computation",
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"throughput": "Capacitance limited (pF/m)",
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"latency": "Capacitance response (ns)",
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"precision": "pF resolution",
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"power": "1-5W (signal injection)",
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"risk": "LOW (non-invasive)"
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},
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"resistance_computation": {
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"feasible": True,
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"mode": "Resistance-based morphic computation",
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"description": "Use copper resistance for computation",
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"throughput": "Resistance limited (Ω/m)",
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"latency": "Resistance response (ns)",
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"precision": "mΩ resolution",
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"power": "1-5W (signal injection)",
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"risk": "LOW (non-invasive)"
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},
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"impedance_computation": {
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"feasible": True,
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"mode": "Impedance-based morphic computation",
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"description": "Use characteristic impedance for computation",
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"throughput": "Impedance limited (100Ω)",
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"latency": "Impedance response (ns)",
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"precision": "0.1Ω resolution",
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"power": "1-5W (signal injection)",
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"risk": "LOW (non-invasive)"
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}
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}
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return analysis
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def design_morphic_approach(self) -> Dict:
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"""Design line-based morphic computational approach."""
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approach = {
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"inductance_morphic": {
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"concept": "Use copper wire inductance as morphic device",
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"implementation": "Inject signals to measure inductance changes",
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"operations": ["inductance arithmetic", "frequency response", "resonant computation"],
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"throughput": "Inductance limited (nH/m)",
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"latency": "ns response",
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"precision": "nH resolution",
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"power": "1-5W",
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"risk": "LOW"
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},
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"capacitance_morphic": {
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"concept": "Use twisted pair capacitance as morphic device",
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"implementation": "Inject signals to measure capacitance changes",
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"operations": ["capacitance arithmetic", "charge/discharge", "resonant computation"],
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"throughput": "Capacitance limited (pF/m)",
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"latency": "ns response",
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"precision": "pF resolution",
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"power": "1-5W",
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"risk": "LOW"
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},
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"resistance_morphic": {
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"concept": "Use copper resistance as morphic device",
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"implementation": "Inject signals to measure resistance changes",
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"operations": ["resistance arithmetic", "voltage/current", "thermal computation"],
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"throughput": "Resistance limited (Ω/m)",
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"latency": "ns response",
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"precision": "mΩ resolution",
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"power": "1-5W",
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"risk": "LOW"
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},
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"impedance_morphic": {
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"concept": "Use characteristic impedance as morphic device",
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"implementation": "Inject signals to measure impedance changes",
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"operations": ["impedance arithmetic", "reflection coefficient", "SWR computation"],
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"throughput": "Impedance limited (100Ω)",
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"latency": "ns response",
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"precision": "0.1Ω resolution",
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"power": "1-5W",
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"risk": "LOW"
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}
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}
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return approach
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def estimate_performance(self) -> Dict:
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"""Estimate performance of line morphic computation."""
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performance = {
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"inductance": {
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"throughput": "Inductance limited (nH/m)",
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"latency": "ns response",
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"precision": "nH resolution",
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"operations": "inductance arithmetic",
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"power": "1-5W"
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},
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"capacitance": {
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"throughput": "Capacitance limited (pF/m)",
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"latency": "ns response",
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"precision": "pF resolution",
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"operations": "capacitance arithmetic",
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"power": "1-5W"
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},
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"resistance": {
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"throughput": "Resistance limited (Ω/m)",
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"latency": "ns response",
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"precision": "mΩ resolution",
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"operations": "resistance arithmetic",
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"power": "1-5W"
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},
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"impedance": {
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"throughput": "Impedance limited (100Ω)",
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"latency": "ns response",
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"precision": "0.1Ω resolution",
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"operations": "impedance arithmetic",
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"power": "1-5W"
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}
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}
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return performance
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def run_analysis(self) -> Dict:
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"""Run DisplayPort line morphic analysis."""
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print("=" * 60)
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print("DISPLAYPORT LINE MORPHIC COMPUTATION ANALYSIS")
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print("=" * 60)
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# Step 1: Analyze DisplayPort lines
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print("\n[1/4] Analyzing DisplayPort lines...")
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print(f" Device: {self.displayport_lines['device']}")
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print(f" Lanes: {self.displayport_lines['lanes']}")
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print(f" Construction: {self.displayport_lines['construction']}")
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print(f" Length: {self.displayport_lines['length']}")
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print(f" Computational Potential: {self.displayport_lines['computational_potential']}")
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# Step 2: Analyze morphic potential
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print("[2/4] Analyzing morphic computational potential...")
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potential = self.analyze_morphic_potential()
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print(f" Inductance: {potential['inductance_computation']['feasible']} - {potential['inductance_computation']['risk']}")
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print(f" Capacitance: {potential['capacitance_computation']['feasible']} - {potential['capacitance_computation']['risk']}")
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print(f" Resistance: {potential['resistance_computation']['feasible']} - {potential['resistance_computation']['risk']}")
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print(f" Impedance: {potential['impedance_computation']['feasible']} - {potential['impedance_computation']['risk']}")
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# Step 3: Design morphic approach
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print("[3/4] Designing line-based morphic computational approach...")
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approach = self.design_morphic_approach()
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print(f" Morphic modes: {len(approach)}")
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for mode, details in approach.items():
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print(f" {mode}: {details['throughput']} - {details['risk']}")
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# Step 4: Estimate performance
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print("[4/4] Estimating performance...")
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performance = self.estimate_performance()
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print(f" Inductance: {performance['inductance']['throughput']}")
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print(f" Capacitance: {performance['capacitance']['throughput']}")
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print(f" Resistance: {performance['resistance']['throughput']}")
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print(f" Impedance: {performance['impedance']['throughput']}")
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print("\n" + "=" * 60)
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print("DISPLAYPORT LINE MORPHIC COMPUTATION ANALYSIS COMPLETE")
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print("=" * 60)
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return {
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"displayport_lines": self.displayport_lines,
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"line_capabilities": self.line_capabilities,
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"morphic_potential": potential,
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"morphic_approach": approach,
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"performance_estimates": performance
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}
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if __name__ == '__main__':
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analyzer = DisplayPortLineMorphic()
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results = analyzer.run_analysis()
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# Save results
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output_file = OUTPUT_DIR / "displayport_line_morphic.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("DISPLAYPORT LINE MORPHIC COMPUTATION SUMMARY")
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print("=" * 60)
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print(f"Device: {results['displayport_lines']['device']}")
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print(f"Construction: {results['displayport_lines']['construction']}")
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print(f"Computational Potential: {results['displayport_lines']['computational_potential']}")
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print(f"Max Precision: nH/pF/mΩ/0.1Ω resolution")
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