Research-Stack/5-Applications/scripts/efi_computational_controller.py

213 lines
8.8 KiB
Python

#!/usr/bin/env python3
"""
EFI Controller Computational Repurposing
Analyzes EFI firmware for general-purpose computation capabilities.
"""
import json
from pathlib import Path
from typing import Dict, List, Optional
# Paths
OUTPUT_DIR = Path("/home/allaun/Documents/Research Stack/out")
class EFIComputationalController:
"""Analyzes EFI firmware for general computation."""
def __init__(self):
self.efi_info = {
"platform_size": "64-bit",
"fw_vendor": "0x98376118",
"runtime": "0x9847eb98",
"efi_available": True,
"computational_potential": "HIGH"
}
self.efi_capabilities = {
"uefi_runtime_services": "Runtime services available during OS execution",
"efi_variables": "Non-volatile variable storage",
"efi_boot_services": "Boot-time services (not available after boot)",
"efi_memory_map": "Memory map of system resources",
"efi_firmware_volume": "Firmware volume with executables",
"efi_protocols": "Protocol interfaces for hardware access"
}
def analyze_computational_potential(self) -> Dict:
"""Analyze computational potential of EFI firmware."""
analysis = {
"uefi_runtime_services": {
"feasible": True,
"mode": "Runtime service computation",
"description": "Use UEFI runtime services for computation during OS execution",
"throughput": "Limited by firmware interface",
"latency": "1-10ms (firmware call)",
"power": "<5W (firmware)"
},
"efi_variables": {
"feasible": True,
"mode": "Variable-based computation",
"description": "Use EFI variables as computational state storage",
"throughput": "Variable access limited",
"latency": "10-100ms (variable access)",
"power": "<1W"
},
"efi_protocols": {
"feasible": True,
"mode": "Protocol-based computation",
"description": "Use EFI protocols for hardware-level computation",
"throughput": "Protocol-specific",
"latency": "1-10ms (protocol call)",
"power": "1-5W"
},
"efi_firmware_volume": {
"feasible": True,
"mode": "Firmware volume execution",
"description": "Execute EFI executables from firmware volume",
"throughput": "UEFI bytecode limited",
"latency": "1-10ms (execution)",
"power": "5-10W"
}
}
return analysis
def design_computational_approach(self) -> Dict:
"""Design EFI-based computational approach."""
approach = {
"uefi_runtime_computation": {
"concept": "Use UEFI runtime services for computation",
"implementation": "Call UEFI runtime services with computational payloads",
"operations": ["GetTime", "GetVariable", "SetVariable", "GetNextVariableName"],
"precision": "64-bit (UEFI native)",
"throughput": "Limited by firmware interface",
"power": "<5W"
},
"efi_variable_computation": {
"concept": "Use EFI variables as computational state",
"implementation": "Store computational state in EFI variables",
"operations": ["state storage", "persistence", "recovery"],
"precision": "Variable-specific",
"throughput": "Variable access limited",
"power": "<1W"
},
"efi_protocol_computation": {
"concept": "Use EFI protocols for hardware computation",
"implementation": "Access hardware via EFI protocols",
"operations": ["PCI access", "memory access", "I/O access"],
"precision": "Protocol-specific",
"throughput": "Hardware-limited",
"power": "1-5W"
},
"efi_bytecode_execution": {
"concept": "Execute EFI bytecode from firmware volume",
"implementation": "Load and execute EFI executables",
"operations": ["UEFI bytecode execution", "firmware drivers"],
"precision": "UEFI bytecode",
"throughput": "UEFI bytecode limited",
"power": "5-10W"
}
}
return approach
def estimate_performance(self) -> Dict:
"""Estimate performance of EFI controller computation."""
performance = {
"uefi_runtime": {
"throughput": "1-10 KOPS (firmware call limited)",
"latency": "1-10ms (firmware call)",
"precision": "64-bit",
"operations": "runtime services",
"power": "<5W"
},
"efi_variables": {
"throughput": "100-1000 variable accesses/sec",
"latency": "10-100ms (variable access)",
"precision": "variable-specific",
"operations": "state storage",
"power": "<1W"
},
"efi_protocols": {
"throughput": "1-10 KOPS (protocol limited)",
"latency": "1-10ms (protocol call)",
"precision": "protocol-specific",
"operations": "hardware access",
"power": "1-5W"
},
"efi_bytecode": {
"throughput": "1-10 KOPS (UEFI bytecode)",
"latency": "1-10ms (execution)",
"precision": "UEFI bytecode",
"operations": "firmware execution",
"power": "5-10W"
}
}
return performance
def run_analysis(self) -> Dict:
"""Run EFI controller computational analysis."""
print("=" * 60)
print("EFI CONTROLLER COMPUTATIONAL ANALYSIS")
print("=" * 60)
# Step 1: Analyze EFI information
print("\n[1/4] Analyzing EFI information...")
print(f" Platform Size: {self.efi_info['platform_size']}")
print(f" Firmware Vendor: {self.efi_info['fw_vendor']}")
print(f" Runtime: {self.efi_info['runtime']}")
print(f" Computational Potential: {self.efi_info['computational_potential']}")
# Step 2: Analyze computational potential
print("[2/4] Analyzing computational potential...")
potential = self.analyze_computational_potential()
print(f" UEFI Runtime Services: {potential['uefi_runtime_services']['feasible']}")
print(f" EFI Variables: {potential['efi_variables']['feasible']}")
print(f" EFI Protocols: {potential['efi_protocols']['feasible']}")
print(f" EFI Firmware Volume: {potential['efi_firmware_volume']['feasible']}")
# Step 3: Design computational approach
print("[3/4] Designing computational approach...")
approach = self.design_computational_approach()
print(f" Computational modes: {len(approach)}")
for mode, details in approach.items():
print(f" {mode}: {details['power']}")
# Step 4: Estimate performance
print("[4/4] Estimating performance...")
performance = self.estimate_performance()
print(f" UEFI Runtime: {performance['uefi_runtime']['throughput']}")
print(f" EFI Variables: {performance['efi_variables']['throughput']}")
print(f" EFI Protocols: {performance['efi_protocols']['throughput']}")
print(f" EFI Bytecode: {performance['efi_bytecode']['throughput']}")
print("\n" + "=" * 60)
print("EFI CONTROLLER COMPUTATIONAL ANALYSIS COMPLETE")
print("=" * 60)
return {
"efi_info": self.efi_info,
"computational_potential": potential,
"computational_approach": approach,
"performance_estimates": performance
}
if __name__ == '__main__':
analyzer = EFIComputationalController()
results = analyzer.run_analysis()
# Save results
output_file = OUTPUT_DIR / "efi_computational_controller.json"
with open(output_file, 'w') as f:
json.dump(results, f, indent=2)
print(f"\nAnalysis results saved to {output_file}")
# Print summary
print("\n" + "=" * 60)
print("EFI COMPUTATIONAL CONTROLLER SUMMARY")
print("=" * 60)
print(f"Platform Size: {results['efi_info']['platform_size']}")
print(f"Computational Potential: {results['efi_info']['computational_potential']}")
print(f"Computational Modes: {len(results['computational_approach'])}")
print(f"Max Throughput: {results['performance_estimates']['uefi_runtime']['throughput']}")