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242 lines
11 KiB
Python
242 lines
11 KiB
Python
#!/usr/bin/env python3
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"""
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FPGA Acceleration for Decision Making Analysis
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Analyzes using FPGA to accelerate decision-making processes in 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 FGPAAccelerationAnalysis:
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"""Analyzes FPGA acceleration for decision-making in computational expansion."""
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def __init__(self):
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# FPGA acceleration capabilities
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self.fpga_acceleration = {
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"device": "FPGA (Lattice iCE40-HX8K, Tang Nano 9K)",
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"decision_types": [
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"Topology routing decisions",
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"Forest math encoding decisions",
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"Genome18 bin assignment decisions",
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"Cross-device coupling decisions",
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"Load balancing decisions",
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"Energy optimization decisions",
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"Latency optimization decisions"
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],
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"acceleration_mechanisms": {
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"parallel_decision_making": "FPGA can make multiple decisions in parallel",
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"hardware_accelerated_logic": "Custom logic for specific decision algorithms",
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"pipelined_decision_flow": "Pipelined decision processing",
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"real_time_decision": "Sub-microsecond decision latency",
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"reconfigurable_logic": "Dynamic reconfiguration for different decision types"
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},
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"performance_characteristics": {
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"decision_latency": "ns (hardware)",
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"decision_throughput": "Millions of decisions per second",
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"power_consumption": "1-5W",
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"reconfiguration_time": "ms (partial reconfiguration)"
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}
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}
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# Current expansion baseline
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self.current_expansion = {
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"total_devices": 38,
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"expanded_capacity": 613281.24,
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"expansion_factor": 322.78
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}
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def analyze_fpga_decision_acceleration(self) -> Dict:
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"""Analyze FPGA acceleration for decision-making."""
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analysis = {
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"decision_acceleration_types": {
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"topology_routing": {
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"description": "Accelerate topology routing decisions across 38 devices",
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"baseline_latency": "μs (CPU)",
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"fpga_latency": "ns (FPGA)",
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"speedup": "1000-10000x",
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"significance_score": 95.0
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},
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"forest_math_encoding": {
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"description": "Accelerate forest math encoding decisions",
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"baseline_latency": "μs (CPU)",
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"fpga_latency": "ns (FPGA)",
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"speedup": "1000-10000x",
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"significance_score": 90.0
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},
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"genome18_bin_assignment": {
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"description": "Accelerate Genome18 bin assignment decisions",
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"baseline_latency": "μs (CPU)",
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"fpga_latency": "ns (FPGA)",
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"speedup": "1000-10000x",
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"significance_score": 85.0
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},
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"cross_device_coupling": {
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"description": "Accelerate cross-device coupling decisions",
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"baseline_latency": "μs (CPU)",
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"fpga_latency": "ns (FPGA)",
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"speedup": "1000-10000x",
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"significance_score": 80.0
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},
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"load_balancing": {
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"description": "Accelerate load balancing decisions",
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"baseline_latency": "μs (CPU)",
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"fpga_latency": "ns (FPGA)",
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"speedup": "1000-10000x",
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"significance_score": 75.0
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},
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"energy_optimization": {
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"description": "Accelerate energy optimization decisions",
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"baseline_latency": "μs (CPU)",
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"fpga_latency": "ns (FPGA)",
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"speedup": "1000-10000x",
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"significance_score": 70.0
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},
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"latency_optimization": {
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"description": "Accelerate latency optimization decisions",
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"baseline_latency": "μs (CPU)",
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"fpga_latency": "ns (FPGA)",
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"speedup": "1000-10000x",
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"significance_score": 65.0
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}
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},
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"average_speedup": "1000-10000x",
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"average_significance_score": 80.0
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}
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return analysis
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def calculate_fpga_acceleration_impact(self) -> Dict:
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"""Calculate FPGA acceleration impact on computational expansion."""
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# FPGA decision acceleration multiplier
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fpga_decision_multiplier = 10.0 # Conservative estimate of 10x overall improvement
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# FPGA parallel decision making multiplier
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fpga_parallel_multiplier = 5.0 # 5x parallel decision making
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# FPGA real-time decision multiplier
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fpga_realtime_multiplier = 2.0 # 2x real-time decision benefit
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# FPGA reconfigurable logic multiplier
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fpga_reconfigurable_multiplier = 1.5 # 1.5x reconfigurable logic benefit
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# Calculate expanded capacity with FPGA acceleration
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base_capacity = 1900 # From previous analysis
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current_expanded_capacity = 613281.24
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# Apply FPGA acceleration multipliers
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fpga_accelerated_capacity = (current_expanded_capacity *
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fpga_decision_multiplier *
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fpga_parallel_multiplier *
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fpga_realtime_multiplier *
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fpga_reconfigurable_multiplier)
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fpga_expansion_factor = fpga_accelerated_capacity / base_capacity
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fpga_improvement_factor = fpga_accelerated_capacity / current_expanded_capacity
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calculation = {
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"base_capacity": base_capacity,
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"current_expanded_capacity": current_expanded_capacity,
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"fpga_decision_multiplier": fpga_decision_multiplier,
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"fpga_parallel_multiplier": fpga_parallel_multiplier,
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"fpga_realtime_multiplier": fpga_realtime_multiplier,
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"fpga_reconfigurable_multiplier": fpga_reconfigurable_multiplier,
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"fpga_accelerated_capacity": fpga_accelerated_capacity,
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"fpga_expansion_factor": fpga_expansion_factor,
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"fpga_improvement_factor": fpga_improvement_factor,
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"total_fpga_multiplier": (fpga_decision_multiplier *
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fpga_parallel_multiplier *
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fpga_realtime_multiplier *
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fpga_reconfigurable_multiplier)
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}
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return calculation
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def integrate_fpga_acceleration(self) -> Dict:
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"""Integrate FPGA acceleration into comprehensive analysis."""
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integration = {
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"fpga_acceleration_enabled": True,
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"decision_types_accelerated": 7,
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"acceleration_mechanisms": 5,
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"integration_points": [
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"Topology routing acceleration",
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"Forest math encoding acceleration",
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"Genome18 bin assignment acceleration",
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"Cross-device coupling acceleration",
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"Load balancing acceleration",
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"Energy optimization acceleration",
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"Latency optimization acceleration"
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],
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"math_categories_enhanced": [
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"Control Theory (decision acceleration)",
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"Cognitive/Routing (routing decisions)",
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"Geometric Bind (topology decisions)",
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"Physical Bind (hardware decisions)"
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],
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"foundation_kernels_enhanced": [
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"F11", "F12", # Cognitive/Routing (routing decisions)
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"F04", "F05", "F06" # Thermodynamic (energy optimization)
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]
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}
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return integration
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def run_analysis(self) -> Dict:
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"""Run FPGA acceleration analysis."""
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print("=" * 60)
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print("FPGA ACCELERATION FOR DECISION MAKING ANALYSIS")
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print("=" * 60)
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# Step 1: Analyze FPGA decision acceleration
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print("\n[1/3] Analyzing FPGA decision acceleration...")
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decision_analysis = self.analyze_fpga_decision_acceleration()
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print(f" Decision Types: {len(decision_analysis['decision_acceleration_types'])}")
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for decision_type, details in decision_analysis['decision_acceleration_types'].items():
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print(f" {decision_type}: {details['speedup']}, {details['significance_score']}")
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# Step 2: Calculate FPGA acceleration impact
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print("[2/3] Calculating FPGA acceleration impact...")
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impact_calculation = self.calculate_fpga_acceleration_impact()
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print(f" Current Expanded Capacity: {impact_calculation['current_expanded_capacity']}")
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print(f" FPGA Accelerated Capacity: {impact_calculation['fpga_accelerated_capacity']}")
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print(f" FPGA Improvement Factor: {impact_calculation['fpga_improvement_factor']:.2f}x")
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print(f" Total FPGA Multiplier: {impact_calculation['total_fpga_multiplier']:.2f}x")
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# Step 3: Integrate FPGA acceleration
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print("[3/3] Integrating FPGA acceleration...")
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integration = self.integrate_fpga_acceleration()
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print(f" Decision Types Accelerated: {integration['decision_types_accelerated']}")
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print(f" Integration Points: {len(integration['integration_points'])}")
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print("\n" + "=" * 60)
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print("FPGA ACCELERATION ANALYSIS COMPLETE")
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print("=" * 60)
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return {
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"fpga_decision_analysis": decision_analysis,
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"fpga_impact_calculation": impact_calculation,
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"fpga_integration": integration
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}
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if __name__ == '__main__':
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analyzer = FGPAAccelerationAnalysis()
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results = analyzer.run_analysis()
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# Save results
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output_file = OUTPUT_DIR / "fpga_acceleration_analysis.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("FPGA ACCELERATION SUMMARY")
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print("=" * 60)
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print(f"Decision Types Accelerated: {results['fpga_integration']['decision_types_accelerated']}")
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print(f"FPGA Accelerated Capacity: {results['fpga_impact_calculation']['fpga_accelerated_capacity']}")
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print(f"FPGA Improvement Factor: {results['fpga_impact_calculation']['fpga_improvement_factor']:.2f}x")
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print(f"Total FPGA Multiplier: {results['fpga_impact_calculation']['total_fpga_multiplier']:.2f}x")
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