AI HAT+ Hardware Specifications¶
Overview¶
The 26 TOPS variant of the Raspberry Pi AI HAT+ provides neural network acceleration through the Hailo-8 neural network inference accelerator. This hardware accelerator enables high-performance AI processing for The Path (AI-Pi) game system.
Hardware Specifications¶
AI_Accelerator:
model: "Hailo-8"
performance: "26 TOPS"
interface: "PCIe 2.0 x1"
power_efficiency: "2.5 TOPS/W"
Memory_Requirements:
dedicated_memory: "2GB reserved"
buffer_memory: "512MB for inference"
model_storage: "1GB recommended"
Performance_Modes:
max_performance:
tops: "26"
power: "10.4W"
use_case: "Multiple concurrent AI models"
balanced:
tops: "19.5"
power: "7.8W"
use_case: "Standard gameplay"
power_saving:
tops: "13"
power: "5.2W"
use_case: "Battery operation"
Integration Points¶
PCIe Communication¶
from hailo_platform import HailoPlatform, DeviceType
def initialize_hailo():
"""Initialize Hailo device with performance mode"""
platform = HailoPlatform()
device = platform.create_device(DeviceType.PCIE)
device.set_power_mode("performance") # 26 TOPS mode
return device
def optimize_model(model_path: str) -> HailoModel:
"""Optimize model for Hailo-8 hardware"""
optimizer = HailoOptimizer(
target_platform="hailo8",
optimization_level=3,
power_mode="performance"
)
return optimizer.optimize(model_path)
Performance Monitoring¶
class HailoMonitor:
def __init__(self):
self.device = initialize_hailo()
def get_metrics(self) -> dict:
"""Get real-time performance metrics"""
return {
'temperature': self.device.temperature,
'power_consumption': self.device.power_consumption,
'utilization': self.device.utilization,
'memory_usage': self.device.memory_usage,
'inference_time': self.device.last_inference_time
}
def check_thermal_throttling(self) -> bool:
"""Monitor for thermal throttling"""
return self.device.temperature > 85 # Celsius
Model Optimization¶
Hardware-Specific Optimizations¶
class ModelOptimizer:
def __init__(self):
self.optimizer = HailoOptimizer()
def optimize_for_gameplay(self, model: HailoModel) -> HailoModel:
"""Optimize model for gameplay requirements"""
return self.optimizer.optimize(
model,
target_fps=60,
max_power=10.4,
precision="mixed"
)
def quantize_model(self, model: HailoModel) -> HailoModel:
"""Quantize model for optimal performance"""
return self.optimizer.quantize(
model,
calibration_set=self.get_calibration_data(),
optimization_level=3
)
Performance Requirements¶
Inference Performance¶
Minimum_Requirements:
inference_time: "<5ms"
model_size: "<500MB"
concurrent_models: 4
memory_usage: "<2GB"
Monitoring_Thresholds:
temperature: "85°C max"
power: "10.4W max"
utilization: "90% max"
memory: "90% max"
Error Handling¶
class HailoError(Exception):
"""Base exception for Hailo-related errors"""
pass
class HailoInitError(HailoError):
"""Raised when Hailo device initialization fails"""
pass
class HailoPerformanceError(HailoError):
"""Raised when performance requirements aren't met"""
pass
def handle_hailo_error(error: HailoError) -> None:
"""Handle Hailo-specific errors"""
if isinstance(error, HailoInitError):
# Try reinitializing with lower performance mode
initialize_hailo(power_mode="balanced")
elif isinstance(error, HailoPerformanceError):
# Scale down model complexity
reduce_model_complexity()
Integration Requirements¶
Driver Installation¶
# Install Hailo drivers and runtime
sudo apt-get update
sudo apt-get install -y hailo-driver
sudo apt-get install -y hailo-runtime
# Verify installation
hailo-pcie-status
Python Dependencies¶
Power Management¶
```python def set_power_mode(mode: str) -> None: """Set Hailo power mode based on requirements""" device = initialize_hailo()
modes = {
'max_performance': {
'tops': 26,
'power_limit': 10.4
},
'balanced': {
'tops': 19.5,
'power_limit': 7.8
},
'power_saving': {
'tops': 13,
'power_limit': 5.2
}
}
config = modes[mode]
device.set_power_mode(mode, config)