mblt-tracker 0.1.0

A Python library to track device usage, such as Mobilint NPU, NVIDIA GPU, Intel CPU, ...

Mobilint Device Tracker

A lightweight Python library for tracking hardware metrics (Power, Utilization, Memory, Temperature) across CPU, GPU, and NPU.

Overview

mblt-tracker is designed to help developers and researchers measure hardware performance with fair and consistent criteria. It provides a unified interface to poll metrics in the background while your code runs, producing both summarized statistics and detailed time-series traces.

✨ Key Features

• Multi-Backend Support: Unified interface for Intel CPU, NVIDIA GPU, and Mobilint NPU.
• Background Tracking: Uses a background scheduler to poll metrics without blocking your main execution.
• Comprehensive Metrics: Capture Power (Watts), Utilization (%), Memory Usage (MB/%), and Temperature (C).
• Statistical Summaries: Automatically calculates averages, peaks (max), and p99 values.
• Time-Series Traces: Export raw data for custom plotting and analysis.
• Lightweight: Minimal overhead, designed for production and research environments.

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🚀 Installation

pip install mblt-tracker

For the latest features, install directly from source:

git clone https://github.com/mobilint/mblt-tracker.git
cd mblt-tracker
pip install -e .

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📖 Quick Start Guide

The typical workflow involves initializing a tracker, starting it before your target workload, and stopping it after.

from mblt_tracker import CPUDeviceTracker # or GPUDeviceTracker, NPUDeviceTracker

# 1. Initialize with a polling interval (seconds)
tracker = CPUDeviceTracker(interval=0.1)

# 2. Start tracking (best to run after warm-up)
tracker.start()

# --- Your workload starts here ---
# e.g., model.inference(data)
# --- Your workload ends here ---

# 3. Stop tracking
tracker.stop()

# 4. Access results
metrics = tracker.get_metric()

def format_metric(value, unit):
    return f"{value:.2f} {unit}" if value is not None else f"N/A {unit}"

print(f"Average Power: {format_metric(metrics['avg_power_w'], 'W')}")
print(f"Max Utilization: {format_metric(metrics['max_utilization_pct'], '%')}")
print(f"Max Temperature: {format_metric(metrics['max_temperature_c'], 'C')}")

# 5. Export time-series trace (list of (timestamp, power_w))
trace = tracker.get_trace()

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📊 Metrics Coverage

Metric	Intel CPU	NVIDIA GPU	Mobilint NPU
Power (W)	✅ (RAPL)	✅ (NVML)	✅ (mobilint-cli)
Utilization (%)	✅ (psutil)	✅ (NVML)	✅ (mobilint-cli)
Memory (MB/%)	✅ (psutil)	✅ (NVML)	✅ (mobilint-cli)
Per-Device Stats	✅ (Sockets)	✅ (GPU Indices)	❌ (Global/Total)

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🛠️ Hardware Specifics

Intel CPU

Uses pyRAPL for power measurements and psutil for utilization/memory.

• Permission: Requires read access to Intel RAPL sysfs.

  sudo chmod -R a+r /sys/class/powercap/intel-rapl/
  

• Docker: Run containers with --privileged or mount the powercap directory.

• Features: Tracks total system CPU usage or specific indices (e.g., CPUDeviceTracker(cpu_id=[0, 1])).

• Temperature: Uses psutil.sensors_temperatures() when the platform exposes CPU thermal sensors.

NVIDIA GPU

Uses NVML (via nvidia-ml-py) for high-fidelity hardware monitoring.

• Features: Tracks total system GPU usage or specific indices (e.g., GPUDeviceTracker(gpu_id=[0, 1])).
• Dependencies: Requires NVIDIA Drivers and NVML library installed.
• Temperature: Reads on-die GPU temperature through NVML.

Mobilint NPU

Polls the mobilint-cli status command.

• Platform: Currently supports Linux only.
• Requirement: Ensure Mobilint Utility Tool is installed and mobilint-cli is in your PATH.
• NPU Power: Distinguishes between NPU-specific power and total system power.
• Temperature: Parses NPU temperature from mobilint-cli status output when available.

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📝 Metric Output Format

Calling get_metric() returns a dictionary with the following standard keys (where applicable):

{
  "avg_power_w": 25.4,          // Average total power in Watts
  "max_power_w": 45.2,          // Peak power observed
  "p99_power_w": 40.1,          // 99th percentile power
  "avg_utilization_pct": 78.5,  // Average device utilization
  "max_utilization_pct": 95.0,  // Peak device utilization
  "avg_memory_used_mb": 2048.0, // Average memory usage
  "total_memory_mb": 8192.0,    // Total available memory
  "avg_temperature_c": 72.3,    // Average device temperature
  "samples": 100                // Number of data points collected
}

Note: Some trackers provide additional keys like cpu or gpu for per-socket/per-device breakdown.

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🤝 Contributing

We welcome contributions! To set up for development:

1. Install dev dependencies: pip install -e ".[dev]"
2. Run tests: pytest tests/

📄 License

This project is licensed under the BSD-3-Clause License. See the LICENSE file for details.

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Developed with ❤️ by Mobilint Inc.