Real-time Nvidia GPU dashboard

Summary

GPU Hot Real-Time NVIDIA GPU Monitoring Dashboard Single-container web dashboard for NVIDIA GPU monitoring with real-time charts. Overview Self-contained dashboard for monitoring NVIDIA GPUs on remote servers. Access utilization and health metrics from a browser without SSH. Runs in a single container on one port. No configuration required - start the container and open a browser. Quick Start docker-compose up --build Open http://localhost:1312 Requirements: Docker, NVIDIA Container Toolkit (install guide) Why Not Just Use... nvidia-smi CLI: Requires SSH access No historical data or charts Manual refresh only Hard to compare multiple GPUs prometheus/grafana: Complex setup (exporters, databases, dashboard configs) Overkill for simple monitoring needs Higher resource usage This is the middle ground: web interface with charts, zero configuration. Features 7 Charts per GPU: Utilization, Temperature, Memory, Power Draw Fan Speed, Clock Speeds (graphics/SM/memory), Power Efficiency Monitoring: Automatic multi-GPU detection GPU process tracking (PID, memory usage) System CPU/RAM monitoring Threshold indicators (temp: 75°C/85°C, util: 80%, memory: 90%) Metrics Collected: Core Metrics GPU & Memory Utilization (%) Temperature - GPU core & memory (°C) Memory - used/free/total (MB) Power - draw & limits (W) Fan Speed (%) Clock Speeds - graphics, SM, memory, video (MHz) Advanced Metrics PCIe Generation & Lane Width (current/max) Performance State (P-State) Compute Mode Encoder/Decoder sessions & statistics Driver & VBIOS versions Throttle status Installation Docker (Recommended) git clone https://github.com/psalias2006/gpu-hot cd gpu-hot docker-compose up --build Local Development pip install -r requirements.txt python app.py Verify GPU Access docker run --rm --gpus all nvidia/cuda:12.1.0-base-ubuntu22.04 nvidia-smi If this fails, install NVIDIA Container Toolkit first. Configuration None required. Optional customization: Environment Variables: NVIDIA_VISIBLE_DEVICES=0,1 # Speci...