Understanding Your NVIDIA-SMI GPU Output | Generated by AI
Question: What does this NVIDIA-SMI output indicate about my GPU status and running processes?
Answer: This text is the output of the NVIDIA System Management Interface (nvidia-smi), a command-line utility used to monitor and manage NVIDIA GPU devices. Your specific output shows a high-end enterprise GPU currently running an AI workload.
System Overview
- Driver Version (575.57.08): The version of the NVIDIA graphics driver installed on your system.
- CUDA Version (12.9): The maximum version of the CUDA toolkit supported by this driver.
GPU Hardware Status
The table describes the NVIDIA H100 80GB HBM3, one of the most powerful GPUs designed for AI and data centers.
- Memory Usage: You are using 33,331 MiB out of a total 81,559 MiB (approx. 80GB). This means about 40% of the VRAM is occupied.
- GPU-Util (82%): The GPU is actively working. An 82% utilization rate suggests a significant computation is currently being processed.
- Power Usage (226W / 700W): The card is drawing 226 Watts. It has a high thermal ceiling of 700 Watts, indicating it is currently under a moderate-to-heavy load but not at its absolute peak.
- Temperature (45°C): The card is running quite cool, likely due to high-efficiency data center cooling, as H100s can handle much higher temperatures.
Active Processes
The lower section identifies exactly what is consuming those resources:
- Process Name:
/usr/local/bin/ollama - Type (C): The “C” stands for Compute. This confirms the GPU is being used for a computational task (like LLM inference) rather than a graphical display.
- Memory Consumption: The Ollama process is responsible for almost all the used memory (33,322 MiB), which suggests you have a large language model (LLM) loaded into the GPU memory.
Would you like me to explain how to optimize the memory usage for this specific Ollama process?