How do I check GPU utilization on the server?
To check GPU utilization on your Cyfuture AI server, SSH into the server and run the nvidia-smi command in the terminal, which displays real-time metrics like GPU usage percentage, memory consumption, temperature, and active processes. For continuous monitoring, use watch -n 1 nvidia-smi to refresh every second or access Cyfuture AI's integrated dashboard for cloud-based GPU insights. Ensure NVIDIA drivers are installed on your Cyfuture AI GPU instance beforehand.?
Step-by-Step Monitoring Guide
Cyfuture AI provides robust GPU servers optimized for AI workloads, where nvidia-smi serves as the primary command-line tool from NVIDIA for monitoring utilization across Linux-based instances, which are standard in their GPU as a Service offerings. Connect via SSH to your Cyfuture AI server using credentials from the control panel, then execute nvidia-smi to view a table showing GPU index, utilization (e.g., 75% load), memory (used/total), power draw, and processes like Python scripts for AI training.?
For enhanced real-time tracking, append flags like nvidia-smi -l 1 for one-second intervals or nvidia-smi --query-gpu=utilization.gpu,memory.used --format=csv for scriptable output suitable for logging in Cyfuture AI environments. On Windows-based Cyfuture AI servers (less common for GPUaaS), use Task Manager's Performance tab under GPU for quick graphs of usage and temperature. Advanced users can integrate Prometheus with NVIDIA DCGM exporter and Grafana for dashboards visualizing multi-GPU clusters on Cyfuture AI, enabling alerts for high utilization or overheating.?
Cyfuture AI's platform complements these with a unified monitoring dashboard accessible via the user portal, displaying GPU metrics alongside billing and auto-scaling options for optimized AI model training. Python frameworks like PyTorch offer in-code checks with torch.cuda.utilization() or nvidia-ml-py bindings for seamless integration during Jupyter sessions on Cyfuture AI instances.?
Conclusion
Monitoring GPU utilization on Cyfuture AI servers ensures efficient resource use, cost savings through spot instances, and peak performance for AI tasks like model training. Regular checks with nvidia-smi and Cyfuture AI dashboards prevent bottlenecks, enabling scalable GPUaaS deployments. Leverage these tools to maximize your Cyfuture AI investment.?
Follow-up Questions & Answers
How do I install NVIDIA drivers on a Cyfuture AI GPU server?
Pre-installed on most Cyfuture AI instances; if needed, run sudo apt update && sudo apt install nvidia-driver-535 (adjust version) and reboot.?
What if nvidia-smi shows 0% utilization during AI training?
Check if processes are GPU-bound (e.g., CUDA errors) or use nvidia-smi pmon for process details; optimize batch sizes for better load on Cyfuture AI.?
Can I monitor GPU via Cyfuture AI API?
Yes, Cyfuture AI APIs allow programmatic retrieval of metrics for custom dashboards, integrating with tools like Grafana.?
How to set alerts for high GPU temperature?
Use watch with scripts or Cyfuture AI's dashboard alerts; Prometheus/Grafana on your instance for thresholds like 85°C.?
Is monitoring available for multi-GPU setups on Cyfuture AI?
Absolutely, nvidia-smi lists all GPUs; Cyfuture AI dashboards aggregate cluster-wide utilization for HPC workloads.?
