GPU Performance Monitor for HPC Clusters
Project description
WedgeBox-HPC
Simple GPU Performance Monitoring for HPC Clusters
Overview
WedgeBox-HPC provides detailed GPU telemetry for debugging and optimizing machine learning workloads on HPC infrastructure.
Features:
- Multi-vendor GPU support (NVIDIA, AMD)
- Process-level GPU resource tracking
- Zero-configuration monitoring
- Human-readable console output + detailed JSON reports
Quick Start
# Download
wget https://raw.githubusercontent.com/wedgebox/wedgebox-hpc/main/wedgebox-hpc
chmod +x wedgebox-hpc
# Run
./wedgebox-hpc
Requirements
- Python 3.8+
- psutil (
pip install psutil --user) - GPU drivers (nvidia-smi for NVIDIA, rocm-smi for AMD)
For HPC Administrators
See docs/installation.md for cluster-wide deployment instructions.
Output
Generates:
- Console summary (human-readable)
wedgebox-report-[timestamp].json(machine-readable)
Use Cases
- Debug slow training jobs
- Monitor GPU utilization
- Profile memory usage
- Identify resource bottlenecks
- Track multi-GPU workload distribution
License
MIT License - See LICENSE file
Project details
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