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hyperpod-version-checker

hyperpod-version-checker

Check and compare software component versions on SageMaker HyperPod cluster nodes - NVIDIA drivers, CUDA toolkit, cuDNN, NCCL, EFA, AWS OFI NCCL, GDRCopy, MPI, Neuron SDK (Trainium/Inferentia), Python, and PyTorch. Use when checking component versions, verifying CUDA/driver compatibility, detecting version mismatches across nodes, planning upgrades, documen…

Independent GitHub snapshot · Automated classification · Original documentation governs

Aawslabs / agent-pluginsApache-2.0

Documentation de la Skill

GitHub

name: hyperpod-version-checker description: Check and compare software component versions on SageMaker HyperPod cluster nodes - NVIDIA drivers, CUDA toolkit, cuDNN, NCCL, EFA, AWS OFI NCCL, GDRCopy, MPI, Neuron SDK (Trainium/Inferentia), Python, and PyTorch. Use when checking component versions, verifying CUDA/driver compatibility, detecting version mismatches across nodes, planning upgrades, documenting cluster configuration, or troubleshooting version-related issues on HyperPod. Triggers on requests about versions, compatibility, component checks, or upgrade planning for HyperPod clusters. metadata: version: "1.0.0"

HyperPod Version Checker

Upload to cluster nodes via hyperpod-ssm skill, then execute.

Usage

# Text report to console + file
bash hyperpod_check_versions.sh

# JSON only to stdout (text report still saved to file) — best for piping/parsing
bash hyperpod_check_versions.sh --json

# Custom output file
bash hyperpod_check_versions.sh --output /tmp/versions.txt

# No color (for logging)
bash hyperpod_check_versions.sh --no-color

Output file: component_versions_<hostname>_<timestamp>.txt (default)

What It Checks

ComponentDetection MethodApplicable When
NVIDIA Drivernvidia-smiGPU instances (p3/p4/p5/g5)
CUDA Toolkitnvcc, /usr/local/cuda symlinkGPU instances
cuDNNHeader file, packagesGPU instances doing deep learning
NCCLLibrary filename, header, packagesDistributed GPU training
EFA/opt/amazon/efa_installed_packages, fi_infoEFA-capable instances (p4d/p4de/p5/trn1/trn2)
AWS OFI NCCLefa_installed_packages, library searchEFA + NCCL workloads
GDRCopyrpm/dpkg, kernel moduleGPU instances with RDMA (p4d+/p5)
MPImpirun, /opt/amazon/openmpiDistributed training
Neuron SDKneuronx-cc, neuron-ls, packagesTrainium/Inferentia (trn1/trn2/inf1/inf2)
Python/PyTorchpython3, torch importML workloads
Container runtimedocker, containerd, kubectl, nvidia-ctkEKS clusters

Multi-Node Comparison

Run on each node individually via the hyperpod-ssm skill. With --json, stdout is clean JSON for easy diffing.

Compatibility Reference

The script automatically analyzes CUDA/driver compatibility. For reference:

Driver SeriesSupported CUDA
580+13.x, 12.x, 11.x
570+12.8+ (Blackwell), 12.x, 11.x
545+12.3-12.7, 11.x
525-53512.0-12.2, 11.x
450+11.x only

NCCL: Use 2.18+ for CUDA 12.x, 2.12+ for CUDA 11.x. Must be consistent across all nodes.

EFA InstallerAWS OFI NCCL
1.29+v1.7.3+ (recommended)
1.26-1.28v1.7.0-v1.7.2
1.20-1.25v1.6.0+
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