How do I install the Hyperpod Version Checker skill?

Run npx skillmds@latest add gabrielmoreira/hyperpod-version-checker in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Hyperpod Version Checker safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Hyperpod Version Checker?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Hyperpod Version Checker free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Hyperpod Version Checker?

gabrielmoreira (@gabrielmoreira) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Hyperpod Version Checker by gabrielmoreira

Name: Hyperpod Version Checker
Rating: 4.2 (5 reviews)
Author: gabrielmoreira

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, documenting cluster configuration, or troubleshooting version-related issues on HyperPod. Triggers on requests about versions, compatibility, component checks, or upgrade planning for HyperPod clusters.

gabrielmoreira Updated Sep 9, 2026 17 repo stars

File contents

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

Component	Detection Method	Applicable When
NVIDIA Driver	`nvidia-smi`	GPU instances (p3/p4/p5/g5)
CUDA Toolkit	`nvcc`, `/usr/local/cuda` symlink	GPU instances
cuDNN	Header file, packages	GPU instances doing deep learning
NCCL	Library filename, header, packages	Distributed GPU training
EFA	`/opt/amazon/efa_installed_packages`, `fi_info`	EFA-capable instances (p4d/p4de/p5/trn1/trn2)
AWS OFI NCCL	`efa_installed_packages`, library search	EFA + NCCL workloads
GDRCopy	rpm/dpkg, kernel module	GPU instances with RDMA (p4d+/p5)
MPI	`mpirun`, `/opt/amazon/openmpi`	Distributed training
Neuron SDK	`neuronx-cc`, `neuron-ls`, packages	Trainium/Inferentia (trn1/trn2/inf1/inf2)
Python/PyTorch	`python3`, `torch` import	ML workloads
Container runtime	`docker`, `containerd`, `kubectl`, `nvidia-ctk`	EKS 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 Series	Supported CUDA
580+	13.x, 12.x, 11.x
570+	12.8+ (Blackwell), 12.x, 11.x
545+	12.3-12.7, 11.x
525-535	12.0-12.2, 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 Installer	AWS OFI NCCL
1.29+	v1.7.3+ (recommended)
1.26-1.28	v1.7.0-v1.7.2
1.20-1.25	v1.6.0+

---name: hyperpod-version-checkerdescription: 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.--- # HyperPod Version Checker Upload to cluster nodes via `hyperpod-ssm` skill, then execute. ## Usage ```bash # 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 | Component | Detection Method | Applicable When | | ----------------- | ----------------------------------------------- | --------------------------------------------- | | NVIDIA Driver | `nvidia-smi` | GPU instances (p3/p4/p5/g5) | | CUDA Toolkit | `nvcc`, `/usr/local/cuda` symlink | GPU instances | | cuDNN | Header file, packages | GPU instances doing deep learning | | NCCL | Library filename, header, packages | Distributed GPU training | | EFA | `/opt/amazon/efa_installed_packages`, `fi_info` | EFA-capable instances (p4d/p4de/p5/trn1/trn2) | | AWS OFI NCCL | `efa_installed_packages`, library search | EFA + NCCL workloads | | GDRCopy | rpm/dpkg, kernel module | GPU instances with RDMA (p4d+/p5) | | MPI | `mpirun`, `/opt/amazon/openmpi` | Distributed training | | Neuron SDK | `neuronx-cc`, `neuron-ls`, packages | Trainium/Inferentia (trn1/trn2/inf1/inf2) | | Python/PyTorch | `python3`, `torch` import | ML workloads | | Container runtime | `docker`, `containerd`, `kubectl`, `nvidia-ctk` | EKS 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 Series | Supported CUDA | | ------------- | ----------------------------- | | 580+ | 13.x, 12.x, 11.x | | 570+ | 12.8+ (Blackwell), 12.x, 11.x | | 545+ | 12.3-12.7, 11.x | | 525-535 | 12.0-12.2, 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 Installer | AWS OFI NCCL | | ------------- | --------------------- | | 1.29+ | v1.7.3+ (recommended) | | 1.26-1.28 | v1.7.0-v1.7.2 | | 1.20-1.25 | v1.6.0+ |

Frequently asked questions