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Pytorch on AIX: Bringing AI to the AIX enterprise world.

By Aditya Kamath posted 6 days ago

  

IBM AIX operating system is a known and trusted environment to run mission-critical workloads in enterprise environments.

But what if these systems could do more than just run? What if they could learn?

With PyTorch running on AIX, you can bring the power of machine learning directly to your enterprise core in Power Systems without moving data off the box.

PyTorch, transformers, tokenizers, and sentence-transformers are now available for AIX users having OS level 7.3 and higher in AIX Toolbox.

Why run PyTorch on AIX?

  1. Use AI near your data—logs, monitoring.

  2. Do inference of open-source models.

  3. Train lightweight models locally on Power CPUs with on-chip accelerators (MMA).

  4. Embed intelligence in backend services, shell scripts, or background jobs.

  5. Do anomaly detection inside your AIX workloads.

What can you do? Some of the real use cases.

  • Generate embeddings from open-source models.

  • Simple binary decision tasks.

  • Detect anomalous things, like in logs, with auto-encoders.

  • Run lightweight inference in production.

  • Forecast system metrics using LSTM like the below code.

And many more...

How to install pytorch on AIX

Do,

dnf update
dnf install python3-torch    

PyTorch on AIX can be used by SREs, sysadmins, developers, testers, data scientists, and AI teams looking to integrate deep learning into core infrastructure.

PyTorch on AIX is more than portability—it’s about potential since one can run AI at the center of the enterprise infrastructure.

Where the logs are, the business data lives, decisions are made,

AIX offers a reliable and scalable foundation for enterprise workloads, and when paired with PyTorch, it now enables deep learning capabilities.

Installing tokenizers, transformers, and sentence-transformers on AIX.

Building and Installing tokenizers from source

# ToolBox dependencies
dnf install rust*
dnf install python3.9-maturin
dnf install python3.9-scikit-learn
dnf install python3.9-devel

# Path to your OpenXL compiler
export CC="/opt/IBM/openxlC/17.1.2/bin/ibm-clang_r -pthread -maix64"
export CXX="/opt/IBM/openxlC/17.1.2/bin/ibm-clang++_r -pthread -maix64"
export RUSTFLAGS="-C link-args=/usr/lib/libc++abi.a"

wget https://files.pythonhosted.org/packages/92/76/5ac0c97f1117b91b7eb7323dcd61af80d72f790b4df71249a7850c195f30/tokenizers-0.21.1.tar.gz
tar -xf tokenizers-0.21.1.tar.gz
cd tokenizers-0.21.1

pip3 install . --no-build-isolation --no-deps -I

# Installing transformers and sentence-transformers

pip3 install tqdm
pip3 install transformers --no-build-isolation --no-deps -I
pip3 install sentence-transformers --no-build-isolation --no-deps -I

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