====MPI4PI====
TOD

----
==== PyTorch====
Consider the following simple python test script( "pytorch_test.py"):
 
<code python>
import torch

def test_pytorch():
    print("PyTorch version:", torch.__version__)
    print("CUDA available:", torch.cuda.is_available())
    
    if torch.cuda.is_available():
        print("CUDA device:", torch.cuda.get_device_name(0))
        device = torch.device("cuda")
    else:
        device = torch.device("cpu")
    
    # Simple tensor operation
    x = torch.tensor([1.0, 2.0, 3.0], device=device)
    y = torch.tensor([4.0, 5.0, 6.0], device=device)
    z = x + y
    print("Tensor operation result:", z)

test_pytorch()
</code>

To test it on the unite cluster you can use the folling sbatch scrpit to run it:
<code bash>
#!/bin/bash
#SBATCH --job-name=pytorch_test
#SBATCH --output=pytorch_test.out
#SBATCH --error=pytorch_test.err
#SBATCH --time=00:10:00
#SBATCH --partition=a40
#SBATCH --gres=gpu:1
#SBATCH --mem=4G
#SBATCH --cpus-per-task=2

# Load necessary modules (modify based on your system)
module load python/pytorch-2.5.1-llvm-cuda-12.3-python-3.13.1-llvm

# Activate your virtual environment if needed
# source ~/your_env/bin/activate

# Run the PyTorch script
python3.13 pytorch_test.py

</code>
----
====Pandas====
Consider the following simple python test script( “pandas_test.py”):
<code python>
import pandas as pd
import numpy as np

# Create a simple DataFrame
data = {
    'A': [1, 2, 3, 4],
    'B': [5, 6, 7, 8],
    'C': [9, 10, 11, 12]
}
df = pd.DataFrame(data)
print("Original DataFrame:")
print(df)

# Test basic operations
print("\nSum of each column:")
print(df.sum())

print("\nMean of each column:")
print(df.mean())

# Adding a new column
df['D'] = df['A'] + df['B']
print("\nDataFrame after adding new column D (A + B):")
print(df)

# Filtering rows
filtered_df = df[df['A'] > 2]
print("\nFiltered DataFrame (A > 2):")
print(filtered_df)

# Check if NaN values exist
print("\nCheck for NaN values:")
print(df.isna().sum())
</code>

You can use the following snatch script to run it:
<code bash>
#!/bin/bash
#SBATCH --job-name=pytorch_test
#SBATCH --output=pytorch_test.out
#SBATCH --error=pytorch_test.err
#SBATCH --time=00:10:00
#SBATCH --partition=a40
#SBATCH --gres=gpu:1
#SBATCH --mem=4G
#SBATCH --cpus-per-task=2

# Load necessary modules (modify based on your system)
module load python/3.13.1-llvm
module load python/3.13/pandas/2.2.3

# Activate your virtual environment if needed
# source ~/your_env/bin/activate

# Run the PyTorch script
python3.13 pandas_test.py
</code>
----
====Other popular====
TOD