Software Installation Guide¶
This guide provides instructions for installing commonly used scientific software packages on the PERUN cluster using Conda environments.
Overview¶
All software installations should be performed within Conda environments to ensure:
- Isolated dependencies for different projects
- Reproducible environments across computing sessions
- No conflicts with system libraries or other projects
Tip — Create a Dedicated Environment
Before installing any software, create a new Conda environment:
Linear Algebra Libraries¶
BLAS (Basic Linear Algebra Subprograms)¶
BLAS provides standard building blocks for performing basic vector and matrix operations.
Installation:
Version Information
Latest version: 2.307
LAPACK (Linear Algebra PACKage)¶
LAPACK is a library of high-performance linear algebra routines for solving systems of linear equations, eigenvalue problems, and singular value decomposition.
Installation:
Version Information
Latest version: 3.11.0
ScaLAPACK (Scalable LAPACK)¶
ScaLAPACK is a library of high-performance linear algebra routines for parallel distributed memory machines. It extends LAPACK to distributed-memory architectures.
Installation:
Version Information
Latest version: 2.2.0
Interactive Computing¶
Jupyter¶
Jupyter is a metapackage that installs all Jupyter components including JupyterLab, Jupyter Notebook, and related tools for interactive computing.
Installation:
Version Information
Latest version: 1.1.1
Quantum Chemistry¶
Psi4¶
Psi4 is an open-source quantum chemistry package written in C++ and driven by Python, designed for efficient and accurate electronic structure calculations.
Installation:
Version Information
Latest version: 1.10
Example — Basic Psi4 Usage
import psi4
psi4.set_memory('8 GB')
psi4.set_num_threads(4)
# Define molecule
mol = psi4.geometry("""
O
H 1 0.96
H 1 0.96 2 104.5
""")
# Run calculation
energy = psi4.energy('scf/cc-pvdz')