Predicting time: SCF

⚙️ QE Prediction Guide

This tool uses a trained Neural Network model to estimate the time per SCF call for your Quantum ESPRESSO calculations. The prediction is based on your QE input file, pseudopotentials, and system parameters.

System parameters describe the computational setup used for your calculation. Please specify them according to the machine or configuration you plan to run on:

• Number of cores – total number of cores used in the calculation (MPI × OpenMP). It affects the overall parallelization and speedup.
• Number of nodes – number of compute nodes allocated for the job. Each node typically contains several cores and memory resources.
• Threads per node – number of OpenMP threads used per node. This defines the hybrid parallelization (MPI × OpenMP) setup.
• n_pool – number of k-point or band parallelization groups (npool in Quantum ESPRESSO). It distributes work among MPI pools for better performance in large systems.

For more information or to report any unexpected issue, please contact: Mandana Safari — m.safari@cineca.it