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Updated: Jul 13, 2025

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform
Published on: August 2, 2019
Performance and profiling data of plane-wave calculations in quantum ESPRESSO simulation on three supercomputing
Worawan Marurngsith1, Supakiet Waiphinit1, Wiraporn Rosmode1
1Department of Computer Science, Faculty of Science and Technology, Thammasat University (Lampang Campus) 248 M.2 Hang Chat, Lampang 52190 Thailand.
This study analyzes Quantum ESPRESSO (QE) performance for Cerium Oxide simulations. It identifies optimal parameters and resources for efficient self-consistent field (SCF) calculations, aiding HPC resource estimation.
Area of Science:
- Computational Materials Science
- High-Performance Computing (HPC)
Background:
- Quantum ESPRESSO (QE) is crucial for materials simulations.
- Optimizing self-consistent field (SCF) calculations is key for computational efficiency.
Purpose of the Study:
- To profile parallel execution of multiple QE versions.
- To identify optimal parameters and resources for efficient SCF calculations.
- To provide a roadmap for HPC resource estimation and scalability analysis.
Main Methods:
- Utilized Extrae performance profiling tool for execution traces.
- Benchmarked QE performance across three HPC centers (ThaiSC, NSCC, NCI).
- Analyzed K-point parallelization parameter impact and scaled simulations across 32 nodes.
Main Results:
- Dataset reflects parallel execution profiles of five QE versions.
- Identified optimal parameters and computing resources for efficient SCF loops.
- Demonstrated scalability of QE across 1,536 CPU cores on NCI Gadi.
Conclusions:
- The dataset serves as a guide for researchers to estimate computational needs.
- Provides insights into scalability bottlenecks for materials simulations.
- Offers adaptable guidelines for various HPC systems and materials.
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