Benchmarking Scientific Software for Computational Chemistry in the Dutch National Supercomputer

Project reference: 2126

This project consists in benchmarking computational chemistry applications in the Dutch National supercomputer. The goal of this project is to get acquainted with different relevant software for scientific simulations and be able to analyse and describe the performance of the most relevant applications that are currently run by researchers in the field. The performance results will give out a comprehensive summary of the best compilation options that can be used to achieve maximum performance for different types of simulations on CPUs and GPUs.

Project Mentor: Ana Maria de Carvalho Vicente da Cunha

Project Co-mentor: Carlos Teijeiro Barjas

Site Co-ordinator: Carlos Teijeiro Barjas

Participants: Sahin Can Alpaslan, Milana Mirkovic

Learning Outcomes:

1. Knowledge about different types of simulations and scientific software for computational chemistry
2. Learn how to analyse and optimize the performance for CPU/GPU applications
3. Understand how to properly compile applications to get maximum performance
4. Explore the performance possibilities of GPU-Offloading

Student Prerequisites (compulsory):
Basic knowledge of Linux

Student Prerequisites (desirable):
Experience with working with HPC machines. Good understanding of OpenMP, and MPI. Interest in learning on scientific simulations, particularly for computational chemistry.

Training Materials:

For a better understanding of the use GPU’s the student can look these resources:

• https://developer.nvidia.com/embedded/learn/tutorials
• https://manual.gromacs.org
• https://www.nwchem-sw.org
• https://ambermd.org
• https://www.scm.com

Workplan:

During the time of the internship the student will learn how to benchmark applications in a new supercomputer without the need for specific prior knowledge.

* Week 1: getting familiar with the simulation software and input preparation for different simulations
* Weeks 2 to 4: submission of the different calculations and get the timings for both CPU and GPU, and analysis of the results as soon as they are available
* Weeks 5 to 7: thorough evaluation and polishing of results, analysing the impact of different hardware and compilation options and testing for performance.
* Week 8: deliver a report about the performance of the studied applications and best practices for different simulations.

Final Product Description:
From this project we expect to produce a white paper with the benchmark results of the latest computational chemistry applications. We also expect that this work will be helpful for future use of such applications in our systems.

Adapting the Project: Increasing the Difficulty:
The simulation algorithms used will be changed during the internship, so that the student may analyse the impact of a given type of computation and data layout in different hardware (varying the processor architecture and memory hierarchy).

Adapting the Project: Decreasing the Difficulty:
Use of the same simulation algorithm throughout the analysis, having only minimal changes in the setup.

Resources:

• Laptop provided by SURF
• Supercomputer account provided by SURF
• Access to benchmarking software available at SURF: Q-Chem, NWChem, CP2K, GROMACS, Amber, ADF (AMS)

Organisation:

SURF B.V.