December 2020


LearnHPC: dynamic creation of HPC infrastructure for educational purposes

LearnHPC: dynamic creation of HPC infrastructure for educational purposes
In a newly successful PRACE-ICEI proposal, E-CAM, FocusCoE, HPC Carpentry and EESSI join forces to bring HPC resources to the classroom in a simple, secure and scalable way. Our plan is to reproduce the model developed by the Canadian open-source software project Magic Castle. The proposed solution creates virtual HPC infrastructure(s) in a public cloud, in this case on the Fenix Research Infrastructure, and generates temporary event-specific HPC clusters for training purposes, including a complete scientific software stack. The scientific software stack is fully optimised for the available hardware and will be provided by the European Environment for Scientific Software Installations (EESSI).

The ALL Load Balancing Library

The ALL Load Balancing Library
Scalability of parallel applications depends on a number of characteristics, among which is efficient communication, equal distribution of work or efficient data lay-out. Especially for methods based on domain decomposition, as it is standard for, e.g., molecular dynamics, dissipative particle dynamics or particle-in-cell methods, unequal load is to be expected for cases where particles are not distributed homogeneously, different costs of interaction calculations are present or heterogeneous architectures are invoked, to name a few. For these scenarios the code has to decide how to redistribute the work among processes according to a work sharing protocol or to dynamically adjust computational domains, to balance the workload. The A Load Balancing Library (ALL) developed within E-CAM at the Julich Supercomputing Center aims to provide an easy and portable way to include dynamic domain-based load balancing into particle based simulation codes.

EKHAM the Comics

Identifying exciting and original tools to engage the general public with advanced research is an intriguing and non-trivial challenge for the scientific community. E-CAM decided to try something unusual, and embarked on an interesting and slightly bizarre experience: collaborating with experts and artists to use comics to talk about HPC and simulation and modelling!
Comics & Science ? The E-CAM issue: an experiment in dissemination
Join us in disseminating the story of EKHAM The Wise, to pursue together our mission to promote modelling, simulation and HPC among students of all ages and interested public!

Related Articles

E-CAM article on the EU Research Magazine

E-CAM article on the EU Research Magazine
An article about E-CAM was released with the Autumn edition of the EU Research Magazine. The piece consists on an interview to Ignacio Pagonabarraga, Sara Bonella, Donal Mackernan and Jony Castagna, and describes E-CAM's work in software development, training and interactions with industry.

Featured Software Modules



For analysis of MD simulations MDTraj is a fast and commonly used analysis. However MDTraj has limitations, such as the requirement that the whole trajectory and result of the computation fits into memory. Dask-traj rewrites part of MDTraj to work with Dask in order to achieve out-of-memory computations, and combined with dask-distributed results in possible out-of-machine parallelisation, essential for HPCs and a (surprising) speed-up even on a single machine.

PerGauss, Periodic Boundary Conditions for gaussian bases

The module PerGauss (Periodic Gaussians) consists on an implementation of periodic boundary conditions for gaussian bases for the Quantics program package. In quantum dynamics, the choice of coordinates is crucial to obtain meaningful results. While xyz or normal mode coordinates are linear and do not need a periodical treatment, particular angles, such as dihedrals, must be included to describe accurately the (photo-)chemistry of the system under consideration. In these cases, periodicity can be taken into account, since the value of the wave function and hamiltonian repeats itself after certain intervals.

Load balancing for multi-GPU DL_MESO

December Module of the Month: Load balancing for multi-GPU DL_MESO
This module concerns the implementation of the E-CAM Load Balancing Library (ALL) in the multi-GPU version of DL_MESO_DPD code. The intention is to allow for better performance when modelling complex systems with DL_MESO_DPD, like large proteins or lipid bilayers, redistributing the work load across the GPUs.

Recent Publications


Quantum Monte Carlo determination of the principal Hugoniot of deuterium

Michele Ruggeri, Markus Holzmann, David M. Ceperley, and Carlo Pierleoni
Phys. Rev. B 102, 144108
Open access version

Towards blood flow in the virtual human: efficient self-coupling of HemeLB

J. W. S. McCullough, R. A. Richardson, A. Patronis, R. Halver, R. Marshall, M. Ruefenacht, B. J. N. Wylie, T. Odaker, M. Wiedemann, B. Lloyd, E. Neufeld, G. Sutmann, A. Skjellum, D. Kranzlmüller and P. V. Coveney
Interface Focus 11: 20190119
DOI: (open access)

Upcoming Online Events


High Throughput Computing with Dask

Organisers: Alan O'Cais, David Swenson
Dates: 21st January, 4th and 11th February 2021

Extended Software Development Workshop in HPC for mesoscale simulation

Organisers: Jony Castagna, Michael Seaton, Silvia Chiacchiera, Leon Petit
Dates: 18th - 22nd January 2021

All the best for 2021 !!

An image of...
Characters from the story of Ekham the wise.
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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 676531