On this page you will find PRACE White Papers related to Visualisation.
Title: Visualization of output from Large-Scale Brain Simulations
Authors: SimonBenjaminssona, David Silversteina, PawelHermana, Paul Melisb, Vladimir Slavnićc,Marko
Spasojevićc, KirilAlexievd, Anders Lansnera,
a Dept of Computational Biology, CSC,KTH Royal institute of Technology
b Visualization Group, SARA, SciencePark 140, 1098 XG, Amsterdam, The Netherlands
c Scientific Computing Laboratory,Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 1108,Belgrade, Serbia
d Department of Mathematical Methodsfor Sensor Information Processing, Institute of Information and Communication Technologies, 25AAcad.G.Bonchev Str., Sofia 1113, Bulgaria
Authors: This project concerned the development of tools for visualization of output from brain simulations performed on supercomputers. The project had two main parts: 1) creating visualizations using large-scale simulation output from existing neural simulation codes, and 2) making extensions to some of the existing codes to allow interactive runtime (in-situ) visualization. In 1) simulation data was converted to HDF5 format and split over multiple files. Visualization pipelines were created for different types of visualizations, e.g. voltage and calcium. In 2) by using the VisIt visualization application and its libsim library, simulation code was instrumented so that VisIt could access simulation data directly. The simulation code was instrumented and tested on different clusters where control of simulation was demonstrated and in-situ visualization of neural unit’s and population data was achieved.
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Title: In-situ Visualization State-of-the-art and Some Use Cases
Authors: MarziaRivia, Luigi Caloria, Giuseppa Muscianisia,Vladimir Slavnicb
aCINECA, via Magnanelli 6/3,40033 Casalecchio di Reno, Italy
bScientific ComputingLaboratory, Institute of Physics Belgrade, University of Belgrade,Pregrevica 118, 1108, Belgrade, Serbia
Abstract: In this paper we present an investigation about techniques and frameworks supporting in situ-visualization. With this term we mean that visualization is coupled with simulation and it occurs whilst the simulation is running. By coupling these together we can utilize the high performance computing for post processing, and we can circumvent the bottlenecks associated with storing and retrieving data in disk storage. Moreover it allows monitoring the simulation in-situ, performing not only visualization, but analysis of the incoming data as it is generated so that the simulation may be stopped or modified, thereby conserving CPU resources. In particular we have tested two techniques, by exploiting different visualization tools on two applications. The first one is the astrophysics code Pluto instrumented by using a ParaView plug-in called ICARUS, the second one is the neural simulator code BrainCore instrumented by using a library of VisIt.
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Find this document on Zenodo, DOI 10.5281/zenodo.6303483.
Title: Parallel Visualization of Petascale Simulation Results from GROMACS NAMD and CP2K on IBM Blue Gene P using VisIt Visualization Toolkit
Authors: Dr. ValentinPavlov, Dr. Miroslav Iliev, Anton Tomov, Veslin Slavchev, DimitarDimitrov, Nina Ilieva
NCSA, Acad. G. Bonchev str., bl. 25A,Sofia 1113, Bulgaria
Authors: Visualization is a key post-processing activity for petaflops simulations. In this paper we have researched, identified and implemented a methodology suitable for carrying out this activity, based on the VisIt open-source visualization tool by LLNL. We have installed the toolkit on a specialized hardware in NCSA’s Tier-1 facilities in Sofia, integrating it with our primary Tier-1 system, an IBM Blue Gene/P. We have researched the possibility to support GROMACS, CP2K and NAMD data formats and proposed best practice procedures. The experience and methodology is documented and can be used to integrate the tools into other PRACE facilities.
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Find this document on Zenodo, DOI 10.5281/zenodo.6303458.
Title: In-situ visualization using Damaris: The Code_Saturne use case
Author: Joshua C Bowdena, Francois Tessiera, Charles Deltela, Simone Bnàb, Gabriel Antoniua
aInria, Rennes – Bretange Atlantic, Campus de Beaulieu Rennes, 35042, cedex, France
bSuperComputing Application and Innovation Department, Cineca, Via Magnanelli 6/3, 40133, Casalecchio di Reno, Bologna, Italy
Abstract:
As the exascale era approaches, maintaining scalable performance in data management tasks (storage, visualization, analysis, etc.) remains a key challenge in sustaining high performance for the application execution. To address this challenge, the Damaris middleware leverages dedicated computational resources in multicore nodes to offload data management tasks, including I/O, data compression, scheduling of data movements, in-situ analysis, and visualization. In this study we evaluate the benefits of Damaris to improve the efficiency of in-situ visualization for Code_Saturne, a fluid dynamics modeling environment. The experiments show Damaris to adequately hide the I/O processing of various Paraview processing pipelines in Code_Saturne. In all cases the Damaris enabled version of Code_Saturne was found to be more efficient than the identical non-Damaris capable version when running the same Paraview pipeline.
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Find this document on Zenodo, DOI 10.5281/zenodo.5547432.