EUFORIA FP7-INFRASTRUCTURES-2007-1, Grant 211804 JRA4 Overview and plans M. Haefele, E....

EUFORIA FP7-INFRASTRUCTURES-2007-1, Grant 211804

JRA4 Overview and plans

M. Haefele, E. Sonnendrücker

Euforia kick-off meeting

22 January 2008

Gothenburg


Outline

Presentation of JRA4 tasks

Task 1: Existing visualization tools

Task 2: Visualization & Kepler platform

Task 3: Lossy data compression format

Task 4: 4D and 5D visualization


Outline







PurposeProvide visualization support for project

Unified visualization framework for all codes to be integrated

Post-processing visualization

Integration of visualization tools in Kepler workflow

Monitoring

Steering


Outline







Python Matplotlib Pure Python library based on numpy

Can be used in

python scripts

web application server that can call python

Syntax close to Matlab visualization tools

=> Replace Matlab visualization for free !

Only 2D plots are available

3D plots will use the VTK library


Python matplotlib


VTK : Visualization Toolkit Open source C++ library

Community of more than 1000 developers

Architecture managed by a private company : Kitware

Exists and evolves since 1998

=> powerful and stable tool


ParaView Software based on parallel VTK

Can be seen as a GUI for VTK

The user designs the VTK pipeline by himself

The user must know the different pieces of the pipeline

Great flexibility

Parallelization of both processing and rendering

Plugin system based on the use of new VTK classes

Open source software designed by Los Alamos Lab and Kitware


Paraview


VisIt Software based on parallel VTK

Tool to visualize different kind of data

The VTK pipeline is hidden from the user

More user friendly

Less flexibility

Parallelization of processing (remote processing)

The plugin system proposes an intermediate layer on top of VTK

Open source software designed by Lawrence Livermore Lab


VisIt


Task1: Work plan

List visualization requirements of codes in platform

Develop data (MDS+, UAL) import plugin for

Matplotlib

VisIt

Develop sample visualizations for typical data in Matplotlib and VisIt

Write tutorials


Outline







Monitoring tools

Visualization during the simulation

Check if the simulation is still OK

1D, 2D (light) dataset are enough

Visualization can be performed on the gateway

Visualization must be integrated to Kepler

Which quantities are reliable for code monitoring ?

Which tools have to be integrated into kepler ?


Interpretation tools Visualization after the simulation

Huge dataset generated by distributed simulations

1. Copy every dataset to a central visualization resource

Requires big storage and network bandwidth

Requires a single visualization resource

2. Leave dataset on the remote simulation resource

Requires no extra storage or network bandwidth

Requires remote visualization resource


Visualization strategy

In both case, we suggest to use an existing tool based

on VTK: VisIt (or ParaView)

Example of CSCS (J. Favre)

Shared remote visualization resource strategy

Data reading, processing and rendering are performed at the computer center

Only resulting pictures go through the network

Interactive visualization performed with ParaView


Remaining questions

Build a link between visualization tool and Kepler in order to keep track of generated pictures ?

What are physicists looking for in the data ?


Outline







Large dataset management

Size S of a uniformly discretized function in Bytes

d=2, N=128 => 128 KB

d=3, N=128 => 16 MB

d=4, N=128 => 2 GB

d=4, N=256 => 32 GB

d=6, N=128 => 32 TB

S=NdF


Large dataset management

Strategy : Use data compression to reduce the size of the numerical problem

Hierarchical bases of finite elements

Local compression algorithm

Compression integrated into the parallel simulation

Efficient algorithm for slice reconstruction


Results for a 32 GB function

Particles beam result


Results for a 32 GB function

Laser-plasma interaction result


Present status

Interactive exploration of 4D data with 2D slices

Integration of the compression process into the parallel simulation

=> Allow the export of the distribution function

=> Without damaging the speedup of the simulation

Data reduction with a factor between 8 and 150


Task 3: Work plan

Enhance compression algorithm

Parallelization of slice reconstruction algorithm

Integration of these tools into VisIt, Kepler...

Handle 5D dataset


Outline







Specific difficulties Visualization of data coming from kinetic simulations

Particle distribution function lives in phase space

The full model requires 6D + time

Objective : visualize functions f: RR4 RR

How to visualize a 4D function ?

How to represent the large dataset (2-32GB) for an interactive visualization ?


Multidimensional visualization 4D distribution function f(r, v//)

Dimension reduction

Representation of a set of slices/projections

Data coming from Gysela5D (CEA Cadarache)


Demonstration

Demo time !

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EUFORIA FP7-INFRASTRUCTURES-2007-1, Grant 211804 JRA4 Overview and plans M. Haefele, E....

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