Creating Gateway Alliances Using WS-PGRADE/gUSE - Science Gateways for Distributed Computing Infrastructures - page 251

V Δ is filtered with a lower bound threshold and all the voxels satisfying the

￿

file for further analysis purposes (as shown in the
resulting bottom image of Fig. 18.2 ).

filters are saved in a text

Several renderings of V Δ are performed:
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￿

Volume rendering;

Isosurface rendering of the density field to produce panoramic movies using

different isovalues (as shown in the resulting bottom image of Fig. 18.2 );

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Orthoslice rendering, i.e., orthogonal slice planes through the volume dataset.

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18.4.2 Stellar Evolutionary Simulations

The availability of large sets of stellar evolution models spanning a wide range of
stellar masses and initial chemical compositions is a necessary prerequisite for any
investigation aimed at interpreting observations of galactic and extragalactic, both
resolved and unresolved stellar populations. A stellar evolutionary simulator pro-
duces one synthetic model (SM).
Frascati Raphson Newton Evolutionary Code (FRANEC) is a state-of-the-art
(Pietrinferni 2004, 2006, 2013) numerical code for stellar astrophysics. This code is
perfectly suited for computing evolutions of stars on the basis of a number of
different physical inputs and parameters. A single run of FRANEC produces one
synthetic model (SM). To produce an isochrone, for a given chemical composition,
through a full isochrone run (FIR), it is necessary to execute a large number of SM
runs, varying the initial mass of the stellar models, which requires expensive com-
putations on DCIs. Once these evolutionary tracks and isochrones (and other
additional data) are computed, they can be distributed in datasets over different sites.
The computations of stellar models produce simulation output files with a set of

associated metadata. Such metadata are linked to all parameters concerning the
numerical evolutionary code. In this way it is possible to store and easily search and
retrieve the obtained data by many sets of stellar simulations, and furthermore to get
access to a large amount of homogeneous data, such as tracks and isochrones
computed by using FRANEC.
The FRANEC workflow has a modular architecture, making it easy to identify
reusable modules for building other workflows.
Modules can be differentiated on the basis of their functionality:

1. The EOS computation module provides the equation of State in tabular form.
The input values are the metallicity Z and the type of mixture (distribution of
chemical elements heavier than helium).
2. The OPACITY Computation module produces a table of opacity from precal-
culated tables. Given the Metallicity value Z and the type of mixture it obtains a
new table of opacity that is interpolated from the precalculated ones.
3. FRANEC is the core module of the workflow. It produces the models of stellar
evolution starting from the outputs of the two modules EOS and OPACITY and a