## Sait.oat.ts.astro.it

Mem. S.A.It. Suppl. Vol. 8, 64
Two platform independent versions of ATLAS12
Institut f¨ur Astronomie, Universit¨at Wien, T¨urkenschanzstraße 17, 1180 Vienna, Austriae-mail: [email protected]
**Abstract. **ATLAS12 makes use of some non-standard features of the VAX/VMS compiler,

which is highly appreciable if one uses a VMS workstation, but causes problems of portabil-

ity that make it difficult to compile ATLAS12 on various non-VMS operating systems. This

article describes the modifications to ATLAS12 that became necessary in order to get this

code running with the open source GNU compiler (g77), which is easily available on most

Linux/Unix based systems (including Mac OS X). We also present our parallel and modu-

larised Ada95 version of ATLAS12 and give an overview of CAMAS, our new magnetic

stellar atmosphere code.

**Key words. **Methods: numerical – Stars: atmospheres – Stars: magnetic fields

it is an opacity sampling code, which is in-dispensable in order to allow for peculiar
This contribution describes the modifications
abundances in individual stars. Furthermore
that were necessary in order to convert
ATLAS12 is the de facto standard stellar atmo-
ATLAS12 into a essentially platform indepen-
sphere program and contains well tested opac-
dent code. We will not discuss the usage of
ity routines. On account of this ATLAS12 is
ATLAS12 and the underlying physics, since
considered a good starting point and compari-
they are well described in the publications of
son for our opacities and models.

In order to adapt the ATLAS12 code to
ber of articles in this volume. Here we focus
fit our needs some known problems had to be
on our changes to the original version of the
overcome: (a) The equation of state incorpo-
ATLAS12 code. Finally salient features of our
rated in ATLAS does not allow for depth de-
ATLAS related magnetic stellar atmosphere
pendent abundances. (b) The depth and fre-
code CAMAS are shortly discussed.

quency resolutions are limited by the fixed ar-ray lengths and the pretabulated matrix used by
1.1. ATLAS12: advantages &
the radiation transport subroutine (JOSH). (c)
ATLAS12 reads the line data from binary files.

The data files distributed with ATLAS are big
ATLAS12 was chosen as a non-magnetic com-
files, which can cause problems, since
parison to our new magnetic atmosphere code
most of the PCs using Intel or AMD proces-
CAMAS for several reasons: most importantly,
1 The endianness describes where the most signif-
icant bit is located. Big end first is called big endian,
*Send o*ff*print requests to*: K. M. Bischof
e.g. the values of the 4-byte big endian integers in
K. M. Bischof: ATLAS12, platform independent
sors are little endian, and the big endian switch
– floating point and variable precision
in the file I/O command is not working in the
*[0. *→ *0.d0]*
current version of the g77 compiler. (File I/O
If this precision is not explicitly defined,
will be discussed in detail in the next section).

the g77 compiler may use any precision
Evidently, in the absence of a VMS
and the code may yield different results
FORTRAN compiler, the platform dependence
from the VAX/VMS FORTRAN version.

was the problem that had to be solved first. In a
Thus the precision of all floating point lit-
further step, ATLAS12 was successfully ported
erals has been defined.

to Ada95, an object oriented parallel language.

– declaration and initialisation of all
variables*[replace "IMPLICIT REAL*8" statement]*
**2. FORTRAN77 version**

The "IMPLICIT REAL*8" statementcauses a compilation problem. It was
It is becoming more and more common to
therefore removed. We also decided to
replace old VMS workstations with systems
explicitly initialise the variables that need
running under Linux or Mac OS. Faced with
to be set to zero, because the defaults for
the same portability problems as e.g.
the "-finit-local-zero" switch of the g77
we chose to abandon VAX/VMS-
compiler may be different on different ma-
specific FORTRAN commands and to estab-
chines. The declaration and initialisation of
lish a FORTRAN77 version that can be com-
all variables also made the modularisation
piled using the free GNU FORTRAN com-
of the code and consequently the porting
piler (g77), since this is the most easily avail-
to Ada95 feasible.

able compiler for Linux/Unix based systems
– "dummy arrays" and data types
(including Mac OS X). Therefore we consider
*[var(1) *→ *var(*), Real*8 *→ *Double*
this version useful for astronomers having no
*Precision, *. .*]*
access to (proprietary) VAX/VMS compatible
The VAX/VMS FORTRAN syntax for
FORTRAN compilers.

the declaration of "dummy arrays" causes
Our platform independent g77 version of
compiler errors or warnings and was there-
ATLAS12 can be downloaded from our home-
fore replaced. The data types Real*4 and
Real*8 are deprecated - consequently both
data types were replaced with "DoublePrecision" for variables that do not appearin common-blocks.

2.1. Distinctions between VAX/VMS-
– addressing two-dimensional arrays
*[NNN(1) *→ *NNN(1,1) ]*
Due to the absence of the additional functional-
A two-dimensional array cannot be ad-
ity provided by the VAX/VMS compiler these
dressed like a one-dimensional array in
non-standard features have to be emulated by
standard FORTRAN77. In contrast to g77
adding the corresponding commands directly
FORTRAN, where one needs two indices
into the code. Most changes concern the defi-
to address a two-dimensional array, it is
nition and the handling of the variables. Some
possible in VAX/VMS FORTRAN to ad-
additional portability problems were caused by
dress such arrays using only one index.

the use of functions provided by the underlying
Since ATLAS12 makes use of this short-
operating system (e.g.,"ABORT").

hand, these array-references had to bechanged.

The most important modifications that
– values of variables in subroutines
were necessary in order to port the code to g77
*["SAVE var"]*
There are two ways of memory allocation:static allocation, which is the VAX/VMS
the ATLAS12 data files are computed by "1*st *byte *224 + 2*nd *byte * 216 + 3*rd *byte * 28 + 4*th *byte"
default and allows subprograms to retain
K. M. Bischof: ATLAS12, platform independent
Fig. 1. The results of 25 iterations on a 10 000 K main sequence model with solar abundances. This plotshows the small differences in the flux error (upper panel) and in the flux derivatives (lower panel) betweenthe model computed with the VMS compiler and with the Linux g77 compiler after 25 iterations. Thedashed lines indicate the respective convergence limits. It can be seen that the differences do not precludeconvergence; being very small they can be interpreted as due to different floating point representations onthe two machines.

variable values, and stack allocation, which
endianness is not recognised by the g77
is the g77 default and does not retain val-
compiler, and so these files are now read
ues of variables defined in subprograms un-
byte by byte on little endian machines, after
less they are declared using the "SAVE"
which a byte-reordering routine is applied.

command. Since ATLAS12 was originally
Tests of the read routines showed that out
written for a VMS workstation it assumes
of approx. 9 million selected lines from
that subroutines are able to retain the val-
highlines.dat and lowlines.dat only 3 lines
ues of all their "private" variables until the
were selected differently by the Linux
next call. When translating the code to the
and VAX/VMS codes when computing a
g77 FORTRAN version we checked which
10 000 K main sequence star model. This
variables are reused after the function-call
negligible discrepancy most probably re-
and retained only the values of these vari-
sults from the different floating point rep-
ables because saving all variables was con-
resentations of the machines.

sidered a waste of memory.

– replace system dependent calls
– different I/O-format and file-format
*[ABORT *→ *EXIT(0)]*
*[reorder bytes after reading]*
Some statements in ATLAS12, mainly the
The binary files distributed by R. L. Kurucz
routines that help the user to compute the
contain big endian encoded integers. The
runtime, and the exit statements, contain
read option that allows the selection of the
K. M. Bischof: ATLAS12, platform independent
Fig. 2. The results of 25 iterations on a 10 000 K main sequence model with peculiar abundances (C, N,O: −1 dex; Cr, Fe, Ni: +1 dex). This plot shows that the differences in the flux error (upper panel) and inthe flux derivatives (lower panel) also remain small if the abundances are changed in the ATLAS9 startingmodel. (In Fig. no changes to the starting model were made.)
VAX/VMS system calls. These had to be
workstation and the g77 FORTRAN code run-
replaced by their Unix/Linux equivalents.

ning on a Debian Linux PC.

– GOTO cannot jump into if-block with
The resulting models computed on these
different platforms were compared. In Fig.
In the subroutine PFGROUND it may oc-
and Fig. the results after 25 iterations on a
cur that a GOTO statement leads into
converged ATLAS9 10 000 K main sequence
an if-block with unmet condition. The
model with (a) solar abundances and (b) pe-
VAX/VMS compiler allows this action
culiar abundances (C, N, O: −1 dex; Cr, Fe,
whereas the g77 compiler refuses to
Ni: +1 dex) are shown. There are no visible
compile this construct. Therefore minor
differences between any of the output models.

changes to the program structure proved
The only variables where small differences can
be seen are the flux error and the flux deriva-tive. These differences are of the order of a fewparts per thousand, which is about the order
of magnitude one would expect from different
(VAX/VMS compared to g77)
floating-point representations and different nu-merical precision. Since the convergence cri-
In order to test whether the porting was suc-
teria (marked with dashed lines in the figures)
cessful a comparison was made between the
are one part per thousand in flux error and 0.1
VAX/VMS code running on a DEC VMS
in flux derivative, it is obvious that these differ-
K. M. Bischof: ATLAS12, platform independent
same time it becomes fairly easy to test the ef-fects that occur if one replaces the subroutinesused in ATLAS12 with the ones used in ourcodes. In the present case an example for these*replaceable parts *is the solver for the radia-tion transport (JOSH) which was replaced by aFeautrier solver. An example for the *insertionof packages *is the Ng acceleration.

3.1. Feautrier solver
If one intends to calculate models with dif-ferent numbers of depth points, it can beconsidered a serious drawback of the JOSH
Fig. 3. Structure of our version of ATLAS12. The
routine that the grid resolution cannot be
location of the newly included / replaced packages
specified at runtime. This radiation transport
with standard interfaces mentioned in is in-
solver interpolates the values from the opti-
dicated. JOSH and Feautrier are radiation transport
cal depth scale of the model onto a fixed set
routines, Ng is an iteration acceleration routine.

of depth points where the integration matri-ces used in this method (see )are pretabulated. Therefore we replaced this
ences may safely be ignored. Fig. as well as
routine with the non-magnetic Feautrier solver
Fig. display these negligible differences.

). This solver allows for achange of the grid-resolution without recompi-
**3. Parallel Ada95 version**

lation, whereas the JOSH routine would neednew hard-coded integration matrices.

For reasons explained in detail in
Due to the different numerical errors and
different grid resolutions these solvers yield
ing line synthesis code COSSAM
slightly discrepant results.

and radiative diffusion codeCARAT are written inAda95. In order to include the Kurucz opacity
3.2. Ng acceleration
routines into our codes, the whole of ATLAS12
The implementation of the iteration scheme
was ported to this programming language.

proposed ) accelerates the conver-
Ada95 is an object oriented language
gence of our models by 10 to 50 %.

which encourages modularisation and facili-
This scheme uses the results of four (or
tates the parallelisation of the code. As all
more) iterations of a function *f *(. ., *f*
modern computing languages, Ada95 allows
one to determine the needed array-sizes at run-
*n*−1, *fn*) to construct a new function ¯
closer to the converged function (see ).

time and is therefore able to minimise the
The iteration process can be written as:
memory requirements and to handle any num-ber of frequencies (up to the limits imposed by
*A fn*−1 = *fn*
the hardware used).

The *modularisation *of our Ada95 version
where *f *(*x*) represents a real function and *A *a
of ATLAS12 is a big advantage since establish-
(non)linear operator. If *A *can be assumed to be
ing interfaces for all subroutines ("encapsu-
linear (or at least a linear approximation to *A*
lation") simplifies the exchange and insertion
exists) it is possible to calculate the optimum
of subroutines into existing codes. This new
values of the weighting constants *c*1, *c*2, . .

program architecture provides *reusable pack-*
The application of the operator *A *to the func-
*ages *(e.g. the continuum package) and at the
tions on the right hand side of can be
K. M. Bischof: ATLAS12, platform independent
CAMAS with(out) Ng
= ∆0 + *c*1(∆1 − ∆0) + *c*2(∆2 − ∆0)+ . .

0 := *fn *− *fn*−1. The best weights *c*1, *c*2, . .

can be found by using the condition that the
effect of the operator *A *on the new function
¯*f *has to be minimised. This can be written as
k*A *¯*f *− ¯*f*k2 → min.

Eq. yields the following system of equa-
tions if the derivatives with respect to the
weights *c*1, *c*2, . . are calculated:
Fig. 4. Application of the Ng-acceleration. The be-
∆0(∆1 − ∆0)d*x *= *c*1 (∆1 − ∆0)(∆1 − ∆0)d*x*
haviour of the flux errors during the iteration pro-
cess is shown for a model with Ng-acceleration and
a model, were this acceleration was not used. The
1 − ∆0)(∆2 − ∆0)d*x*
sudden declines of the errors are produced by the
application of the Ng-acceleration.

∆0(∆2 − ∆0)d*x *= *c*1 (∆1 − ∆0)(∆2 − ∆0)d*x*
+ *c*2 (∆2 − ∆0)(∆2 − ∆0)d*x*
The integrals arise from the definition of the in-
ner product. This system is solved in the stan-
Fig. 5. The Ng acceleration scheme. This scheme
dard way (since all differences ∆*i *are known).

uses the results of four (or more) iterations (. ., *f*
Using the calculated weights *c*
1, *c*2, . . the new
input function for the next iteration step is cal-
*n*−2, *fn*−1, *fn*) to construct a new function ¯
closer to the converged function. *A *is a linear op-
erator that represents or at least approximates theiteration. The differences between two consecutive
*fn*+1 = (1 − *c*1 − *c*2 − . .) *fn*
iteration results *fn*−1 and *fn *are denoted by ∆0.

+ *c*1 *fn*−1 + *c*2 *fn*−2 + . .

Test calculations show that the application of
computed using Eq. This leads to Eq.
the Ng scheme can save up to 50% of the com-
putation time. In Fig. one can easily see that
*f *= (1 − *c*1 − *c*2 − . .) *fn*−1
after the usage of the Ng routine there is a dra-
+ *c*1 *fn*−2 + *c*2 *fn*−3 + . .

matic decline in the flux errors. If the devia-
*A *¯*f *= (1 − *c*
tions of the computed function from the con-
1 − *c*2 − . .) *fn*
verged function are small, the influence of the
1 *fn*−1 + *c*2 *fn*−2 + . .

nonlinearity of *A *gets stronger and the applica-
The converged function satisfies *A f *= *f *.

tion of the Ng routine is no longer able to speed
The difference between the not fully converged
up the process.

function ¯*f *and the expected result after ap-plication of the linear operator *A *¯*f *can be ex-
3.3. Parallelisation
Porting the code to Ada95 has another ad-
*A *¯*f *− ¯*f *= (1 − *c*1 − *c*2 − . .)∆0 + *c*1∆1 + *c*2∆2
vantage: with a modularised Ada95 code it is
easy to create a thread-parallel version. Since
K. M. Bischof: ATLAS12, platform independent
opacity calculations over the available CPUsand the addition of the subtotals from the dif-ferent CPUs (indicated by the small box be-low the boxes labelled "CPU1" and "CPU2"in Fig.
In a further step the line-selection has also
been parallelised. Obviously this results in a
Fig. 6. The effect of the parallelisation on the run-
runtime distribution very similar to the runtime
time distribution. The diagram on the left shows that
distribution in the sequential case. The saving
a sequential version of ATLAS12 spends most of
of total computation time behaves analogously
the CPU time on opacity sampling in the frequency
to the decrease of integration time described in
loop. Parallelisation of this loop saves a consider-
the last paragraph.

able amount of wall clock time. Due to the smallsynchronisation overhead the decrease of the run-time depends linearly on the number of processors.

3.4. Examples (VAX/VMS compared to
The diagram on the right shows that using a second
CPU saves half the wall clock time spent on opacitysampling.

For comparison 25 iterations were carried outon an ATLAS9 10 000 K main sequence modelwith (a) solar abundances and (b) peculiarabundances (C, N, O: −1 dex; Cr, Fe, Ni:+1 dex). In Fig. well as in Fig. can beseen that the differences to the original versionbecome larger, which is most probably due tothe different available data types, but are stillunimportant. The higher numeric precision ofthe data types declared in the Ada95 versionsuggests that the results of the Ada95 code areless subject to rounding errors.

Fig. 7. Program structure of the parallelised version
**4. CAMAS - a "magnetic" atmosphere**

of ATLAS12. The opacity calculations (and opac-
ity integrations) are distributed over the availableCPUs. The summation of the subtotals from the dif-
Working on magnetic CP stars one has to com-
ferent CPUs is indicated by the small box under the
pute the influence of the magnetic field on
boxes labelled "CPU1" and "CPU2".

the structure of the atmospheres. Therefore wehave established a new magnetic stellar atmo-sphere code called CAMAS (Codice per le
ATLAS12 spends most of the computation
Atmosfere Magnetiche Stellari).

time on opacity sampling (see Fig. this part
This can be regarded as an ATLAS re-
of the program was parallelised. As the calcu-
lated code, since it presently makes use of
lations of the opacities at different wavelengths
the ATLAS12 continuous opacities. The line
do not depend on each other, there is very little
lists for CAMAS were extracted from VALD
synchronisation overhead and the computation
(and the line opacity rou-
time needed for the integration of the opacities
tines were taken from the COSSAM code. The
over all frequencies decreases linearly with the
chemical equilibrium calculations in CAMAS
increase of the number of processors used by
are different from ATLAS. CAMAS uses an
the program. Figure 7 shows the structure of
equation of state with hydrogen chemistry
our version ATLAS12 version in Ada95. The
(Mihalas 1967). For the temperature correction
difference between the parallel version and the
procedure a variant of the Lucy Uns¨old method
sequential version lies in the distribution of the
(Dreizler 2003) is employed.

K. M. Bischof: ATLAS12, platform independent
Fig. 8. Comparison of the Ada95 model to the FORTRAN models: results of 25 iterations on a 10 000 Kmain sequence model with solar abundances. (Analogous to Fig. The differences between the Ada95model and the VMS model are larger than the differences between the FORTRAN models. This is probablydue to different data types of higher numeric precision declared in Ada95 and the different mathematicallibraries.

So far the influence of the magnetic field
kinds of Linux/Unix based systems (includ-
on the atmospheric structure is not fully
ing Mac OS X). The Ada95 version also offers
taken into account. Magnetic line blanket-
some additional functionality. It is platform in-
ing is included but Lorentz forces are ne-
dependent, split up in modules and runs in par-
glected. The Zeeman Feautrier solver for the
allel on multi-processor machines. Any limita-
polarised radiation transfer equation has been
tions as to the maximum number of depth and
taken from the CARAT code
frequency grid-points and the number of lines
the line opacity calcula-
that can be treated have been pushed far be-
tions are based on Component by Component
yond what is possible with the original version.

Sampling. CAMAS is producing converged
The incorporation of the continuous opacity
models but it still has to be improved by adding
routines of ATLAS12 in our new CAMAS
some missing physics (e.g. magnetic pressure)
code for magnetic atmospheres makes it pos-
and to be tested thoroughly.

sible to compare our future models with thoseof R. L. Kurucz.

Our g77 FORTRAN code produces the
M. J. Stift and R. L. Kurucz are gratefully acknowl-
same models as the original VAX/VMS
edged. The VAX/VMS models were computed with
FORTRAN code. Therefore it can safely be
the help of E. A. Dorfi and his working group. This
used for calculating ATLAS12 models on all
work has been supported by the *Austrian Science*
K. M. Bischof: ATLAS12, platform independent
Fig. 9. Comparison of the Ada95 model to the FORTRAN models: results of 25 iterations on a 10 000 Kmain sequence model with peculiar abundances (C, N, O: −1 dex; Cr, Fe, Ni: +1 dex). One can see that thedifferences between the results of the codes do not get larger than one would expect due to the different datatypes and mathematical libraries.

*Fund (FWF)*, project P16003 "Radiative diffusion
Kupka, F. G., Ryabchikova, T. A., Piskunov,
in magnetic stellar atmospheres".

N. E., Stempels, H. C., & Weiss, W. W.

2000, Baltic Astronomy, 9, 590
These programs can be downloaded from:
Kurucz, R. L. 1970, SAO Special Report, 309,
Mihalas, D. 1967, Methods in Computational
Ng, K.-C. 1974, J. Chem. Phys., 61, 2680Sbordone, L., MSAIS, 8, 61
Alecian, G., & Stift, M. J. 2002, A&A, 387,
Stift, M. J. 1998, Contributions of the
Astronomical Observatory Skalnate Pleso,
Alecian, G., & Stift, M. J. 2004, A&A, 416,
Stift, M. J., & Dubois, P. F. 1998, Computers
in Physics, 12, 150
Stift, M. J. 2000, A peculiar Newsletter, 33
Dreizler, S. 2003, ASP Conf. Ser. 288: Stellar
Atmosphere Modeling, 288, 69
Wade, G. A., Bagnulo, S., Kochukhov, O.,
Feautrier, P. 1964, SAO Special Report, 167,
Landstreet, J. D., Piskunov, N., & Stift, M. J.

2001, A&A, 374, 265

Source: http://sait.oat.ts.astro.it/MSAIS/8/PDF/64.pdf

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