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SWIFT
SWIFTsim
Commits
bdf1fe16
Commit
bdf1fe16
authored
9 years ago
by
Pedro Gonnet
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Merge branch 'pasc_paper' of gitlab.cosma.dur.ac.uk:swift/swiftsim into pasc_paper
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PASC paper
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bdf1fe16
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@@ -553,13 +553,13 @@ architectures for a representative cosmology problem.
...
@@ -553,13 +553,13 @@ architectures for a representative cosmology problem.
The initial distribution of particles used in our tests is extracted and
The initial distribution of particles used in our tests is extracted and
resampled from low-redshift outputs of the EAGLE project
\cite
{
Schaye2015
}
, a
resampled from low-redshift outputs of the EAGLE project
\cite
{
Schaye2015
}
, a
large suite of state-of-the-art cosmological simulations. By selecting outputs
large suite of state-of-the-art cosmological simulations. By selecting outputs
at late times, we constructed a simulation setup which is
representative of the
at late times
(redshift
$
z
=
0
.
5
$
)
, we constructed a simulation setup which is
most expensive part of these simulations, i.e. when the
particles are
representative of the
most expensive part of these simulations, i.e. when the
highly-clustered and no longer uniformly distributed. This
distribution of
particles are
highly-clustered and no longer uniformly distributed. This
particles is shown on Fig.~
\ref
{
fig:ICs
}
and periodic boundary
conditions are
distribution of
particles is shown on Fig.~
\ref
{
fig:ICs
}
and periodic boundary
used. In order to fit our simulation setup into the limited
memory of some of
conditions are
used. In order to fit our simulation setup into the limited
the systems tested, we have randomly down-sampled the particle
count of the
memory of some of
the systems tested, we have randomly down-sampled the particle
output to
$
800
^
3
=
5
.
12
\times
10
^
8
$
,
$
600
^
3
=
2
.
16
\times
10
^
8
$
and
count of the
output to
$
800
^
3
=
5
.
12
\times
10
^
8
$
,
$
600
^
3
=
2
.
16
\times
10
^
8
$
and
$
376
^
3
=
5
.
1
\times
10
^
7
$
particles respectively. Scripts to generate these initial
$
376
^
3
=
5
.
1
\times
10
^
7
$
particles respectively. Scripts to generate these initial
conditions are provided with the source code. We then run the
\swift
code for
conditions are provided with the source code. We then run the
\swift
code for
100 time-steps and average the wall clock time of these time-steps after having
100 time-steps and average the wall clock time of these time-steps after having
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