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OK. I think it could be a "memory - cache" related problem.<br>
<br>
I did the same test with lower cut-off (still 6 CPUs).<br>
Now my serial run used 0.2 % of the memory and my parallel around
1.3% <br>
<br>
The parallelization over the fft grid is still faster, but the kpts
parallelization now is faster than the serial run.<br>
Serial: PWSCF : 1m 3.14s CPU
time, 1m 4.05s WALL time<br>
fft grid parallelization: PWSCF : 15.46s CPU time,
16.36s WALL time<br>
kpts parallelization: PWSCF : 35.98s CPU
time, 36.47s WALL time<br>
<br>
Thank you and best regards,<br>
Davide<br>
<br>
<br>
On 02/14/2011 02:49 PM, Gabriele Sclauzero wrote:
<blockquote cite="mid:50807287-9445-4387-890A-C72DDD91F789@sissa.it"
type="cite">Dear Davide,
<div><br>
</div>
<div> it might be a memory-contention problem, since CPU cache
sizes are of the order of a few MB. Please provide the detailed
timings at the end of the runs (that are the first thing one
should look at in order to interpret these kind of speedup
tests).</div>
<div><br>
</div>
<div>Next time please take a few seconds to sign your post using
full name and affiliation.</div>
<div><br>
</div>
<div>Regards,</div>
<div><br>
</div>
<div>GS</div>
<div><br>
</div>
<div><br>
<div>
<div>Il giorno 14/feb/2011, alle ore 12.18, Davide Sangalli ha
scritto:</div>
<br class="Apple-interchange-newline">
<blockquote type="cite">
<div>Thank you for the answer.<br>
<br>
I did a check to be sure, but these jobs use only few MB
of memory.<br>
The serial run uses just 2.5% of my node memory (so around
15% for the <br>
run on 6 CPUs).<br>
It does not seems to me that this could be the problem.<br>
Moreover in the fft parallelization the memory was not
distributed neither.<br>
<br>
Is it possible that pwscf is not properly compiled?<br>
Is there any other check that you would suggest to do?<br>
<br>
Best regards,<br>
Davide<br>
<br>
*************************************<br>
Largest allocated arrays est. size (Mb)
dimensions<br>
Kohn-Sham Wavefunctions 5.68 Mb (
6422, 58)<br>
NL pseudopotentials 13.33 Mb (
6422, 136)<br>
Each V/rho on FFT grid 7.81 Mb (
512000)<br>
Each G-vector array 1.76 Mb (
230753)<br>
G-vector shells 0.09 Mb (
12319)<br>
Largest temporary arrays est. size (Mb)
dimensions<br>
Auxiliary wavefunctions 22.73 Mb (
6422, 232)<br>
Each subspace H/S matrix 0.82 Mb (
232, 232)<br>
Each <psi_i|beta_j> matrix 0.12 Mb
( 136, 58)<br>
Arrays for rho mixing 62.50 Mb (
512000, 8)<br>
writing wfc files to a dedicated directory<br>
<br>
<br>
On 02/14/2011 11:34 AM, Paolo Giannozzi wrote:<br>
<blockquote type="cite">Davide Sangalli wrote:<br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite">
<blockquote type="cite">What could my problem be?<br>
</blockquote>
</blockquote>
<blockquote type="cite">the only reason I can think of is
that k-point parallelization doesn't<br>
</blockquote>
<blockquote type="cite">(and cannot) distribute memory, so
the total memory requirement will<br>
</blockquote>
<blockquote type="cite">be npools*(size of serial
execution). If you run on the same node six<br>
</blockquote>
<blockquote type="cite">instances of a large executable,
memory conflicts may slow down more<br>
</blockquote>
<blockquote type="cite">than parallelization can speed up.<br>
</blockquote>
<blockquote type="cite"><br>
</blockquote>
<blockquote type="cite">P.<br>
</blockquote>
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</blockquote>
</div>
<br>
<div>
<span class="Apple-style-span" style="border-collapse:
separate; color: rgb(0, 0, 0); font-family: Helvetica;
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<div><span class="Apple-style-span" style="color: rgb(126,
126, 126); font-size: 16px; font-style: italic;"><br
class="Apple-interchange-newline">
§ Gabriele Sclauzero, EPFL SB ITP CSEA</span></div>
<div><font class="Apple-style-span" color="#7e7e7e"><i> PH
H2 462, Station 3, CH-1015 Lausanne</i></font></div>
</span>
</div>
<br>
</div>
<pre wrap="">
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</pre>
</blockquote>
<br>
<br>
Davide Sangalli<br>
MDM labs, IMM, CNR.<br>
Agrate (MI) Italy<br>
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