NWChem/web/benchmarks/ddscf/bench.html
2006-01-12 20:39:06 +00:00

163 lines
6.3 KiB
HTML

<!DOCTYPE HTML SYSTEM "legacy.dtd">
<HTML>
<!-- DO NOT EDIT: this is a cleared public file -->
<HEAD><TITLE>scf benchmarks</TITLE></HEAD>
<BODY BACKGROUND="../../backgrounds/zsm.gif" BGCOLOR="FAEBD7">
<UL>
<LI><A HREF="../index.html">Return to NWChem benchmarks</A>
<LI><A HREF="../../nwchem.html">Return to NWChem home page</A>
</LI></UL><HR>
<H1>Massively-Parallel Self-Consistent Field Benchmarks</H1>
<P><I>The scaling of the distributed-data SCF is illustrated,
including some very fast in-core calculations on the CRAY-T3D (e.g.,
the total time for a 324 function, DZP basis, SCF on <I>C14F6H8</I> is
just 5.5 minutes). The excellent scaling of large in-core
calculations also proves that the direct algorithm will benefit fully
from the introduction of faster integral technology into NWChem.</I>
<H2>Background</H2>
<P>As part of our <A HREF="../../hpcci/hpcci.html">High-Performance
Computing and Communications Collaboration</A> we have collected a set
of benchmark calculations to use to help in establishing design goals
and in tracking performance. A paper is in preparation which compares
the performance of NWChem with other computational chemistry packages
on a variety of parallel computers. The current document picks out
certain interesting highlights.
<H2><I>Si108O194H81C5N</I> - zeolite fragment</H2>
<UL>
<LI> 2053 functions, minimal basis
<LI> 389 atoms, no symmetry
</UL>
<P>This system was of interest to PNNL researchers as an early
cluster model for reactions inside minerals. It is a fragment of the
zeolite ZSM-5, terminated with hydrogen atoms and with an embedded
pyridine molecule. The high sparsity and small basis caused
the previous version of NWChem to spend most of its time accessing
global arrays, but the current version spends less than 1.6% of the
time in global array accesses (CRAY-T3D, 256 nodes).
<P>This calculation would not be possible with a replicated-data
algorithm on many massively parallel computers since the Fock and
density matrices require at least 34 Mbytes (storing lower triangular
matrices). The distributed-data algorithm requires just 0.26
Mbytes/node (on 256 processors, storing full square matrices) leaving
much more memory to optimize the speed of integral evaluation.
<P>The following table presents wall times in hours for complete
SCF calculations on this system on several parallel computers. The
SP1 at Argonne National Laboratory is unusual since it has
SP1 compute nodes but uses an SP2 switch.
<PRE>
No. of
proc.s T3D KSR2 SP1
------ --- ---- ---
64 - - 5
72 - 4.4 -
128 2.9 - -
</PRE>
<H2><I>C14F6H8</I></H2>
<UL>
<LI> 324 functions, C(3s2p1d), F(3s2p1d), H(3s)
<LI> 28 atoms, no symmetry
</UL>
<P>This medium-sized molecule is representative of many routine
calculations and is also about the largest molecule without symmetry
for which it is practical to cache all integrals in memory. The
combination of massive parallelism and in-core algorithm makes for
very high performance. The distributed data method makes over 200
Mbytes more memory available for caching integrals than would be
available using a replicated-data approach.
<P>The following table presents total wall times in <I>seconds</I>
for a complete SCF calculation on this system using a fully in-core
algorithm on the NERSC CRAY-T3D which has 64 Mbytes of memory per
node.
<PRE>
T3D
Processors New (in-core)
---------- -------------
128 605
256 334
</PRE>
<H2><I>(Cp)Co(NO)(CH3)</I></H2>
<UL>
<LI> 114 function, minimal basis
<LI> 17 atoms, <I>Cs</I> symmetry
</UL>
<P>This cluster was provided by our industrial collaborators as being
representative of systems being considered as catalysts. Due to bugs,
previous versions of NWChem obtained only first-order convergence for
this system. This problem has been addressed and full, stable
second-order convergence is now obtained. In addition, <A
HREF="ddscf.html">optimizations in the use of linear algebra</A> has
significantly improved the scalability of this calculation.
<P> The following table presents total wall time in minutes for this
problem for the old and new versions of the code running on the KSR-2
and CRAY T3D. The drop-off in performance is typical for small
molecules and is due to poor load-balancing - the cobalt atom has
many more functions on it than the other atoms. The performance could be
enhanced by splitting large atoms, but this is only necessary for small
molecules.
<PRE>
KSR T3D
------------------------- -------------------------
No. of Old New New Old New New
proc.s Direct Direct In-core Direct Direct In-core
------ ------ ------ ------- ------ ------ -------
1 - 406.0 - - - -
8 - 53.2 7.5 - - -
16 38.0 29.6 4.5 - 31.0 -
32 31.8* 18.8 2.9 23 17.7 2.3
64 21.3** 12.3 2.8 15 10.9 -
128 - - - 11 7.9 -
* = 36 processor time
** = 72 processor time
</PRE>
<H2>Acknowledgments</H2>
This work was performed under the auspices of the High Performance
Computing and Communications Program of the Office of Scientific
Computing, U.S. Department of Energy under contract DE-AC6-76RLO 1830
with Battelle Memorial Institute which operates the Pacific Northwest
National Laboratory, a multiprogram national laboratory. This work
has made extensive use of software developed by the Molecular Science
Software Group of the Environmental Molecular Sciences Laboratory
project managed by the Office Health and Energy Research.
This research was performed in part using the Caltech Concurrent
Supercomputing Facilities (CCSF) operated by Caltech on behalf of the
Concurrent Supercomputing Consortium. Access to this facility was
provided by Pacific Northwest National Laboratory.
<P>
<HR>
<ADDRESS>Prepared by RJ Harrison: Email: nwchem-support@emsl.pnl.gov.</ADDRESS>
</BODY>
</HTML>