[Acpc-l] EINLADUNG zu einem Vortrag ueber "Cache Performance Optimizations for Iterative Linear Solvers and the Lattice Boltzmann Method"
Christoph Ueberhuber
christof@aurora.anum.tuwien.ac.at
Tue, 18 May 2004 09:10:35 +0200
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E I N L A D U N G zu einem Vortrag von
MARKUS KOWARSCHIK
Friedrich-Alexander-Universitaet Erlangen-Nuernberg
=FCber "CACHE PERFORMANCE OPTIMIZATIONS
FOR ITERATIVE LINEAR SOLVERS AND THE
LATTICE BOLTZMANN METHOD" =20
ORT: TU Wien, =84Freihaus=93, Seminarraum SEM 101C
Wiedner Hauptstrasse 8, Turm A, 4. Stock =20
ZEIT: Donnerstag, 27. Mai 2004, 14:15 Uhr
INHALT: In order to mitigate the effects of the constantly widening gap
between CPU speed and DRAM main memory performance, today's=20
computer architectures typically employ hierarchical memory designs=20
involving several layers of fast, yet relatively small cache memories=20
based on SRAM technology. Caches are supposed to contain copies=20
of frequently used data. Efficient code execution, however, can only be=20
expected if the codes respect the structure of the underlying memory=20
subsystem.
Unfortunately, current optimizing compilers are not able to synthesize
chains of complicated cache-based code transformations. Hence, they
rarely deliver the performance expected by the users and much of the
tedious and error-prone work concerning the tuning of the memory
efficiency is thus left to the software developer.
In this talk, we will first describe and analyze techniques which
primarily target the optimization of data cache performance on
hierarchical memory architectures. These techniques cover both data
layout transformations and data access transformations. We will focus
on iterative numerical algorithms for the solution of large sparse
systems of linear equations as well as cellular automata, particularly
the lattice Boltzmann method for simulating fluid flows.
Furthermore, the design of an inherently cache-aware patch-adaptive
multigrid algorithm will be introduced. This numerical scheme is
derived from the theory of the fully adaptive multigrid method and
does not result from the successive application of cache-based code
transformations which may theoretically be automized.
=20
=20
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<P><BR><FONT face=3DArial>E I N L A D U N G zu einem Vortrag =
von<BR><BR></FONT><FONT face=3DArial><SPAN =
class=3D832561213-23042004><FONT=20
color=3D#008080>MARKUS =
KOWARSCHIK<BR></FONT>Friedrich-Alexander-Universitaet=20
Erlangen-Nuernberg</SPAN><BR><BR>=FCber <SPAN=20
class=3D832561213-23042004>"</SPAN></FONT><FONT face=3DArial><SPAN=20
class=3D832561213-23042004><FONT color=3D#008080>CACHE PERFORMANCE=20
OPTIMIZATIONS<BR> &n=
bsp;=20
FOR ITERATIVE LINEAR SOLVERS AND=20
THE<BR> =
LATTICE=20
BOLTZMANN =
METHOD</FONT>"</SPAN> <BR><BR><BR>ORT: TU=20
Wien, „Freihaus“, Seminarraum SEM 10<SPAN=20
class=3D832561213-23042004>1C</SPAN><BR> &nb=
sp; =20
Wiedner Hauptstrasse 8, Turm A, <SPAN=20
class=3D832561213-23042004>4</SPAN>.=20
Stock <BR><BR>ZEIT: </FONT><FONT=20
face=3DArial><FONT color=3D#008080><SPAN=20
class=3D832561213-23042004>Donnerstag</SPAN>, <SPAN=20
class=3D832561213-23042004>2</SPAN>7. Mai 2004, 1<SPAN=20
class=3D832561213-23042004>4</SPAN>:15 =
Uhr<BR></FONT><BR><BR>INHALT: =20
</FONT><FONT face=3DArial color=3D#008080>In order to mitigate the =
effects of the=20
constantly widening gap <BR>between<SPAN class=3D832561213-23042004> =
</SPAN>CPU=20
speed and DRAM main memory performance, today's <BR>computer<SPAN=20
class=3D832561213-23042004> </SPAN>architectures typically employ =
hierarchical=20
memory designs <BR>involving<SPAN class=3D832561213-23042004> =
</SPAN>several=20
layers of fast, yet relatively small cache memories <BR>based on<SPAN=20
class=3D832561213-23042004> </SPAN>SRAM technology. Caches are supposed =
to contain=20
copies <BR>of frequently<SPAN class=3D832561213-23042004> </SPAN>used =
data.=20
Efficient code execution, however, can only be <BR>expected if<SPAN=20
class=3D832561213-23042004> </SPAN>the codes respect the structure of =
the=20
underlying memory <BR>subsystem.</FONT></P>
<P><FONT face=3DArial color=3D#008080>Unfortunately, current optimizing =
compilers=20
are not able to synthesize<BR>chains of complicated cache-based code=20
transformations. Hence, they<BR>rarely deliver the performance expected =
by the=20
users and much of the<BR>tedious and error-prone work concerning the =
tuning of=20
the memory<BR>efficiency is thus left to the software =
developer.</FONT></P>
<P><FONT face=3DArial color=3D#008080>In this talk, we will first =
describe and=20
analyze techniques which<BR>primarily target the optimization of data =
cache=20
performance on<BR>hierarchical memory architectures. These techniques =
cover both=20
data<BR>layout transformations and data access transformations. We will=20
focus<BR>on iterative numerical algorithms for the solution of large=20
sparse<BR>systems of linear equations as well as cellular automata,=20
particularly<BR>the lattice Boltzmann method for simulating fluid=20
flows.</FONT></P>
<P><FONT face=3DArial color=3D#008080>Furthermore, the design of an =
inherently=20
cache-aware patch-adaptive<BR>multigrid algorithm will be introduced. =
This=20
numerical scheme is<BR>derived from the theory of the fully adaptive =
multigrid=20
method and<BR>does not result from the successive application of =
cache-based=20
code<BR>transformations which may theoretically be automized.</FONT></P>
<P><FONT face=3DArial></FONT> </P>
<P><FONT face=3DArial></FONT> </P></BODY></HTML>
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