SparseBench: a sparse iterative benchmark
Jack Dongarra, Victor Eijkhout
Computer Science Department
University of Tennessee
Knoxville, TN 37996-1301, USA
and
Henk van der Vorst
Universiteit Utrecht
Utrecht, the Netherlands
Click here to see the number of accesses to this library.
For comments and questions, mail to
sparsebench@cs.utk.edu.
About the benchmark
SparseBench is a benchmark suite of iterative methods on
sparse data. Sparse matrices, such as derived from
PDEs, form an important problem area in numerical analysis.
Unlike in the case of dense matrices, handling them does not
entail much reuse of data. Thus, algorithms for sparse
matrices will be more bound by memory-speed than by processor-speed.
This benchmark uses common iterative methods, preconditioners,
and storage schemes to evaluate machine performance on typical
sparse operations. The benchmark components are:
- Conjugate Gradient and GMRES iterative methods,
- Jacobi and ILU preconditioners,
- diagonal storage and compressed row storage matrices.
Instructions
Download the file benchmark.tgz below.
Unpack it by
gunzip benchmark.tgz
tar -xf benchmark.tar or tar -x -f benchmark.tar
Go into the benchmark directory
cd SparseBench
and configure for your architecture
configure
Install the software and test your machine by
Test -m <machine name>
where "machine name" is an arbitrary name for your machine.
If you run 'Test' more than once, only higher numbers are kept.
Mail the results back to the benchmark reporting authority by
Report -m <machine name>
You are strongly encouraged to read
the files README and install.ps below, which are also
part of the full tgz file.
Benchmark results
These are preliminary benchmark results, performed mostly on computers
owned by the Innovative Computing Labs of the University of Tennessee.
All tests report Megaflop rates on code that is compiled straight
out of the box.
First we report the highest rate found for any problem.
This was typically attained on a fairly small problem size,
the implication being that the whole problem fit into cache.
Highest performance ranking |
EV6 [a] | 759 |
Power3 [a] | 606 |
EV6 [b] | 438 |
Power3 [b] | 331 |
EV56 | 262 |
PPC G4 | 198 |
R12000 [a] | 155 |
UltraSparcII [a] | 154 |
Athlon | 154 |
R12000 [b] | 108 |
Origin | 106 |
UltraSparcII [b] | 102 |
PentiumIII | 96 |
LX164 | 81 |
UltraSparcII [c] | 47 |
|
List of machines used |
Processor | Machine | Owned by | Compiler options |
Athlon | Athlon 600MHz | R. Clint Whaley | -O |
EV56 | Dec Alpha, 433 MHz | ICL, University of Tennessee |
EV6 [a] | | Geophysik, Freie Universitaet Berlin |
EV6 [b] | DEC Alpha, 500 MHZ | ICL, University of Tennessee |
LX164 | ALPHA, 533MHz | ICL, University of Tennessee |
Origin | SGI Origin, single processor | NCSA | -O |
PPC G4 | Macintosh at 450MHz | ICL, University of Tennessee |
PentiumIII | Dell, dual 550MHz | ICL, University of Tennessee |
Power3 [a] | IBM quad 375MHz power3 | ICL, University of Tennessee |
Power3 [b] | IBM Power3, dual 200MHz | ICL, University of Tennessee |
R12000 [a] | SGI Octane, 270 MHz | ICL, University of Tennessee | -O |
R12000 [b] | SGI Indigo | ICL, University of Tennessee | -O |
UltraSparcII [a] | Sun Enterprise 450 model 1300, single 296MHz | ICL, University of Tennessee | -O |
UltraSparcII [b] | Sun Ultra5 | ICL, University of Tennessee | -O |
UltraSparcII [c] | Sun Enterprise, 248MHz | ICL, University of Tennessee |
|
Next we filter problem by
- Iterative method: gmres or cg;
- Storage scheme: regular (diagonal) or crs (compressed row);
- Preconditioner: none or ilu (incomplete LU).
and we report the "asymptotic performance" which will be the expected Mflop
rate for large problems that overflow the cache.
Asymptotic performance is determined by making a y=a+b/x fit
through the observations, where x is the data set size in Mbytes.
|
Asymptotic performance on "gmres" problems |
EV6 [a] | 216 |
Power3 [a] | 209 |
EV6 [b] | 168 |
Power3 [b] | 130 |
R12000 [a] | 78 |
Origin | 71 |
EV56 | 60 |
Athlon | 44 |
LX164 | 40 |
PentiumIII | 39 |
PPC G4 | 38 |
UltraSparcII [a] | 37 |
R12000 [b] | 30 |
UltraSparcII [c] | 23 |
UltraSparcII [b] | 23 |
|
|
Asymptotic performance on "cg" problems |
EV6 [a] | 285 |
Power3 [a] | 254 |
EV6 [b] | 198 |
Power3 [b] | 110 |
Origin | 70 |
UltraSparcII [a] | 57 |
R12000 [a] | 52 |
PPC G4 | 45 |
LX164 | 45 |
Athlon | 43 |
EV56 | 40 |
PentiumIII | 37 |
UltraSparcII [c] | 26 |
UltraSparcII [b] | 21 |
R12000 [b] | 19 |
|
|
Asymptotic performance on "reg" problems |
EV6 [a] | 285 |
Power3 [a] | 254 |
EV6 [b] | 198 |
Power3 [b] | 110 |
R12000 [a] | 78 |
Origin | 71 |
UltraSparcII [a] | 57 |
EV56 | 55 |
PPC G4 | 45 |
LX164 | 45 |
Athlon | 43 |
PentiumIII | 37 |
R12000 [b] | 28 |
UltraSparcII [c] | 26 |
UltraSparcII [b] | 21 |
|
|
Asymptotic performance on "crs" problems |
Power3 [a] | 209 |
EV6 [a] | 209 |
EV6 [b] | 166 |
Power3 [b] | 130 |
Origin | 68 |
R12000 [a] | 63 |
EV56 | 60 |
Athlon | 44 |
LX164 | 40 |
PentiumIII | 39 |
UltraSparcII [a] | 35 |
R12000 [b] | 30 |
UltraSparcII [c] | 23 |
UltraSparcII [b] | 23 |
PPC G4 | 23 |
|
|
Asymptotic performance on "none" problems |
Power3 [a] | 215 |
EV6 [a] | 205 |
EV6 [b] | 158 |
Power3 [b] | 88 |
R12000 [a] | 64 |
Origin | 63 |
UltraSparcII [a] | 40 |
EV56 | 40 |
PPC G4 | 38 |
LX164 | 36 |
Athlon | 33 |
PentiumIII | 27 |
UltraSparcII [c] | 26 |
R12000 [b] | 24 |
UltraSparcII [b] | 21 |
|
|
Asymptotic performance on "ilu" problems |
EV6 [a] | 163 |
EV6 [b] | 132 |
Power3 [a] | 120 |
Power3 [b] | 90 |
R12000 [a] | 62 |
Origin | 57 |
EV56 | 39 |
UltraSparcII [a] | 34 |
Athlon | 34 |
LX164 | 33 |
PPC G4 | 31 |
PentiumIII | 27 |
R12000 [b] | 20 |
UltraSparcII [c] | 16 |
UltraSparcII [b] | 15 |
|
#########################################################################
file readme
file install.ps
file install.pdf
for Installation Guide for the Sparse Iterative Benchmark
file benchmark.tgz
for Benchmark of Conjugate Gradient methods, using sparse data storage
, Sparse benchmark, version 0.9.7, released 17 Nov 2000.
, Questions/comments to sparsebench@cs.utk.edu
by Jack Dongarra, Victor Eijkhout, Henk van der Vorst
file bench.ps
file bench.pdf
for Details and results of the Sparse Iterative Benchmark
#########################################################################