SparseBench: a sparse iterative benchmark

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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

cd SparseBench

configure

Install the software and test your machine by

Test -m <machine name>

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.

Next we filter problem by

• Iterative method: gmres or cg;
• Storage scheme: regular (diagonal) or crs (compressed row);
• Preconditioner: none or ilu (incomplete LU).

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

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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

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