openjdk team mailing list archive

[tony mancill <tmancill@xxxxxxxxxx>]

On Sun, Aug 18, 2019 at 04:54:52PM +0200, Erich Schubert wrote:
> Hi,
> 
> To reproduce the experiments, get the (older than what I used) ELKI
> standalone jar here:
> 
> https://elki-project.github.io/releases/release0.7.5/elki-bundle-0.7.5.jar
>
> (snip)
>
> A suitable command line is:
> 
> taskset -c 0 $JAVA_HOME/bin/java \
> -jar elki-bundle-0.7.5.jar \
> cli -time -dbc.in aloi-hsb-2x2x2.csv.gz \
> -algorithm clustering.DBSCAN -dbscan.minpts 20 -dbscan.epsilon 0.01 \
> -evaluator NoAutomaticEvaluation -resulthandler DiscardResultHandler
> 
> the "cli" command runs this headless; the "-time" parameter enables a
> minimal output of statistics. The last two parameter disable the
> (unnecessary for this purpose) evaluation and result output. tasksets forces
> this to use only the first CPU (except for the garbage collection,
> everything is single-threaded in this call).

I have been able to reproduce the "Java 8 is faster than Java 11"
results initially reporting using the ALOI datasets from [1].  However,
I have also seen Java 11 outperform Java 8 (by 4-5%) using the same
command-line invocation of ELKI against a different dataset [2].  This
isn't intended to refute your findings but to suggest that there could
be other factors.  Perhaps the performance difference depends on
specific aspects of the workload - e.g., whether there is more pressure
on the memory subsystem than CPU (or something like that).

Each of these are run on Debian sid (3) times on an otherwise quiet
system; the results below are representative (for all runs, JDK 11 was
faster on my system with this dataset):

#
# Java 8 
# OpenJDK 64-Bit Server VM (build 25.222-b10, mixed mode)
#
elki taskset -c 0 /usr/lib/jvm/java-8-openjdk-amd64/bin/java \
    -jar elki-bundle-0.7.5.jar \
    cli -time -dbc.in data/Range-Queries-Aggregates.csv \ 
    -algorithm clustering.DBSCAN -dbscan.minpts 20 -dbscan.epsilon 1 \
    -evaluator NoAutomaticEvaluation -resulthandler DiscardResultHandler
de.lmu.ifi.dbs.elki.datasource.FileBasedDatabaseConnection.load: 829 ms
de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN.average-neighbors: 1.0
There are very few neighbors found. Epsilon may be too small.
de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN.runtime: 513229 ms

#
# Java 11
# OpenJDK 64-Bit Server VM (build 11.0.4+11-post-Debian-1, mixed mode)
#
elki taskset -c 0 /usr/lib/jvm/java-11-openjdk-amd64/bin/java \
    -jar elki-bundle-0.7.5.jar \
    cli -time -dbc.in data/Range-Queries-Aggregates.csv \
    -algorithm clustering.DBSCAN -dbscan.minpts 20 -dbscan.epsilon 1 \
    -evaluator NoAutomaticEvaluation -resulthandler DiscardResultHandler
de.lmu.ifi.dbs.elki.datasource.FileBasedDatabaseConnection.load: 864 ms
de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN.average-neighbors: 1.0
There are very few neighbors found. Epsilon may be too small.
de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN.runtime: 490520 ms

So, this is to be continued...
In any event, thank you for bringing this benchmark to the list.

Cheers,
tony

[1] https://www.dbs.ifi.lmu.de/research/outlier-evaluation/input/ALOI.tar.gz
[2] http://archive.ics.uci.edu/ml/datasets/Query+Analytics+Workloads+Dataset

Attachment: signature.asc
Description: PGP signature