This is a preliminary repository for the submission SEA 2021. Once accepted, this repository will also contain the source code of our tool.
An interactive view of all the data presented here in the sqlite database is available at https://mpelleau.shinyapps.io/Hyperclique/
First of all, you need a recent installation of docker and you need to build the docker image. For this, clone this repository, then:
cd docker
docker build -t sea .
This will build a docker image with all the data, benchs and binaries needed. The -t sea tag gives the container a name (used below in the examples).
The container can open a shell by
docker run -it sea /bin/bash
Once the docker is set up, it is possible to access to the database of runs by
docker run -it sea sqlite3 /home/hyperclique/tuwien.sqlite
Then a number of queries are possible:
- Counts the number of jobs in the database :
SELECT COUNT(*) FROM runs;- Prints the benchmarks with their category:
SELECT interestingbenchs.bench, category FROM interestingbenchs, categories
WHERE interestingbenchs.bench = categories.bench
ORDER BY category, categories.bench;hyperclique is available at /home/hyperclique/hyperclique. You may want to run it with the help argument to get informations about running it
docker run -it sea /home/hyperclique/hyperclique -help
All the problems are under /home/hyperclique/tuwien-htd. You can, for instance, run hyperclique with the first method (a) with the default values from outside the docker image with
docker run -it sea /home/hyperclique/hyperclique -a -i tuwien-htd/Dubois-030.xml.htdOr, if you opened an interactive shell with the following command:
>> docker run -it sea /bin/bash
root@91a79eae4e67:/home/hyperclique# ./hyperclique -a -i tuwien-htd/Dubois-030.xml.htd
c +============================================================================+
c | Hyperclique enumerations |
c | Main Developers: |
c | - Marie Pelleau (marie.pelleau@univ-cotedazur.fr) |
c | - Laurent Simon (lsimon@labri.fr) |
c | Contributors: |
c | - Florian Régin (florian.regin@etu.univ-cotedazur.fr) |
c |----------------------------------------------------------------------------|
c | |
c | Debug: OFF |
c | Display: ON |
c | Hyper-Bron & Kerbosch enumeration: ON |
c | Hybrid-Bron & Kerbosch enumeration: OFF |
c | Clique-CE_HBK enumeration: OFF |
c | Non-uniform clique enumeration: OFF |
c | Filter: OFF |
c | Ordering: random |
c | Node filter: OFF |
c | |
c +============================================================================+
c | * tuwien-htd/Dubois-030.xml.htd |
c | * 60 hyperedges |
c | * 90 nodes |
c | * 3 max rank |
c | parsing time: 0.000259192 seconds |
c +============================================================================+
c | Hyper-Bron & Kerbosch enumeration: |
c |----------------------------------------------------------------------------|
c | 90 | 60 | 60 | 3 | 0.011028915 seconds |
c | nb calls to BK: 308 |
c | total cliques found: 60 |
c | total nb calls to BK: 308 |
c | timedout: 0 |
c | BK total time: 0.011840922 seconds |
c | total time: 0.012100114 seconds |
c +============================================================================+However, for parsing the results, you may want to use the -j argument to output a JSON line:
root@91a79eae4e67:/home/hyperclique# ./hyperclique -a -j -i tuwien-htd/Dubois-030.xml.htd
{"bench": "tuwien-htd/Dubois-030.xml.htd", "o": 0, "f": 0, "n": 0, "hyperedges": 60, "nodes": 90, "maxrank": 3, "parsingtime": 0.000228, "m": "a", "cliques": [{"nbnodes": 90, "nbedges": 60, "nbcliques": 60, "rank": 3, "time": 0.00983233, "nbcalls": 308}], "totalcliques": 60, "totalcalls": 308, "timedout": 0, "bktotaltime": 0.0104824, "totaltime": 0.0107108}To help reading/parsing the output, jq is installed on the docker. You can pretty print the output with
root@91a79eae4e67:/home/hyperclique# ./hyperclique -a -j -i tuwien-htd/Dubois-030.xml.htd | jqWhich gives you the JSON output:
{
"bench": "tuwien-htd/Dubois-030.xml.htd",
"o": 0,
"f": 0,
"n": 0,
"hyperedges": 60,
"nodes": 90,
"maxrank": 3,
"parsingtime": 0.00019,
"m": "a",
"cliques": [
{
"nbnodes": 90,
"nbedges": 60,
"nbcliques": 60,
"rank": 3,
"time": 0.0103165,
"nbcalls": 308
}
],
"totalcliques": 60,
"totalcalls": 308,
"timedout": 0,
"bktotaltime": 0.0109974,
"totaltime": 0.0111877
}let's say you want to run again a configuration in the database. The main component in the traces is the table runs.
sqlite> .schema runs
CREATE TABLE runs
(runid Integer primary key AUTOINCREMENT,
bench varchar(250),
o int,
f int,
n int,
m CHAR(1) CHECK( m IN ('a','b','c') ),
maxrank int,
timedout int(1),
timeout float,
hyperedges int,
nodes int,
totalcliques int,
parsingtime float,
totaltime float,
bktotaltime float,
totalcalls int);
It is possible to see the main configurations and results by
SELECT runs.bench, m, n, f, o, totaltime, timedout
FROM runs, interestingbenchs
WHERE runs.bench=interestingbenchs.bench
LIMIT 10;which gives (the LIMIT keyword is of course optional)
./tuwien-htd/rand-3-24-24-76-632-50.xml.htd|c|2|1|4|0.0077765|0
./tuwien-htd/Nonogram-074-table.xml.htd|c|2|1|4|0.0296264|0
./tuwien-htd/rand-3-28-28-93-632-48.xml.htd|c|2|1|4|0.0201116|0
./tuwien-htd/reg-s20-p03-c20-d10-n10-l5-97.xml.htd|c|2|1|4|0.00680803|0
./tuwien-htd/reg-s20-p03-c20-d10-n10-l5-96.xml.htd|c|2|1|4|0.00688477|0
./tuwien-htd/rand-7-40-8-40-02500-0.xml.htd|c|2|1|4|0.00638341|0
./tuwien-htd/rand-3-24-24-76-632f-32.xml.htd|c|2|1|4|0.00356882|0
./tuwien-htd/Nonogram-151-table.xml.htd|c|2|1|4|0.44246|0
./tuwien-htd/mdd-7-25-5-ps05-psh07-7.xml.htd|c|2|1|4|0.0065936|0
./tuwien-htd/Nonogram-155-table.xml.htd|c|2|1|4|0.0301679|0
So, let's say you want to re-run the second entry
./tuwien-htd/Nonogram-074-table.xml.htd|c|2|1|4|0.0296264|0
You can launch it with (notice that the method is given by -a, -b or -c and not with -m=a or -m=b or -m=c
docker run sea /home/hyperclique/hyperclique -c -m=2 -n=1 -f4 -o0 -j -i ./tuwien-htd/Nonogram-074-table.xml.htd
which gives you the JSON
{"bench": "./tuwien-htd/Nonogram-074-table.xml.htd", "o": 0, "f": 4, "n": 0, "hyperedges": 40, "nodes": 384, "maxrank": 24, "parsingtime": 0.000521, "m": "c", "cliques": [{"nbnodes": 384, "nbedges": 16, "nbcliques": 16, "rank": 24, "time": 4.3197e-05, "nbcalls": 0}, {"nbnodes": 384, "nbedges": 24, "nbcliques": 24, "rank": 16, "time": 0.0838645, "nbcalls": 3265}], "totalcliques": 40, "totalcalls": 3265, "timedout": 0, "bktotaltime": 0.0853867, "totaltime": 0.0859073}
The table interestingbenchs contains all the selected benchs from the paper:
SELECT count(*) FROM interestingbenchs:Will give you 1037. You can get the names by SELECT bench from interestingbenchs;
Other queries
- Jobs in DB :
SELECT COUNT(*) FROM runs; - Total CPU Time (in days):
SELECT ROUND(SUM(totaltime)/3600/24) FROM runs; - Number of timed out jobs:
SELECT COUNT(*) FROM runs WHERE timedout=1;, - Number of trivial jobs (<0.1s):
SELECT COUNT(*) FROM runs WHERE totaltime < 0.1; - Number of interesting jobs (>1s):
SELECT COUNT(*) FROM runs WHERE totaltime > 1; - Number of interesting benchs:
SELECT COUNT(*) FROM interestingbenchs;
Generates the data for the scatter plot (note that we use 2000s in case of a timeout just for a clear distinction on the scatter. This is not related to the Par2 scoring)
SELECT (CASE WHEN runsA.timedout==1 THEN 2000 ELSE runsA.totaltime END) AS timeA,
(CASE WHEN runsB.timedout==1 THEN 2000 ELSE runsB.totaltime END) AS timeB,
category
FROM runs AS runsA, runs AS runsB, interestingbenchs, categories
WHERE runsA.bench=interestingbenchs.bench AND
runsB.bench=interestingbenchs.bench AND
categories.bench=interestingbenchs.bench AND
runsA.m='a' AND runsA.n=0 AND runsA.f=0 AND runsA.o=3 AND
runsB.m='a' AND runsB.n=2 AND runsB.f=1 AND runsB.o=3 Generates the Par2 Ranking for all the configurations:
SELECT m, n, f, o, SUM(timedout) AS '#timeout',
SUM(CASE WHEN timedout==1 THEN 2600 ELSE totaltime END)/COUNT(*) AS Par2Score
FROM runs, interestingbenchs
WHERE runs.bench=interestingbenchs.bench
GROUP by m, n, f, o
ORDER BY Par2Score ASC