Cugraph test and benchmark data

Python

This directory contains small public datasets in mtx and csv format used by cuGraph's python tests. Graph details:

Graph	V	E	Directed	Weighted
karate	34	156	No	No
dolphin	62	318	No	No
netscience	1,589	5,484	No	Yes

karate : The graph "karate" contains the network of friendships between the 34 members of a karate club at a US university, as described by Wayne Zachary in 1977.

dolphin : The graph dolphins contains an undirected social network of frequent associations between 62 dolphins in a community living off Doubtful Sound, New Zealand, as compiled by Lusseau et al. (2003).

netscience : The graph netscience contains a coauthorship network of scientists working on network theory and experiment, as compiled by M. Newman in May 2006.

Modified datasets

The datasets below were added to provide input that contains self-loops, string vertex IDs, isolated vertices, and multiple edges.

Graph	V	E	Directed	Weighted	self-loops	Isolated V	String V IDs	Multi-edges
karate_multi_edge	34	160	No	Yes	No	No	No	Yes
dolphins_multi_edge	62	325	No	Yes	No	No	No	Yes
karate_s_loop	34	160	No	Yes	Yes	No	No	No
dolphins_s_loop	62	321	No	Yes	Yes	No	No	No
karate_mod	37	156	No	No	No	Yes	No	No
karate_str	34	156	No	Yes	No	No	Yes	No

karate_multi_edge : The graph "karate_multi_edge" is a modified version of the "karate" graph where multi-edges were added

dolphins_multi_edge : The graph "dolphins_multi_edge" is a modified version of the "dolphin" graph where multi-edges were added

karate_s_loop : The graph "karate_s_loop" is a modified version of the "karate" graph where self-loops were added

dolphins_s_loop : The graph "dolphins_s_loop" is a modified version of the "dolphin" graph where self-loops were added

karate_mod : The graph "karate_mod" is a modified version of the "karate" graph where vertices and edges were added

karate_str : The graph "karate_str" contains the network of friendships between the 34 members of a karate club at a US university, as described by Wayne Zachary in 1977. The integer vertices were replaced by strings

Additional datasets

Larger datasets containing self-loops can be downloaded by running the provided script from the datasets directory using the --self_loops option:

cd <repo>/datasets
./get_test_data.sh --self_loops

<repo>/datasets/self_loops
 |-ca-AstroPh  (5.3M)
 |-ca-CondMat  (2.8M)
 |-ca-GrQc     (348K)
 |-ca-HepTh    (763K)

These datasets are not currently used by any tests or benchmarks

Graph	V	E	Directed	Weighted	self-loops	Isolated V	String V IDs	Multi-edges
ca-AstroPh	18,772	198,110	No	No	Yes	No	No	No
ca-CondMat	23,133	93,497	No	Yes	Yes	No	No	No
ca-GrQc	5,242	14,387	No	No	Yes	No	No	No
ca-HepTh	9,877	25,998	No	Yes	Yes	No	No	No

ca-AstroPh : The graph "ca-AstroPh" covers scientific collaborations between authors papers submitted to Astro Physics category in the period from January 1993 to April 2003 (124 months), as described by J. Leskovec, J. Kleinberg and C. Faloutsos in 2007.

ca-CondMat : The graph "ca-CondMat" covers scientific collaborations between authors papers submitted to Condense Matter category in the period from January 1993 to April 2003 (124 months), as described by J. Leskovec, J. Kleinberg and C. Faloutsos in 2007.

ca-GrQc : The graph "ca-GrQc" covers scientific collaborations between authors papers submitted to General Relativity and Quantum Cosmology category in the period from January 1993 to April 2003 (124 months), as described by J. Leskovec, J. Kleinberg and C. Faloutsos in 2007.

ca-HepTh : The graph "ca-HepTh" covers scientific collaborations between authors papers submitted to High Energy Physics - Theory category in the period from January 1993 to April 2003 (124 months), as described by J. Leskovec, J. Kleinberg and C. Faloutsos in 2007.

Custom path to larger datasets directory

Cugraph's C++ and Python analytics tests need larger datasets (>5GB uncompressed) and reference results (>125MB uncompressed). They can be downloaded by running the provided script from the datasets directory.

cd <repo>/datasets
./get_test_data.sh

You may run this script from elsewhere and store C++ or Python test input to another location.

Before running the tests, you should let cuGraph know where to find the test input by using:

export RAPIDS_DATASET_ROOT_DIR=<path_to_datasets_dir>

Benchmarks

Cugraph benchmarks (which can be found here) also use datasets installed to this folder. Because the datasets used for benchmarking are also quite large (~14GB uncompressed), they are not installed by default. To install datasets for benchmarks, run the same script shown above from the datasets directory using the --benchmark option:

cd <repo>/datasets
./get_test_data.sh --benchmark

The datasets installed for benchmarks currently include CSV files for use in creating both directed and undirected graphs:

<repo>/datasets/csv
 |- directed
 |--- cit-Patents.csv       (250M)
 |--- soc-LiveJournal1.csv  (965M)
 |- undirected
 |--- europe_osm.csv        (1.8G)
 |--- hollywood.csv         (1.5G)
 |--- soc-twitter-2010.csv  (8.8G)

The benchmark datasets are described below:

Graph	V	E	Directed	Weighted
cit-Patents	3,774,768	16,518,948	Yes	No
soc-LiveJournal1	4,847,571	43,369,619	Yes	No
europe_osm	50,912,018	54,054,660	No	No
hollywood	1,139,905	57,515,616	No	No
soc-twitter-2010	21,297,772	265,025,809	No	No

cit-Patents : A citation graph that includes all citations made by patents granted between 1975 and 1999, totaling 16,522,438 citations.

soc-LiveJournal : A graph of the LiveJournal social network.

europe_osm : A graph of OpenStreetMap data for Europe.

hollywood : A graph of movie actors where vertices are actors, and two actors are joined by an edge whenever they appeared in a movie together.

soc-twitter-2010 : A network of follower relationships from a snapshot of Twitter in 2010, where an edge from i to j indicates that j is a follower of i.

NOTE: the benchmark datasets were converted to a CSV format from their original format described in the reference URL below, and in doing so had edge weights and isolated vertices discarded.

Reference

The SuiteSparse Matrix Collection (formerly the University of Florida Sparse Matrix Collection) : https://sparse.tamu.edu/ The Stanford Network Analysis Platform (SNAP)