Arboricity and subgraph listing algorithms
SIAM Journal on Computing
Reductions in streaming algorithms, with an application to counting triangles in graphs
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Efficient semi-streaming algorithms for local triangle counting in massive graphs
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Main-memory triangle computations for very large (sparse (power-law)) graphs
Theoretical Computer Science
DOULION: counting triangles in massive graphs with a coin
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Graph Twiddling in a MapReduce World
Computing in Science and Engineering
Estimating clustering indexes in data streams
ESA'07 Proceedings of the 15th annual European conference on Algorithms
Low depth cache-oblivious algorithms
Proceedings of the twenty-second annual ACM symposium on Parallelism in algorithms and architectures
Counting triangles and the curse of the last reducer
Proceedings of the 20th international conference on World wide web
Scheduling irregular parallel computations on hierarchical caches
Proceedings of the twenty-third annual ACM symposium on Parallelism in algorithms and architectures
Triangle listing in massive networks and its applications
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Approximate counting of cycles in streams
ESA'11 Proceedings of the 19th European conference on Algorithms
New streaming algorithms for counting triangles in graphs
COCOON'05 Proceedings of the 11th annual international conference on Computing and Combinatorics
Colorful triangle counting and a MapReduce implementation
Information Processing Letters
Finding, counting and listing all triangles in large graphs, an experimental study
WEA'05 Proceedings of the 4th international conference on Experimental and Efficient Algorithms
Brief announcement: the problem based benchmark suite
Proceedings of the twenty-fourth annual ACM symposium on Parallelism in algorithms and architectures
Counting arbitrary subgraphs in data streams
ICALP'12 Proceedings of the 39th international colloquium conference on Automata, Languages, and Programming - Volume Part II
On the streaming complexity of computing local clustering coefficients
Proceedings of the sixth ACM international conference on Web search and data mining
Hi-index | 0.00 |
The number of triangles in a graph is a fundamental metric widely used in social network analysis, link classification and recommendation, and more. In these applications, modern graphs of interest tend to both large and dynamic. This paper presents the design and implementation of a fast parallel algorithm for estimating the number of triangles in a massive undirected graph whose edges arrive as a stream. Our algorithm is designed for shared-memory multicore machines and can make efficient use of parallelism and the memory hierarchy. We provide theoretical guarantees on performance and accuracy, and our experiments on real-world datasets show accurate results and substantial speedups compared to an optimized sequential implementation.