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High-Performence Computing - Parallel, Distributed, and Cache-Conscious Algorithm Design and Analysis, Multithreaded Algorithms, Prefix Sums, Tree Contraction, Work-Efficient Parallel BFS, Graph Separation, Partitioning, Connectivity, Supercomputing

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Author(s): Various

Language: English
Tags: input; output; IO; I/O; input/output; sorting; complexity; lower bound; lower bounds; fooling the masses; twelve ways; 12 ways; fool the masses; multithreaded algorithms; CLRS; prefix sums; list rank; listrank; tree contraction; trees; BFS; breadth-first search; separator theorem; planar graphs; heuristic; partitioning graphs; graph partition; k-way partition; irregular graphs; connectivity; algebraic connectivity; sparse matrices; eigenvectors; graph theory; pregel-like graph processing systems

1 Introduction
2 Breadth-First Search Overview
2.1 Preliminaries
2.2 Parallel BFS: Prior Work
3 Breadth-First Search on Distributed Memory Systems
3.1 BFS with 1D Partitioning
3.2 BFS with 2D Partitioning
4 Implementation Details
4.1 Graph Representation
4.2 Local Computation
4.3 Distributed-memory parallelism
4.4 Load-balancing traversal
5 Algorithm Analysis
5.1 Analysis of the 1D Algorithm
5.2 Analysis of the 2D Algorithm
6 Experimental Studies
7 Conclusions and Future Work
8 References
Introduction
Background on BSP and Pregel
Systems Tested
Giraph
GPS
Mizan
GraphLab
Algorithms
PageRank
SSSP
WCC
DMST
Evaluation Methodology
System Setup
Datasets
Algorithms
Evaluation Metrics
Experimental Results
Summary of Results
Giraph
GPS
Mizan
GraphLab
Results for LJ and OR Datasets
Experiences
Giraph
GPS
Mizan
GraphLab
Conclusion
References