Novel Parallel Algorithms for Fast Multi-GPU-Based Generation of Massive Scale-Free Networks

Novel Parallel Algorithms for Fast Multi-GPU-Based Generation of Massive Scale-Free Networks

Abstract A novel parallel algorithm is presented for generating random scale-free networks using the preferential attachment model. The algorithm, named cuPPA, is custom-designed for “single instruction multiple data (SIMD)” style of parallel processing supported by modern processors such as graphic...

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Bibliographic Details
Main Authors: Maksudul Alam, Kalyan S. Perumalla, Peter Sanders
Format: Article
Language:English
Published: SpringerOpen 2019-03-01
Series:Data Science and Engineering
Subjects:
GPU
Preferential attachment
Random networks
Scale-free networks
Online Access:http://link.springer.com/article/10.1007/s41019-019-0088-6

Internet

http://link.springer.com/article/10.1007/s41019-019-0088-6

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