Generating Billion-Edge Scale-Free Networks in Seconds: Performance Study of a Novel GPU-based Preferential Attachment Model

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 graphical processing units (GPUs). To the best of our knowledge, our algorithm is the first to exploit GPUs, and also the fastest implementation available today, to generate scale-free networks using the preferential attachment model. A detailed performance study is presented to understand the scalability and runtime characteristics of the cuPPA algorithm. In one of the best cases, when executed on an NVidia GeForce 1080 GPU, cuPPA generates a scale-free network of a billion edges in less than 2 seconds.

[1]  S. N. Dorogovtsev,et al.  Evolution of networks , 2001, cond-mat/0106144.

[2]  Behrouz Minaei-Bidgoli,et al.  ROLL: Fast In-Memory Generation of Gigantic Scale-free Networks , 2016, SIGMOD Conference.

[3]  Andy B. Yoo,et al.  Parallel Generation of Massive Scale-Free Graphs , 2010, ArXiv.

[4]  Ulrich Meyer,et al.  Generating Massive Scale-Free Networks under Resource Constraints , 2016, ALENEX.

[5]  Ulrik Brandes,et al.  Efficient generation of large random networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[6]  Maksudul Alam,et al.  HPC-based Parallel Algorithms for Generating Random Networks and Some Other Network Analysis Problems , 2016 .

[7]  Frank S. de Boer,et al.  A high-level and scalable approach for generating scale-free graphs using active objects , 2016, SAC.

[8]  Madhav V. Marathe,et al.  Distributed-memory parallel algorithms for generating massive scale-free networks using preferential attachment model , 2013, 2013 SC - International Conference for High Performance Computing, Networking, Storage and Analysis (SC).

[9]  Jon M. Kleinberg,et al.  The Web as a Graph: Measurements, Models, and Methods , 1999, COCOON.

[10]  Peter Sanders,et al.  Scalable generation of scale-free graphs , 2016, Inf. Process. Lett..

[11]  J. Machta,et al.  Parallel dynamics and computational complexity of network growth models. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[12]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[13]  Eli Upfal,et al.  Stochastic models for the Web graph , 2000, Proceedings 41st Annual Symposium on Foundations of Computer Science.