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Computational methods for finding long simple cycles in complex networks (2017)
Journal Article
Chalupa, D., Balaghan, P., Hawick, K. A., & Gordon, N. A. (2017). Computational methods for finding long simple cycles in complex networks. Knowledge-Based Systems, 125, 96-107 . https://doi.org/10.1016/j.knosys.2017.03.022

© 2017 Elsevier B.V. Detection of long simple cycles in real-world complex networks finds many applications in layout algorithms, information flow modelling, as well as in bioinformatics. In this paper, we propose two computational methods for findin... Read More about Computational methods for finding long simple cycles in complex networks.

Hypercubic storage layout and transforms in arbitrary dimensions using GPUs and CUDA (2010)
Journal Article
Hawick, K. A., & Playne, D. P. (2011). Hypercubic storage layout and transforms in arbitrary dimensions using GPUs and CUDA. Concurrency and Computation: Practice and Experience, 23(10), 1027-1050. doi:10.1002/cpe.1628

Many simulations in the physical sciences are expressed in terms of rectilinear arrays of variables. It is attractive to develop such simulations for use in 1-, 2-, 3- or arbitrary physical dimensions and also in a manner that supports exploitation o... Read More about Hypercubic storage layout and transforms in arbitrary dimensions using GPUs and CUDA.

Parallel graph component labelling with GPUs and CUDA (2010)
Journal Article
Hawick, K. A., Leist, A., & Playne, D. P. (2010). Parallel graph component labelling with GPUs and CUDA. Parallel Computing, 36(12), 655-678. doi:10.1016/j.parco.2010.07.002

Graph component labelling, which is a subset of the general graph colouring problem, is a computationally expensive operation that is of importance in many applications and simulations. A number of data-parallel algorithmic variations to the componen... Read More about Parallel graph component labelling with GPUs and CUDA.

Regular lattice and small-world spin model simulations using CUDA and GPUs (2010)
Journal Article
Hawick, K. A., Leist, A., & Playne, D. P. (2011). Regular lattice and small-world spin model simulations using CUDA and GPUs. International Journal of Parallel Programming, 39(2), 183-201. doi:10.1007/s10766-010-0143-4

Data-parallel accelerator devices such as Graphical Processing Units (GPUs) are providing dramatic performance improvements over evenmulti-coreCPUs for lattice-oriented applications in computational physics. Models such as the Ising and Potts models... Read More about Regular lattice and small-world spin model simulations using CUDA and GPUs.

Exploiting graphical processing units for data-parallel scientific applications (2009)
Journal Article
Leist, A., Playne, D. P., & Hawick, K. A. (2009). Exploiting graphical processing units for data-parallel scientific applications. Concurrency and Computation: Practice and Experience, 21(18), 2400-2437. doi:10.1002/cpe.1462

Graphical processing units (GPUs) have recently attracted attention for scientific applications such as particle simulations. This is partially driven by low commodity pricing of GPUs but also by recent toolkit and library developments that make them... Read More about Exploiting graphical processing units for data-parallel scientific applications.