Abstract
Traversing huge graphs is a crucial part of many real-world problems, including graph databases. We show how to apply Fixed Length lightweight compression method for traversing graphs stored in the GPU global memory. This approach allows for a significant saving of memory space, improves data alignment, cache utilization and, in many cases, also processing speed. We tested our solution against the state-of-the-art implementation of BFS for GPU and obtained very promising results.
The project was funded by National Science Centre, decision DEC-2012/07/D/ST6/02483.
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Kaczmarski, K., Przymus, P., Rzążewski, P. (2015). Improving High-Performance GPU Graph Traversal with Compression. In: Bassiliades, N., et al. New Trends in Database and Information Systems II. Advances in Intelligent Systems and Computing, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-319-10518-5_16
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DOI: https://doi.org/10.1007/978-3-319-10518-5_16
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