Abstract
GPGPU programming requires adjusting existing algorithms and often inventing new ones in order to achieve maximum performance. Solutions already created for supercomputers in nineties are not applicable since SIMD GPU devices are in many aspects different than vector supercomputers. This paper presents a new implementation of B+-tree index for GPU processors. It may be used in cases when processing parallelism and order of elements are equally important in computation. The solution is based on data representation optimal for GPU processing and an efficient parallel tree creation algorithm. We also deeply compare GPU B+-tree and other solutions. © 2012 Springer-Verlag.
Cite
CITATION STYLE
Kaczmarski, K. (2012). B+-tree optimized for GPGPU. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7566 LNCS, pp. 843–854). https://doi.org/10.1007/978-3-642-33615-7_27
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