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Compact data structure and scalable algorithms for the sparse grid technique
2011
Proceedings of the 16th ACM symposium on Principles and practice of parallel programming - PPoPP '11
The sparse grid discretization technique enables a compressed representation of higher-dimensional functions. In its original form, it relies heavily on recursion and complex data structures, thus being far from well-suited for GPUs. In this paper, we describe optimizations that enable us to implement compression and decompression, the crucial sparse grid algorithms for our application, on Nvidia GPUs. The main idea consists of a bijective mapping between the set of points in a
doi:10.1145/1941553.1941559
dblp:conf/ppopp/MurarasuWBBP11
fatcat:voszcfoqqjflxamcrzhz5byoee