In this paper, we look at the complexity of designing algorithms without any bank conflicts in the shared memory of Graphical Processing Units (GPUs). Given input of size n, w processors and w memory banks, we study three fundamental problems: sorting, permuting and w-way partitioning (defined as sorting an input containing exactly n/w copies of every integer in [w]). We solve sorting in optimal O (formula presented) time. When n ≥ w2, we solve the partitioning problem optimally in O(n/w) time. We also present a general solution for the partitioning problem which takes O (formula presented) time. Finally, we solve the permutation problem using a randomized algorithm in O (formula presented) time. Our results show evidence that when working with banked memory architectures, there is a separation between these problems and the permutation and partitioning problems are not as easy as simple parallel scanning.
CITATION STYLE
Afshani, P., & Sitchinava, N. (2015). Sorting and permuting without bank conflicts on GPUs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9294, pp. 13–24). Springer Verlag. https://doi.org/10.1007/978-3-662-48350-3_2
Mendeley helps you to discover research relevant for your work.