Issue No.05 - May (1996 vol.7)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/71.503770
<p><b>Abstract</b>—Given a sequence of <it>n</it> elements, the All Nearest Smaller Values (ANSV) problem is to find, for each element in the sequence, the nearest element to the left (right) that is smaller, or to report that no such element exists. Time and work optimal algorithms for this problem are known on all the PRAM models [<ref rid="bibl04563" type="bib">3</ref>], [<ref rid="bibl04565" type="bib">5</ref>] but the running time of the best previous hypercube algorithm [<ref rid="bibl04566" type="bib">6</ref>] is optimal only when the number of processors <it>p</it> satisfies 1 ≤<it>p</it>≤<it>n</it>/((lg<super>3</super>n)(lg lg <it>n</it>)<super>2</super>). In this paper, we prove that any normal hypercube algorithm requires Ω(<it>n</it>) processors to solve the ANSV problem in <it>O</it>(lg <it>n</it>) time, and we present the first normal hypercube ANSV algorithm that is optimal for all values of <it>n</it> and <it>p</it>. We use our ANSV algorithm to give the first <it>O</it>(lg <it>n</it>)-time <it>n</it>-processor normal hypercube algorithms for triangulating a monotone polygon and for constructing a Cartesian tree.</p>
All nearest smaller values, normal hypercube algorithm, monotone polygon triangulation, Cartesian tree.
Dina Kravets, "All Nearest Smaller Values on the Hypercube", IEEE Transactions on Parallel & Distributed Systems, vol.7, no. 5, pp. 456-462, May 1996, doi:10.1109/71.503770