We give a result that implies an improvement by a factor of log log n in the hypercube bounds for the geometric problems of batched planar point location, trapezoidal decomposition, and polygon triangulation. The improvements are achieved through a better solution to the multisearch problem on a hypercube, a parallel search problem where the elements in the data structure S to be searched are totally ordered, but where it is not possible to compare in constant time any two given queries q and q′. Whereas the previous best solution to this problem took O( log n( log log n)3) time on an n-processor hypercube, the solution given here takes O( log n( log log n)2) time on an n-processor hypercube. The hypercube model for which we claim our bounds is the standard one, SIMD, with O(1) memory registers per processor, and with one-port communication. Each register can store O( log n) bits, so that a processor knows its ID.
Lower Bounds for Dynamic Transitive Closure, Planar Point Location, and Parentheses Matching
