A Range Minima Parallel Algorithm for Coarse Grained Multicomputers

Parallel Range Minima on Coarse Grained Multicomputers

The Saukas-Song Selection Algorithm and Coarse Grained Parallel Sorting

We analyze the running time of the Saukas-Song algorithm for selection on a coarse grained multicomputer without expressing the running time in terms of communication rounds. We derive sorting algorithms that are asymptotically optimal for restricted ranges of processors on coarse grained multicomputers.

Strassen’s Algorithm on Coarse Grained Multicomputers

The “standard” naive algorithm for computing the product of two n n × matrices that is typically presented in an introduction to linear algebra runs in ( ) 3 n Θ time on a sequential computer. Strassen [11] developed a recursive algorithm that computes the product of two n n × matrices in ( ) ( ) 81 . 2 7 log2 n O n = Θ sequential time. We present an efficient implementation of Strassen’s algor...

Graph coloring on coarse grained multicomputers

We present an efficient and scalable Coarse Grained Multicomputer (CGM) coloring algorithm that colors a graph G with at most ∆+1 colors where ∆ is the maximum degree in G. This algorithm is given in two variants: a randomized and a deterministic. We show that on a p-processor CGM model the proposed algorithms require a parallel time of O( |G| p ) and a total work and overall communication cost...

Linkk Oping Electronic Articles in This Work Has Beensubmitted for Publication Elsewhere. Parallel Algorithms for Searching Monotone Matrices on Coarse Grained Multicomputers Linkk Oping Electronic Articles in Computer and Information Science

We present parallel algorithms for geometric problems on coarse grained multicomputers More speci cally for a square mesh connected p processor computer we show that The implicit row maxima problem on a totally monotone n nmatrix can be solved in O n p log p time if n p The all farthest neighbors problem for a convex n gon can be solved in O n p p time if n p The maximum perimeter triangle insc...