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Achieving an even load balance with a low communication overhead is a fundamental task in parallel computing. In this paper we consider the problem of partitioning an array into a number of blocks such that the maximum amount of work in any block is as low as possible. We review diierent proposed schemes for this problem and the complexity of their… (More)

The problem of partitioning a sequence of n real numbers into p intervals is considered. The goal is to nd a partition such that the cost of the most expensive interval measured with a cost function f is minimized. An eecient algorithm which solves the problem in time O(p(n ? p) log p) is developed. The algorithm is based on nding a sequence of feasible… (More)

- Maria Lucka, Tor Sørevik
- 2000

In this paper we explain our strategy for parallelizing a wavelet based compression routine. The compression routine is designed to work within a earthquake simulation model where huge amount of data is written and read from disks. As the compression routine makes up for a significant part of the computation it is very important that it parallelize well. We… (More)

We introduce the class of skew-circulant lattice rules. These are s-dimensional lattice rules that may be generated by the rows of an s × s skew-circulant matrix. (This is a minor variant of the familiar circulant matrix.) We present briefly some of the underlying theory of these matrices and rules. We are particularly interested in finding rules of… (More)

Many problems have multiple layers of parallelism. The outer-level may consist of few and coarse-grained tasks. Next, each of these tasks may also be rich in parallelism, and be split into a number of fine-grained tasks, which again may consist of even finer subtasks, and so on. Here we argue and demonstrate by examples that utilizing multiple layers of… (More)

In this paper we discuss the use of nested parallelism. Our claim is that if the problem naturally possesses multiple levels of parallelism, then applying parallelism to all levels may significantly enhance the scalability of your algorithm. This claim is sustained by numerical experiments. We also discuss how to implement multi-level parallelism using… (More)

This paper describe the implementation and underlying philoso-phie of a large scale distributed computation of K-optimal lattice rules. The computation is huge corresponding to the equivalent of 36 years computation on a single workstation. In this paper we describe our implementation , how we have built in fault tolerence and our strategy for… (More)

In this paper we describe how to apply ne grain parallelism to augmenting path algorithms for the dense linear assignment problem. We prove by doing that the technique we suggest, can be eeciently implemented on commercial available, massively parallel computers. Using n processors, our method reduces the computational complexity from the sequential O(n 3)… (More)