Tor Sørevik

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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)
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)