Simon Andreas Frimann Lund

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—In this paper we introduce Bohrium, a runtime-system for mapping array-operations onto a number of different hardware platforms, from multi-core systems to clusters and GPU enabled systems. As a result, the Bohrium runtime system enables NumPy code to utilize CPU, GPU, and Clusters. Bohrium integrates seamlessly into NumPy through the implicit data(More)
We address the problem of fusing array operations based on criteria such as shape compatibility, data reuse, and minimizing for data reuse, the fusion problem has been formulated as a static weighted graph partitioning problem (known as the Weighted Loop Fusion problem). We show that this scheme cannot accurately track data reuse between multiple(More)
—Modern processor architectures, in addition to having still more cores, also require still more consideration to memory-layout in order to run at full capacity. The usefulness of most languages is deprecating as their abstractions, structures or objects are hard to map onto modern processor architectures efficiently. The work in this paper introduces a new(More)
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