Ger van Diepen

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The performance potential of the Cell/B.E., as well as its availability, have attracted a lot of attention from various high-performance computing (HPC) fields. While computation intensive kernels proved to be exceptionally well suited for running on the Cell, irregular data-intensive applications are usually considered as poor matches. In this paper, we(More)
Now that large radiotelescopes like SKA, LOFAR, or ASKAP, become available in different parts of the world, radioastronomers foresee a vast increase in the amount of data to gather, store and process. To keep the processing time bounded, parallelization and execution on (massively) parallel machines are required for the commonly-used radioastronomy software(More)
In this report we present our experience with porting two very time consuming kernels from radioastronomy imaging, i.e. the gridding/degridding operations. Both these procedures are implemented using convolutional resampling, a bandwidth-limited application which is not trivial to parallelize on a hybrid memory architecture. We briefly discuss the role of(More)
Aims. This paper discusses the spectral occupancy for performing radio astronomy with the Low-Frequency Array (LOFAR), with a focus on imaging observations. Methods. We have analysed the radio-frequency interference (RFI) situation in two 24-h surveys with Dutch LOFAR stations, covering 30– 78 MHz with low-band antennas and 115–163 MHz with high-band(More)
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