Abstract
CCAT is a large submillimetre telescope to be built near the ALMA site in northern Chile. A large-format KID camera, with up to 48,000 detectors at a single waveband sampled at about 1 kHz, will have a data rate about 50 times larger than SCUBA-2, the largest existing submillimetre camera. Creating a map from this volume of data will be a challenge, both in terms of memory and processing time required. We investigate how to extend SMURF, the iterative map-maker used for reducing SCUBA-2 observations, to a distributed-node parallel system, and estimate how the processing time scales with the number of nodes in the system.
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