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Visual analysis of large and complex data often requires multiple analysts with diverse expertise and different perspectives to collaborate in order to reveal hidden structures and gain insight in the data. While collaborative visualization allows multiple users to collectively work on the same analytic task, the user side computing devices can be used to share the computation workload for demanding data transformations and visualization calculations. In this paper, we present a heterogeneousdoi:10.1145/2818517.2818534 dblp:conf/siggraph/LiCM15 fatcat:zt2hmbyhjff25iigtsilsndbve