Duke, D.J., Borgo, R., Runciman, C. and Wallace, M. (2008) Experience report: visualizing data through functional pipelines. SIGPLAN Notices, 43 (9). pp. 379-382. ISSN 0362-1340
Scientific visualization is the transformation of data into images. The pipeline model is a widely-used implementation strategy. This term refers not only to linear chains of processing stages, but more generally to demand-driven networks of components. Apparent parallels with functional programming are more than superficial: e.g. some pipelines support streams of data, and a limited form of lazy evaluation. Yet almost all visualization systems are implemented in imperative languages. We challenge this position. Using Haskell, we have reconstructed several fundamental visualization techniques, with encouraging results both in terms of novel insight and performance. In this paper we set the context for our modest rebellion, report some of our results, and reflect on the lessons that we have learned.
|Copyright, Publisher and Additional Information:||International Conference on Functional Programming 08, Session 15. Copyright © 2008 by the Association for Computing Machinery, Inc. (ACM).|
|Institution:||The University of Leeds|
|Academic Units:||The University of Leeds > Faculty of Engineering (Leeds) > School of Computing (Leeds)|
|Depositing User:||Mrs Irene Rudling|
|Date Deposited:||19 Dec 2008 12:48|
|Last Modified:||15 Sep 2014 01:27|