Toyota Technological Institute, Chicago
11am Friday 30th May 2008
Room 2511, JCMB, King's Buildings
Note nonstandard day and time
Self-adjusting computation refers to a model of computation where programs can respond to changes to their data automatically. The model has been motivated by applications from a diverse set of fields where data sets change dynamically over time. In this talk, I give an overview of the progress in developing the underpinnings of the model and in developing language and compiler support for writing self-adjusting programs. I consider a number of application domains (e.g., motion modeling, scientific computing, machine learning, computational biology) and show that self-adjusting programs can deliver good performance, both in theory and in practice.