Compiling Data Intensive Applications with Spatial Coordinates

Processing and analyzing large volumes of data plays an increasingly important role in many domains of scientific research. We are developing a compiler which processes data intensive applications written in a dialect of Java and compiles them for efficient execution on cluster of workstations or distributed memory machines. In this paper, we focus on data intensive applications with two important properties: 1) data elements have spatial coordinates associated with them and the distribution of the data is not regular with respect to these coordinates, and 2) the application processes only a subset of the available data on the basis of spatial coordinates. These applications arise in many domains like satellite data-processing and medical imaging. We present a general compilation and execution strategy for this class of applications which achieves high locality in disk accesses. We then present a technique for hoisting conditionals which further improves efficiency in execution of such compiled codes. Our preliminary experimental results showtha t the performance from our proposed execution strategy is nearly two orders of magnitude better than a naive strategy. Further, up to 30% improvement in performance is observed by applying the technique for hoisting conditionals.