Proceedings of the 22nd International Conference on Parallel Architectures and Compilation Techniques (2001)
Sept. 8, 2001 to Sept. 12, 2001
Gagan Agrawal , University of Delaware
Joel Saltz , University of Maryland, College Park
Renato Ferreira , University of Maryland, College Park
Abstract: Processing and analyzing large volumes of data plays an increasingly important role in many domains of scientific research. We are developing a compiler that processes data intensive applications written in a dialect of Java and compiles them for efficient execution on distributed memory parallel machines. In this paper, we focus on the problem of generating correct and efficient communication for data intensive applications. We present static analysis techniques for 1) extracting a global reduction function from a data parallel loop, and 2) determining if a subscript function is monotonic. We also present a runtime technique for reducing the volume of communication during the global reduction phase. We have experimented with two data intensive applications to evaluate the efficacy of our techniques. Our results show that 1) our techniques for extracting global reduction functions and establishing monotonicity of subscript functions can successfully handle these applications, 2) significant reduction in communication volume and execution times is achieved through our runtime analysis technique, 3) runtime communication analysis is critical for achieving speedups on parallel configurations.
Gagan Agrawal, Joel Saltz, Renato Ferreira, "Compiler and Runtime Analysis for Efficient Communication in Data Intensive Applications", Proceedings of the 22nd International Conference on Parallel Architectures and Compilation Techniques, vol. 00, no. , pp. 0231, 2001, doi:10.1109/PACT.2001.953303