Enhancing Data Locality for Dynamic Simulations through Asynchronous Data Transformations and Adaptive Control
Department of Computer Science, The College of William and Mary, Williamsburg, VA 23187
The Twentieth International Conference on Parallel Architectures and Compilation Techniques, Galveston Island, Texas, USA, 2011
@inproceedings{wu2011enhancing,
title={Enhancing Data Locality for Dynamic Simulations through Asynchronous Data Transformations and Adaptive Control},
author={Wu, B. and Zhang, E. and Shen, X.},
booktitle={Proceedings of the International Conference on Parallel Architecture and Compilation Techniques (PACT)},
year={2011}
}
Many dynamic simulation programs contain complex, irregular memory reference patterns, and require runtime optimizations to enhance data locality. Current approaches periodically stop the execution of an application to reorder the computation or data based on the current program state to improve the data locality for the next period of execution. In this work, we examine the implications that modern heterogeneous Chip Multiprocessors (CMP) architecture imposes on the optimization paradigm. We develop three techniques to enhance the optimizations. The first is asynchronous data transformation, which moves data reordering off the critical path through dependence circumvention. The second is a novel data transformation algorithm, named TLayout, designed specially to take advantage of modern throughput-oriented processors. Together they provide two complementary ways to attack a benefit-overhead dilemma inherited in traditional techniques. Working with a dynamic adaptation scheme, the techniques produce significant performance improvement for a set of dynamic simulation benchmarks.
September 30, 2011 by hgpu
