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Computer Science Colloquia

Thursday, July 26, 2012
Shuai Che
Advisor: Kevin Skadron
Attending Faculty: John Lach, Chair; Joanne Dugan, Sudhanva Gurumurthi, and Kamin Whitehouse

1:00 PM, Rice Hall, Rm. 242

Ph.D. Dissertation Defense
Understanding and Optimizing the Performance of Heterogeneous Systems

ABSTRACT
Heterogeneous computing with both CPUs and accelerators, such as GPUs, has become increasingly popular for general purpose computing. GPUs differ from CPUs significantly in architecture and programming models. GPUs provide high compute throughput and memory bandwidth, and offer dramatically better performance for many applications.

However, there is little previous work on understanding GPU application behaviors and how to map applications efficiently on the GPU. New techniques are also needed for both the CPU and the GPU to achieve an overall high performance. To better understand and optimize heterogeneous systems, we propose to study the following research issues to address these concerns. These include 1) the design of the Rodinia benchmark suite for heterogeneous platforms, including both the CPU and the GPU, 2) a detailed characterization of the Rodinia benchmark suite, 3) the Dymaxion framework to optimize the memory access patterns of heterogeneous platforms, 4) an approach for spreading and balancing workloads across the CPU and the GPU, and 5) a methodology to predict the performance of GPU applications.