| Summary: | 碩士 === 國立交通大學 === 資訊科學與工程研究所 === 102 === Heterogeneous architecture has been widely adopted in various computing systems, from mobile devices to servers. However, optimizing the performance for such platforms remains challenging in three aspects: the control flow divergence decreases the utilization of SIMD components, the significant memory copy overhead between computing devices consuming precious memory bandwidth and the load imbalance that degrades the overall performance. In this paper, we proposed three methodologies: Intermediate Feedback, Dynamic Task Partitioning and Heterogeneous Runtime that work collaboratively to overcome the aforesaid problems. We adopted and implemented these methodologies in a heterogeneous runtime library derived from Intel Embree and compared the performance results of the two frameworks running Ray-Tracing on various scenes. Experiment results have shown that the performance gain from the proposed methods is significant, especially in complex scenes with a large amount of objects or with large input data sizes the CPU cannot handle efficiently.
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