Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/84219
Title: Abstract : mapping streaming applications onto GPU systems
Authors: Huynh, Huynh Phung.
Wong, Weng-Fai.
Ray, A.
Goh, Rick Siow Mong.
Hagiescu, Andrei.
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2012
Abstract: We describe an efficient and scalable code generation framework that automatically maps general purpose streaming applications onto GPU systems. This architecture-driven framework takes into account the idiosyncrasies of the GPU pipeline and the unique memory hierarchy. The framework has been implemented as a back-end to the StreamIt programming language compiler. Several key features in this framework ensure maximized performance and scalability. First, the generated code increases the effectiveness of the on-chip memory hierarchy by employing a heterogeneous mix of compute and memory access threads. Our scheme goes against the conventional wisdom of GPU programming which is to use a large number of homogeneous threads. Second, we utilise an efficient stream graph partitioning algorithm to handle larger applications and achieve the best performance under the given on-chip memory constraints. Lastly, the framework maps complex applications onto multiple GPUs using a highly effective pipeline execution scheme. Our comprehensive experiments show its scalability and significant speedup compared to a state-of-the-art solution.
URI: https://hdl.handle.net/10356/84219
http://hdl.handle.net/10220/13114
DOI: 10.1109/SC.Companion.2012.279
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Conference Papers

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