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2010 19th International Conference on Parallel Architectures and Compilation Techniques (PACT) (2010)
Vienna, Austria
Sept. 11, 2010 to Sept. 15, 2010
ISBN: 978-1-5090-5032-1
pp: 217-226
Chuntao Hong , Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing China
Dehao Chen , Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing China
Wenguang Chen , Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing China
Weimin Zheng , Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing China
Haibo Lin , China Research Lab of IBM, Beijing, China
ABSTRACT
Graphics Processing Units (GPU) have been playing an important role in the general purpose computing market recently. The common approach to program GPU today is to write GPU specific code with low level GPU APIs such as CUDA. Although this approach can achieve very good performance, it raises serious portability issues: programmers are required to write a specific version of code for each potential target architecture. It results in high development and maintenance cost.
INDEX TERMS
GPU programming, portability, parallel
CITATION
Chuntao Hong, Dehao Chen, Wenguang Chen, Weimin Zheng, Haibo Lin, "MapCG: Writing parallel program portable between CPU and GPU", 2010 19th International Conference on Parallel Architectures and Compilation Techniques (PACT), vol. 00, no. , pp. 217-226, 2010, doi:
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