Profile-guided loop parallelization and co-scheduling on GPU-based heterogeneous many-core architectures
The GPU-based heterogeneous architectures (e.g., Tianhe-1A, Nebulae), composing multi-core CPU and GPU, have drawn increasing adoptions and are becoming the norm of supercomputing as they are cost-effective and power-efficient. However, programming such heterogeneous architectures still requires s...
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| Language: | English |
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The University of Hong Kong (Pokfulam, Hong Kong)
2013
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| Online Access: | http://hdl.handle.net/10722/188306 |