Directive-Based Data Partitioning and Pipelining and Auto-Tuning for High-Performance GPU Computing
The computer science community needs simpler mechanisms to achieve the performance potential of accelerators, such as graphics processing units (GPUs), field-programmable gate arrays (FPGAs), and co-processors (e.g., Intel Xeon Phi), due to their increasing use in state-of-the-art supercomputers. Ov...
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Virginia Tech
2020
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| Online Access: | http://hdl.handle.net/10919/101497 |