A cross-input adaptive framework for GPU program optimizations

Recent years have seen a trend in using graphic processing units (GPU) as accelerators for general-purpose computing. The inexpensive, single-chip, massively parallel architecture of GPU has evidentially brought factors of speedup to many numerical applications. However, the development of a high-qu...

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Bibliographische Detailangaben
Hauptverfasser:	Yixun Liu, Zhang, E.Z., Xipeng Shen
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Application software Computer architecture Computer graphics Computer science Cross-input Adaptation CUDA Educational institutions Empirical Search G-ADAPT GPU Parallel architectures Predictive models Productivity Program Optimizations Program processors Yarn
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