Abstract
The computational power and memory bandwidth of graphics processing units (GPUs) have turned them into attractive platforms for general-purpose applications at significant speed gains versus their CPU counterparts [1]. In addition, an increasing number of today’s state-of-the-art supercomputers [2] include commodity GPUs to bring us unprecedented levels of high performance and low cost. In this paper, we describe CUDA as the software and hardware paradigm behind those achievements. We summarize its evolution over the past decade, explain its major features and provide insights about future trends for this emerging trend to continue as flagship within high performance computing.
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Acknowledgment
We thank Nvidia for hardware donation and travelling support under CUDA Teaching Center 2011–2016, CUDA Research Center 2012–2016 and CUDA Fellow 2012–2016 Awards.
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© 2016 Springer International Publishing Switzerland
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Ujaldón, M. (2016). CUDA Achievements and GPU Challenges Ahead. In: Perales, F., Kittler, J. (eds) Articulated Motion and Deformable Objects. AMDO 2016. Lecture Notes in Computer Science(), vol 9756. Springer, Cham. https://doi.org/10.1007/978-3-319-41778-3_20
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DOI: https://doi.org/10.1007/978-3-319-41778-3_20
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