{"push_id":2172315332,"size":1,"distinct_size":1,"ref":"refs/heads/topic-alpaka","head":"af16c78f8776c90d934d925b0935b7fd6c765218","before":"77aa79d8d66e31d6d5bbeb5c4ecddacfd415314f","commits":[{"sha":"af16c78f8776c90d934d925b0935b7fd6c765218","author":{"name":"Axel Huebl","email":"cbd9cb02b0a7773a498a8c58a104bb0b3f2f94d8@plasma.ninja"},"message":"Add alpaka & cupla\n\n**alpaka** and **cupla** are two coupled libraries that allow\nprogramming accelerator hardware (GPUs, Xeon Phi, etc.) via a\ncommon, single-source, performance-portable, standard C++11\nprogramming model.\n\nalpaka/cuplda are used in various scientific codes, e.g.\nPIConGPU, HASEonGPU, ISAAC and Mephisto.\n\nA list of publications (including OA links) explain the concepts\nbehind alpaka/cupla:\n\n* DOI:10.1109/IPDPSW.2016.50 (http://arxiv.org/abs/1602.08477),\n  paper in AsHES2016\n\n* DOI:10.5281/zenodo.49768 (thesis: diploma)\n\n* DOI:10.1007/978-3-319-67630-2_36 (https://arxiv.org/abs/1706.10086),\n  paper in ISC17 (P3MA)\n\n* DOI:10.1007/978-3-319-46079-6_21 (https://arxiv.org/abs/1606.02862),\n  paper in ISC16 (IWOPH)\n\n* Live-Porting from CUDA to alpaka/cupla, talk in GTC2016:\n  https://mygtc.gputechconf.com/events/32/schedules/2792\n  Video: http://on-demand.gputechconf.com/gtc/2016/video/S6298.html","distinct":true,"url":"https://api.github.com/repos/ax3l/awesome-cpp/commits/af16c78f8776c90d934d925b0935b7fd6c765218"}]}
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