Steven W. D. Chien, Stefano Markidis, Vyacheslav Olshevsky, Yaroslav Bulatov, Erwin Laure, Jeffrey S. Vetter
Tags: Benchmarking, Computer science, CUDA, Deep learning, FFT, Heterogeneous systems, HPC, Machine learning, nVidia, nVidia Quadro K420, OpenMPI, Package, Performance, Python, TensorFlow, Tesla K80, Tesla V100
Paul Sathre, Mark Gardner, Wu-chun Feng
Tags: AMD FirePro S9150, ATI, Computer science, CUDA, FPGA, Intel Xeon Phi, nVidia, OpenCL, Package, performance portability, Tesla K80
Maria Angelica Davila Guzman, Raul Nozal, Ruben Gran Tejero, Maria Villarroya-Gaudo, Dario Suarez Gracia, Jose Luis Bosque
Andrew Gloster, Lennon O'Naraigh
Hong-zhong Wu, Junjie Zhang, Long-gang Pang, Qun Wang
February 24, 2019 by
hgpuDaniel Smilkov, Nikhil Thorat, Yannick Assogba, Ann Yuan, Nick Kreeger, Ping Yu, Kangyi Zhang, Shanqing Cai, Eric Nielsen, David Soergel, Stan Bileschi, Michael Terry, Charles Nicholson, Sandeep N. Gupta, Sarah Sirajuddin, D. Sculley, Rajat Monga, Greg Corrado, Fernanda B. Viegas, Martin Wattenberg
Tags: Computer science, CUDA, Deep learning, Java, Machine learning, nVidia, nVidia GeForce GTX 1080, OpenGL, Package, TensorFlow, WebGL
February 17, 2019 by
hgpuPeifeng Yu, Mosharaf Chowdhury
February 17, 2019 by
hgpuCanhui Wang, Xiaowen Chu
February 17, 2019 by
hgpuDavid Pfander, Gregor Daiss, Dirk Pfluger
Tags: Clustering, Computer science, Data mining, Distributed computing, Heterogeneous systems, Machine learning, MPI, nVidia, OpenCL, Package, performance portability, Tesla P100
February 10, 2019 by
hgpuZeyi Wen, Jiashuai Shi, Bingsheng He, Qinbin Li, Jian Chen
