Daniel Kang, John Emmons, Firas Abuzaid, Peter Bailis, Matei Zaharia
Tags: Computer science, Computer vision, Databases, Deep learning, Machine learning, Neural networks, nVidia, nVidia DGX-1, Package, TensorFlow, Tesla P100
Aditya Balu, Sambit Ghadai, Gavin Young, Soumik Sarkar, Adarsh Krishnamurthy
Malte Schmidt, Dimitri Block, Uwe Meier
Sercan O. Arik, Mike Chrzanowski, Adam Coates, Gregory Diamos, Andrew Gibiansky, Yongguo Kang, Xian Li, John Miller, Jonathan Raiman, Shubho Sengupta, Mohammad Shoeybi
February 28, 2017 by
hgpuAndre Viebke, Suejb Memeti, Sabri Pllana, Ajith Abraham
February 28, 2017 by
hgpuYixing Li, Zichuan Liu, Kai Xu, Hao Yu, Fengbo Ren
Tags: CNN, Computer science, CUDA, Deep learning, Energy-efficient computing, FPGA, Hardware Architecture, Neural networks, nVidia, nVidia GeForce GTX Titan X, Performance
February 22, 2017 by
hgpuShaohuai Shi, Pengfei Xu, Xiaowen Chu
Tags: Algorithms, BLAS, Caffe, Computer science, CUBLAS, CUDA, Deep learning, Linear Algebra, Matrix multiplication, Neural networks, nVidia, nVidia GeForce GTX 1080, Package, Performance
February 14, 2017 by
hgpuEriko Nurvitadhi, David Sheffield, Jaewoong Sim, Asit Mishra, Ganesh Venkatesh, Debbie Marr
Tags: Algorithms, ASIC, Computer science, CUDA, Deep learning, FPGA, Neural networks, nVidia, nVidia GeForce GTX Titan X, nVidia Tegra TX1, Performance
February 14, 2017 by
hgpuMasatoshi Hidaka, Ken Miura, Tatsuya Harada
February 10, 2017 by
hgpuPatrick Wieschollek, Fabian Groh, Hendrik P.A. Lensch
February 10, 2017 by
hgpuMaciej Wielgosz, Andrzej Skoczen, Matej Mertik
Tags: CUDA, Deep learning, Instrumentation and Detectors, Keras, LSTM, Machine learning, Neural networks, nVidia, Physics, RNN, Tesla K80, Theano
