Aravind Vasudevan, Andrew Anderson, David Gregg
Tags: Algorithms, ARM, Computer science, CUDA, Deep learning, Machine learning, Matrix multiplication, Neural networks, nVidia, nVidia Tegra TX1, Performance
Shaohuai 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
hgpuYi-Yan Nan, Quan-Zhe Li, Jin-Chun Piao, Shin-Dug Kim
February 10, 2017 by
hgpuAli Charara, David Keyes, Hatem Ltaief
Seth D. Pendergrass, J. Nathan Kutz, Steven L. Brunton
December 26, 2016 by
hgpuFarhad Merchant, Tarun Vatwani, Anupam Chattopadhyay, Soumyendu Raha, S K Nandy, Ranjani Narayan
Tags: Algorithms, Computer science, CUDA, Factorization, FPGA, Linear Algebra, Mathematical Software, Matrix multiplication, nVidia, Performance, Tesla C2050
December 17, 2016 by
hgpuSyed Tahir Hussain Rizvi, Gianpiero Cabodi, Denis Patti, Gianluca Francini
December 10, 2016 by
hgpuSteven Eliuk, Cameron Upright, Hars Vardhan, Stephen Walsh, Trevor Gale
November 25, 2016 by
hgpuPedro Bruel, Marcos Amaris, Alfredo Goldman
Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 750, nVidia GeForce GTX 980, Package, Performance, Tesla K40
November 16, 2016 by
hgpuRyotaro Sakai, Fumihiko Ino, Kenichi Hagihara
Farhad Merchant, Tarun Vatwani, Anupam Chattopadhyay, Soumyendu Raha, S K Nandy, Ranjani Narayan