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