Deep Learning for Computer Vision with MATLAB and cuDNN

Features, cuDNN, Deep Learning, Machine Learning, MATLAB

Nadeem Mohammad, posted Oct 28 2015

Deep learning is becoming ubiquitous. With recent advancements in deep learning algorithms and GPU technology, we are able to solve problems once considered impossible in fields such as computer vision, natural language processing, and robotics. Deep learning uses deep neural networks which have been around for a few decades; what’s changed in recent years is

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Cutting Edge Parallel Algorithms Research with CUDA

CUDA Spotlight, Algorithms, CUDA C++, CUDPP

Nadeem Mohammad, posted Oct 20 2015

Leyuan Wang, a Ph.D. student in the UC Davis Department of Computer Science, presented one of only two “Distinguished Papers” of the 51 accepted at Euro-Par 2015.  Euro-Par is a European conference devoted to all aspects of parallel and distributed processing held August 24-28 at Austria’s Vienna University of Technology. Leyuan’s paper Fast Parallel Suffix Array on the GPU,

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Accelerating Materials Discovery with CUDA

Features, Computational Chemistry, CUDA C++, cuRAND, Materials Science, Monte Carlo

Nadeem Mohammad, posted Oct 14 2015

In this post, we discuss how CUDA has facilitated materials research in the Department of Chemical and Biomolecular Engineering at UC Berkeley and Lawrence Berkeley National Laboratory. This post is a collaboration between Cory Simon, Jihan Kim, Richard L. Martin, Maciej Haranczyk, and Berend Smit. Engineering Applications of Nanoporous Materials Nanoporous materials have nano-sized pores such

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Open, Reproducible Computational Chemistry with Python and CUDA

CUDA Spotlight, Computational Chemistry, CUDA, Python

Nadeem Mohammad, posted Oct 12 2015

Increasingly, computational chemistry researchers use GPUs to push the boundaries of discovery. This motivated Christopher Cooper, an Instructor at Universidad Técnica Federico Santa María in Chile, to move to a Python-based software stack. Cooper’s recent paper, “Probing protein orientation near charged nanosurfaces for simulation-assisted biosensor design,” was recently accepted in J. Chemical Physics. Brad: Can you talk a

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Customize CUDA Fortran Profiling with NVTX

CUDA Pro Tip, CUDA Fortran, Optimization, Profiling

Nadeem Mohammad, posted Sep 29 2015

The NVIDIA Tools Extension (NVTX) library lets developers annotate custom events and ranges within the profiling timelines generated using tools such as the NVIDIA Visual Profiler (NVVP) and NSight. In my own optimization work, I rely heavily on NVTX to better understand internal as well as customer codes and to spot opportunities for better interaction

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