Dec 15, 2010 · The techniques to meet these challenges are illustrated on two fundamental pre-processing algorithms – 3D image registration and 3D surface ...
For memory-bound algorithms, fitting the data into the fast but limited GPU resources is achieved through reorganizing the data into self-contained structures ...
Jun 1, 2012 · CUDA optimization strategies for compute- and memory-bound neuroimaging algorithms. Authors: Author Picture Daren Lee. Laboratory of Neuro ...
Jan 12, 2024 · However, its massively threaded architecture introduces challenges when GPU resources are exceeded. This paper presents optimization strategies ...
CUDA optimization strategies for compute- and memory-bound neuroimaging algorithms. Daren Leea (a), Ivo Dinova (a), Bin Dongb(b), Boris.
CUDA Optimization Strategies for Compute- And Memory-Bound Neuroimaging Algorithms by Daren Lee, Ivo Dinov, Bin Dong, Boris Gutman, Igor Yanovsky,
Jun 11, 2018 · I have profiled the kernel using nvprof (selected result below) and it seems that the kernel is memory bound (local memory overhead 96.66%), ...
Missing: strategies neuroimaging
CUDA optimization strategies for compute- and memory-bound neuroimaging algorithms. Computer Methods and Programs in Biomedicine 106, 3 (2012), 175–187.
This paper discusses several methods regarding the use of CUDA (Compute Unified Device Architecture) for 2D and 3D image processing techniques. Some general ...
A Review on GPU Programming Strategies and Recent Trends in GPU Computing ... CUDA optimization strategies for compute- and memory-bound neuroimaging algorithms.