GPU Computing, the basics: – Chip ICT
Use CLBlast as a Dropin replacement in Octave · Issue #326 · CNugteren/CLBlast · GitHub
GitHub - joncox123/Cortexsys: Matlab GPU Accelerated Deep Learning Toolbox
Massively parallel programming with GPUs — Computational Statistics in Python 0.1 documentation
cuBLAS
Time-stepping methods for the simulation of the self-assembly of nano-crystals in Matlab on a GPU - ScienceDirect
Massively parallel programming with GPUs — Computational Statistics in Python 0.1 documentation
Comparison of GPU and CPU Computational Times for ML and ED classifiers. | Download Scientific Diagram
Acceleration in Acoustic Wave Propagation Modelling Using OpenACC/OpenMP and Its Hybrid for the Global Monitoring System | SpringerLink
GPU acceleration of the KAZE image feature extraction algorithm | Journal of Real-Time Image Processing
GPU acceleration of the KAZE image feature extraction algorithm | Journal of Real-Time Image Processing
Time-stepping methods for the simulation of the self-assembly of nano-crystals in Matlab on a GPU - ScienceDirect
Massively parallel programming with GPUs — Computational Statistics in Python 0.1 documentation
Drop-in Acceleration of GNU Octave | NVIDIA Technical Blog
Drop-in Acceleration of GNU Octave | NVIDIA Technical Blog
GNU Octave - Wikipedia
Drop-in Acceleration of GNU Octave | NVIDIA Technical Blog
Process of two-layer 3D domain decomposition on CPU-GPU based... | Download Scientific Diagram
cuBLAS
Electronics | Free Full-Text | GPU Accelerated Nonlinear Electronic Circuits Solver for Transient Simulation of Systems with Large Number of Components
Symmetry | Free Full-Text | Efficient Algorithms for Real-Time GPU Volumetric Cloud Rendering with Enhanced Geometry
Electronics | Free Full-Text | GPU Accelerated Nonlinear Electronic Circuits Solver for Transient Simulation of Systems with Large Number of Components
GPU acceleration of the KAZE image feature extraction algorithm | Journal of Real-Time Image Processing
Computing OpenSURF on OpenCL and General Purpose GPU - Wanglong Yan, Xiaohua Shi, Xin Yan, Lina Wang, 2013
