Top 5 MATLAB Acceleration Techniques
Tools to tackle big data challenges with MATLAB
Quickly evaluate kernels, analyze and visualize results, write test harnesses to validate results
Assessing code performance, adopting efficient serial programming practices, generating C code, etc.
Overview of how to run MATLAB code on an NVIDIA CUDA-enabled GPU (Graphics Processing Unit)
MCXLAB is a Matlab toolbox for Monte Carlo simulations of photon transport in 3D heterogeneous media
Examples and reference materials for MATLAB GPU support via Parallel Computing Toolbox.
Jacket version 1.4 is used to test the performance differences of C2050 versus C1060
Information on simEngine, a MATLAB toolbox to accelerate ODE simulation using GPUs
The post contains some helpful hints for parallel computing as well as hints for working with Jacket
Learn how to stream data from disk directly to an Nvidia CUDA-capable GPU bypassing CPU memory.
Use cases for AccelerEyes, and Jacket for MATLAB by Torben Larsen.