There is a lot to read every time MATLAB releases a new version. Here is a summary of what has changed in 2016a from the eyes of someone doing HPC/Scientific Computing/Numerical Analysis. This means I will leave off a lot, and you should check it out yourself but if you’re using MATLAB for science then this may cover most of the things you care about.

1. Support for sparse matrices on the GPU. A nice addition is sprand and pcg (Preconditioned Conjugate Gradient solvers) for sprase GPU matrices.
2. One other big change in the parallel computing toolbox is you can now set nonlinear solvers to estimate gradients and Jacobians in parallel. This should be a nice boost to the MATLAB optimization toolbox.
3. In the statistics and machine learning toolbox, they added some algorithms for high dimensional data and now let you run kmeans … READ MORE