Category: GPU computing

• Theano: numerical computation in Python

  Theano is a very interesting numeric library for Python that I covered briefly a few years ago. Coming from the machine learning group at Université de Montréal – i.e. Yoshua Bengio et al. – it is well adapted to the kinds of numerical tasks that frequently occur in machine learning problems, in particular deep neural…

  January 26, 2014

• GPU computing: which card should you get?

  Running number-crunching code on a top-of-the-line graphics card can be 10x faster than on a comparably high-end CPU. Not every application will see a 10x benefit – Monte Carlo simulations, image processing, matrix-vector-product-heavy code are excellent candidates. Thanks to general-purpose linear-algebra-on-the-GPU classes – like gpuarray, gnumpy and Data.Array.Accelerate – it’s possible to run high-level Matlab, Python…

  December 25, 2013

• Memory management in gnumpy

  I’m working on a project using gnumpy, which is a wrapper for CUDAmat, a toolbox for GPU computation in Python. I was having memory management issues, where the script would crash after the memory on the graphics card would fill up. I kept trying to delete the variables via del but this seemed to have…

  April 21, 2013