
.. _cifar2013_gpundarray:

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GpuNdArray
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Why a common GPU ndarray?

- Currently there are at least 4 different GPU array data structures in use by Python packages

  - CudaNdarray (Theano), GPUArray (PyCUDA), CUDAMatrix (cudamat), GPUArray (PyOpenCL), ...
  - There are even more if we include other languages

- All of them are a subset of the functionality of ``numpy.ndarray`` on the GPU
- Lots of duplicated effort

  - GPU code is harder/slower to do {\bf correctly} and {\bf fast} than on the CPU/Python

- Lack of a common array API makes it harder to port/reuse code
- Also harder to find/distribute code
- Divides development work


Design Goals

- Make it VERY similar to ``numpy.ndarray``
- Be compatible with both CUDA and OpenCL
- Have the base object accessible from C to allow collaboration with more projects, across high-level languages

  - We want people from C, C++, Ruby, R, ... all use the same base GPU N-dimensional array


Final GpuNdArray Note

- Under development
- Will be the next GPU array container for Theano (this summer!)
- Probably also for PyCUDA, PyOpenCL
- Mailing list: http://lists.tiker.net/listinfo/gpundarray

