PhD student - abll@dtu.dk

Dept. of Applied Mathematics and Computer Science

Technical University of Denmark

Python/NumPy is great for numerical computing! For larger neural networks, however, GPU accelerated array operations are needed for decent run times. CUDArray tries to combine the easy of development from the NumPy with the computational power of Nvidia GPUs in a lightweight and extensible framework. While CUDArray only implements a small subset of NumPy it is mature enough to support a neural network pipeline as demonstrated in the deeppy project.

Larsen, A. B. L. (2014). * CUDArray: CUDA-based NumPy* (No. DTU Compute 2014-21). Department of Applied Mathematics and Computer Science, Technical University of Denmark.
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CUDArray is an open source project under the MIT license. Source and installation instructions are available from the Github repository.

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