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This report presents SkePU, a C++ template library which provides a simple and unified interface for specifying data-parallel computations with the help of skeletons on GPUs using CUDA and OpenCL. The interface is also general enough to support other architectures, and SkePU implements both a sequential CPU and a parallel OpenMP back end. It also supports multi-GPU systems. Benchmarks show that copying data between the host and the GPU is often a bottleneck. Therefore a container which uses lazy memory copying has been implemented to avoid unnecessary memory transfers. SkePU was evaluated with small benchmarks and a larger application, a Runge-Kutta ODE solver. The results show that skeletal parallel programming is indeed a viable approach for GPU Computing and that a generalized interface for multiple back ends is also reasonable. The best performance gains are received when the computation load is large compared to memory I/O (the lazy memory copying can help to achieve this). We see that SkePU offers good performance with a mor