Abstract:Parallelized algorithms can distribute the workload on the available multi-core processors. Graphical Processing Units (GPU) began to be used in general purpose computing thanks to its ability to simultaneously perform thousands of operations in their parallel coprocessors. Unfortunately, providing parallelized versions of typical sequential routines is not a trivial task. Even with the advent of CUDA, the NVIDIA's more intuitive solution for GPU programming, developers need to acquire a deep knowledge of GPU … Show more
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