Papers by Arturo Argueta

    2 papers
    Composing Finite State Transducers on GPUs (P18-1)

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    Challenge: Weighted finite state transducers (FSTs) are used in language processing . a GPU implementation of the composition operation is currently under development .
    Approach: They propose a GPU implementation of the composition operation for weighted finite state transducers.
    Outcome: The proposed approach achieves speedups of up to 6 times over the serial implementation and 4.5 times over OpenFST on the GPU.
    Accelerating Sparse Matrix Operations in Neural Networks on Graphics Processing Units (P19-1)

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    Challenge: Graphics Processing Units (GPUs) are used to train and evaluate neural networks efficiently.
    Approach: They propose two new GPU algorithms for multiplying a matrix by a few-hot vector and fused softmax and top-N selection.
    Outcome: The proposed algorithms achieve speedups over state-of-the-art parallel GPU baselines of up to 7x and 50x, respectively.

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