Research

Adaptive Inference

Varying the amount of computation based on sample difficulty.

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Quantization of DNNs

Reducing the precision of weights and data to achieve better energy efficiency.

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Sparse Computation in DNNs

Enforcing structural sparsity in DNN weights for reduced computation that can be performed efficiently.

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Hardware Designs for DNN Inference

Mainly using systolic arrays, with a focus on integrating sparsity, quantization, and adaptive inference into the design.

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