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Memory Requirements for Convolutional Neural Network Hardware Accelerators.

, , , и . IISWC, стр. 111-121. IEEE Computer Society, (2018)

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Investigating the Effects of Dynamic Precision Scaling on Neural Network Training., и . CoRR, (2018)GPU - Accelerated Parameter Selection for Neural Connectivity Analysis Devices., , , , , , и . BioCAS, стр. 1-4. IEEE, (2018)Bit-Tactical: Exploiting Ineffectual Computations in Convolutional Neural Networks: Which, Why, and How., , , , , , , и . CoRR, (2018)Accelerating Image-Sensor-Based Deep Learning Applications., , , , , , , , , и 1 other автор(ы). IEEE Micro, 39 (5): 26-35 (2019)Bit-Tactical: A Software/Hardware Approach to Exploiting Value and Bit Sparsity in Neural Networks., , , , , , , , и . ASPLOS, стр. 749-763. ACM, (2019)ShapeShifter: Enabling Fine-Grain Data Width Adaptation in Deep Learning., , , , , , , , , и 1 other автор(ы). MICRO, стр. 28-41. ACM, (2019)Laconic deep learning inference acceleration., , , , , , , и . ISCA, стр. 304-317. ACM, (2019)Memory Requirements for Convolutional Neural Network Hardware Accelerators., , , и . IISWC, стр. 111-121. IEEE Computer Society, (2018)Identifying and Exploiting Ineffectual Computations to Enable Hardware Acceleration of Deep Learning., , , , , , , , , и 3 other автор(ы). NEWCAS, стр. 356-360. IEEE, (2018)