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Memory Requirements for Convolutional Neural Network Hardware Accelerators.

, , , and . IISWC, page 111-121. IEEE Computer Society, (2018)

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