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A Reconfigurable Multiplier for Signed Multiplications with Asymmetric Bit-Widths.

, , , , , , , and . ACM J. Emerg. Technol. Comput. Syst., 17 (4): 48:1-48:16 (2021)

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Regularization-Free Structural Pruning for GPU Inference Acceleration., , , , , , , and . ISQED, page 149-153. IEEE, (2021)A Convolutional Neural Network Accelerator Architecture with Fine-Granular Mixed Precision Configurability., , , , and . ISCAS, page 1-5. IEEE, (2020)A Reconfigurable Approximate Multiplier for Quantized CNN Applications., , , , and . ASP-DAC, page 235-240. IEEE, (2020)GANDSE: Generative Adversarial Network-based Design Space Exploration for Neural Network Accelerator Design., , , , , and . ACM Trans. Design Autom. Electr. Syst., 28 (3): 35:1-35:20 (2023)Landslide susceptibility assessment based on multi GPUs: a deep learning approach., , , , , and . CCF Trans. High Perform. Comput., 4 (2): 135-149 (2022)Single-Batch CNN Training using Block Minifloats on FPGAs., , , , and . FPGA, page 53. ACM, (2023)BOOST: Block Minifloat-Based On-Device CNN Training Accelerator with Transfer Learning., , , , , and . ICCAD, page 1-9. IEEE, (2023)A Reconfigurable Multiplier for Signed Multiplications with Asymmetric Bit-Widths., , , , , , , and . ACM J. Emerg. Technol. Comput. Syst., 17 (4): 48:1-48:16 (2021)Joint Sparsity with Mixed Granularity for Efficient GPU Implementation., , , , , and . DATE, page 1356-1359. IEEE, (2021)GANDSE: Generative Adversarial Network based Design Space Exploration for Neural Network Accelerator Design., , , , , and . CoRR, (2022)