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An Incremental Placement Flow for Advanced FPGAs With Timing Awareness., , , , , и . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 41 (9): 3092-3103 (2022)Invited: Algorithm-Software-Hardware Co-Design for Deep Learning Acceleration., , , , и . DAC, стр. 1-4. IEEE, (2023)FPGA-aware automatic acceleration framework for vision transformer with mixed-scheme quantization: late breaking results., , , , , , , , , и 2 other автор(ы). DAC, стр. 1394-1395. ACM, (2022)TAAS: a timing-aware analytical strategy for AQFP-capable placement automation., , , , , , и . DAC, стр. 1321-1326. ACM, (2022)Late Breaking Results: An Analytical Timing-Driven Placer for Heterogeneous FPGAs*., , , , , и . DAC, стр. 1-2. IEEE, (2020)Hardware-efficient stochastic rounding unit design for DNN training: late breaking results., , , , , , , , , и 2 other автор(ы). DAC, стр. 1396-1397. ACM, (2022)Machine Learning Across Network-Connected FPGAs., , , , , и . HPEC, стр. 1-7. IEEE, (2023)A Life-Cycle Energy and Inventory Analysis of Adiabatic Quantum-Flux-Parametron Circuits., , , , , , , и . CoRR, (2023)Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training., , , , , , , , , и 5 other автор(ы). AAAI, стр. 8360-8368. AAAI Press, (2023)ESRU: Extremely Low-Bit and Hardware-Efficient Stochastic Rounding Unit Design for Low-Bit DNN Training., , , , , , , , , и 2 other автор(ы). DATE, стр. 1-6. IEEE, (2023)