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Energy-efficient acceleration of big data analytics applications using FPGAs.

, , , , and . IEEE BigData, page 115-123. IEEE Computer Society, (2015)

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Exploiting Energy-Accuracy Trade-off through Contextual Awareness in Multi-Stage Convolutional Neural Networks., , , and . ISQED, page 265-270. IEEE, (2019)ICNN: An iterative implementation of convolutional neural networks to enable energy and computational complexity aware dynamic approximation., , , and . DATE, page 551-556. IEEE, (2018)Enhancing Power, Performance, and Energy Efficiency in Chip Multiprocessors Exploiting Inverse Thermal Dependence., , , and . IEEE Trans. Very Large Scale Integr. Syst., 26 (4): 778-791 (2018)Accelerating Big Data Analytics Using FPGAs., , , and . FCCM, page 164. IEEE Computer Society, (2015)Revisiting Dynamic Thermal Management Exploiting Inverse Thermal Dependence., , , and . ACM Great Lakes Symposium on VLSI, page 385-390. ACM, (2015)Hadoop Workloads Characterization for Performance and Energy Efficiency Optimizations on Microservers., , , and . IEEE Trans. Multi Scale Comput. Syst., 4 (3): 355-368 (2018)Energy-efficient acceleration of MapReduce applications using FPGAs., , , , , , and . J. Parallel Distributed Comput., (2018)A low-complexity high-throughput ASIC for the SC-FDMA MIMO detectors., , and . ISCAS, page 3065-3068. IEEE, (2012)A High-Throughput VLSI Architecture for Hard and Soft SC-FDMA MIMO Detectors., , and . IEEE Trans. Circuits Syst. I Regul. Pap., 62-I (3): 761-770 (2015)ICNN: The Iterative Convolutional Neural Network., , and . ACM Trans. Embed. Comput. Syst., 18 (6): 119:1-119:27 (2020)