Computational Storage for 3D NAND Flash Error Recovery Flow Prediction
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-48711-8_51
Reference23 articles.
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2. Calore, E., Schifano, S.F.: Performance assessment of FPGAs as HPC accelerators using the FPGA empirical roofline. In: 31th International Conference on Field-Programmable Logic and Applications (FPL), pp. 83–90 (2021). https://doi.org/10.1109/FPL53798.2021.00022
3. Chollet, F., et al.: Keras (2015). https://keras.io
4. Duarte, J., et al.: Fast inference of deep neural networks in FPGAs for particle physics. J. Instrument. 13(07), P07027 (2018). https://doi.org/10.1088/1748-0221/13/07/p07027
5. Goda, A.: Recent progress on 3D NAND flash technologies. Electronics 10(24) (2021). https://doi.org/10.3390/electronics10243156
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