Publisher
Springer Nature Switzerland
Reference21 articles.
1. Alcolea, A., Resano, J.: FPGA accelerator for gradient boosting decision trees. Electronics 10(3) (2021). https://doi.org/10.3390/electronics10030314
2. AMD Xilinx: Vivado overview (2023). https://www.xilinx.com/products/design-tools/vivado.html
3. Biookaghazadeh, S., Zhao, M., Ren, F.: Are FPGAs suitable for edge computing? In: USENIX Workshop on Hot Topics in Edge Computing (HotEdge 18). USENIX Association, Boston, MA, July 2018
4. Breiman, L.: Random forests. Mach. Learn. 45(1), 5–32 (2001)
5. Chen, R., Wu, T., Zheng, Y., Ling, M.: MLoF: machine learning accelerators for the low-cost FPGA platforms. Appl. Sci. 12(1) (2022). https://doi.org/10.3390/app12010089