Implementation of FPGA hardware acceleration using new (2018) Xilinx PYNQ-Z2 architecture. Accelerating data analytics of image processing using unsupervised K-Means clustering algorithms. Base image processing implemented in Python OpenCV K-Means clustering, including variations to function formats. Accelerated algorithm produced in C before being implemented to FPGA programmable logic. Control and interaction with the FPGA architecture conducted via the Python interface.
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Implementation of FPGA hardware acceleration using new (2018) Xilinx PYNQ-Z2 architecture. Acceleration conducted over unsupervised K-Means clustering algorithms. Base recordings taken over Python OpenCV K-Means clustering, as well as variations in formatting. Accelerated algorithm produced in C before being implemented on FPGA programmable logi…
robertdigital/Accelerated-Data-Analytics-Using-Python-Programmed-FPGA-Hardware
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Implementation of FPGA hardware acceleration using new (2018) Xilinx PYNQ-Z2 architecture. Acceleration conducted over unsupervised K-Means clustering algorithms. Base recordings taken over Python OpenCV K-Means clustering, as well as variations in formatting. Accelerated algorithm produced in C before being implemented on FPGA programmable logi…
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