Embedded processors on FPGA: Hard-core vs Soft-core

Field Programmable Gate Arrays (FPGAs) are integrated circuits (ICs) that can be reprogrammed by the consumer after manufacturing. They are based on a matrix of configurable logic blocks connected via programmable interconnects that enables the designer to quickly recreate hardware circuits. In the past, FPGAs were primarily used for prototyping and debugging purposes. However, with their increased popularity, many commercial products now incorporate FPGAs. In the late 1990s, FPGA vendors introduced System-on-chip (SoC) devices that housed one or more hard-core processors and an FPGA fabric on a single IC to allow for more complex designs that involved hardware and software co-integration. While this approach provides advantages of running your design at much higher speeds it does not provide the flexibility of modification to suit the application. Because of this many FPGA vendors provide the solution of using soft-core processors that are configured from logic resources inside the FPGA. While this approach provides the advantage of flexibility they run at about 30% to 50% of the speed of the hard-core processors. Thus each approach has its own advantages and disadvantages. In this thesis, an application was developed to run on two different FPGA platforms. The first platform, Digilent Zybo FPGA board, houses an ARM-Cortex hard-core while the other, Digilent Nexys-4 board, implemented ARM-Cortex soft-core using FPGA resources. IP blocks were designed in Hardware Description Languages Verilog and VHDL to interface with the processor and it’s supported Bus Architecture (AXI/AHB). The application was written in C and assembly language and enacted the function of a Digital Oscilloscope. It used the ADC ports on the FPGA board to continuously read analog signals and plotted them as a dynamic waveform on a VGA monitor. Xilinx Vivado was the primary IDE used for HDL design, synthesis, simulation and implementation for both the platforms. Reports generated from Vivado as well as the run-time results were used to compare the two platforms and identify their strengths and weaknesses. Also discussed is the methodology for choosing either board over the other