Design of RISC Processor with IEEE754 Standard Floating-Point Instruction Set in FPGA using VHDL for Digital Signal Processing Applications

Year 2022, Volume: 15 Issue: 3, 699 - 714, 30.12.2022

Bahadır Özkılbaç , Tevhit Karacalı

https://doi.org/10.18185/erzifbed.1077921

Abstract

The design of RISC processors, which are the key of digital signal processing applications, are increasing in reconfigurable hardware. FPGAs are suitable reconfigurable hardware for RISC processor design, with advantages such as parallel processing and low power consumption. In this study, the design of the 32-bit RISC processor in a FPGA is presented. The designed RISC processor contains IEEE754 standard floating-point number processing unit, which is executed in one clock cycle. The verification of the processor is performed for the Zynq-7000 SoC Artix-7 FPGA chip in the Xilinx Vivado tool. Classification of an artificial neural network using the iris dataset is carried out in this designed RISC processor. In order to compare the performance, the same artificial neural network is executed in real time in the dual-core ARM Cortex-A9 processor in the operating system of the Zynq-7000 SoC. The results show that the RISC processor designed in the FPGA executes at 20x less clock cycles and 3x higher speed compared to the ARM processor.

Keywords

reconfigurable hardware

Design of RISC Processor with IEEE754 Standard Floating-Point Instruction Set in FPGA using VHDL for Digital Signal Processing Applications

Abstract

The design of RISC processors, which are the key of digital signal processing applications, are increasing in reconfigurable hardware. FPGAs are suitable reconfigurable hardware for RISC processor design, with advantages such as parallel processing and low power consumption. In this study, the design of the 32-bit RISC processor in a FPGA is presented. The designed RISC processor contains IEEE754 standard floating-point number processing unit, which is executed in a one clock cycle. The verification of the processor is performed for the Zynq-7000 SoC Artix-7 FPGA chip in the Xilinx Vivado tool. Classification of an artificial neural network using the iris dataset is carried out in this designed RISC processor. In order to compare the performance, the same artificial neural network is executed in real time within the dual-core ARM Cortex-A9 processor in the operating system of the Zynq-7000 SoC. The results show that the RISC processor designed in the FPGA executes at 20x less clock cycles and 3x higher speed compared to the ARM processor.

Keywords

FPGA, ARM, RISC, Reconfigurable Hardware, reconfigurable hardware

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