This research develops photonic integrated circuits that compute using light instead of electrons. By creating integrated all-optical transistors and photonic neural networks, the work advances ultra-fast optical computing systems capable of dramatically outperforming conventional electronic processors in speed, efficiency, and future artificial intelligence applications.

This thesis presents the design and verification of a custom RISC-V processor implemented on Field-Programmable Gate Array (FPGA) technology. The project optimized hardware efficiency, achieved stable 50 MHz performance, and enabled software execution using SystemVerilog design and official benchmarks. It demonstrates how open-source hardware enables affordable, customizable computing solutions.