amhndu/SimpleNES

86Box is a low-level x86 hardware emulator and vintage PC simulator designed to replicate early IBM PC compatibles. It provides virtualized environments for executing legacy operating systems, such as MS-DOS and early versions of Windows, by simulating processors and system designs ranging from the 8086 through the Pentium era. The project distinguishes itself through cycle-accurate processor simulation and high-fidelity hardware emulation. This includes the ability to route retro MIDI audio data to emulated hardware modules or external synthesizers to achieve authentic audio playback from le

DuckStation is a high-performance PlayStation 1 emulator that simulates the original console's hardware logic and CPU and GPU on modern computer systems. It functions as a console hardware emulator, disc image loader, and game state manager to execute original games and preserve retro software. The project differentiates itself through a game graphics upscaler that improves visual clarity using texture filtering, geometry precision corrections, and custom shader chains. It also features advanced memory manipulation tools for layered patch injection and the application of community cheat codes

mGBA is a high-accuracy Game Boy Advance emulator and hardware-level debugger designed to run handheld console ROMs on modern computers. It serves as a scriptable emulation environment that allows for the execution of portable hardware software and the simulation of associated peripherals. The project distinguishes itself through its focus on technical analysis, providing a suite of tools for retro game debugging and game logic inspection. It includes a host-client debug protocol that enables external debugger connectivity via TCP socket communication and an event-driven scripting engine for

PyBoy is a programmable Game Boy emulator and hardware simulation framework written in Python. It functions as an emulation engine that allows users to execute original handheld software while providing a programmatic interface to control, probe, and automate game execution. The project is specifically designed as a reinforcement learning environment, exposing emulator states and controls to facilitate the training of machine learning agents. It distinguishes itself by providing tools for game area mapping and the extraction of simplified 2D screen representations and collision maps to suppor