A single index of interactive simulators across Computer Science, Computing, AI, and ICT. Use the filter to find exactly what you need in seconds.
A-levels
6 item(s)
Advanced CPU: Registers, Buses & the Fetch–Decode–Execute Cycle
Explore the CPU in more depth. Follow instructions and data as they move through registers such as the PC, MAR, MDR, CIR and ACC, and see how the Control Unit, ALU, memory and the three buses work together during the Fetch–Decode–Execute cycle. You can also explore pipelining, CPU architecture and performance.
Follow C# source code through the stages of compilation, from tokens and syntax checking to semantic analysis, optimisation and generated intermediate code.
Explore the physical hardware used to build computer networks. Learn to recognise devices such as routers, switches, hubs, wireless access points, NICs, firewalls, cables and network storage, and discover what each one does.
See how a CPU responds to interrupts while running a program. Watch it save its current state, handle interrupt priorities, run an interrupt routine and then continue where it left off.
Explore how a D-type flip-flop stores one bit of data. Change the input and follow the timing diagram to see when the output changes and when it keeps its stored value.
Explore a computer system in interactive 3D. Discover external devices and look inside the PC to learn what components such as the CPU, RAM, storage and motherboard do.
Follow instructions and data as they move through the CPU. See the registers, Control Unit, ALU and memory working together during the Fetch–Decode–Execute cycle.
See how an operating system shares processor time between several running applications. Compare how multitasking works with different numbers of CPU cores.
Explore how devices connect and communicate across local and wide area networks. Watch data move around a LAN and across wider networks, then compare different network topologies and see how the layout affects routes and reliability.
See how an analogue sound wave becomes digital data. Experiment with sample rate and bit depth to understand sampling, quantisation, sound quality and file size.
Train an AI to recognise road objects and watch the neural network improve. See how weights, hidden layers, training examples and unseen test data affect accuracy
Watch AI agents learn through rewards and penalties. See how exploration, experience and Q-values gradually help them discover better routes to a goal.