# Input / Output Subsystem
Handles devices that allow the computer system to:

* Communicate and interact with the outside world
	- Screen, keyboard, printer

* Store information

![[io-subsystem.png]]

# The Control unit
Program stored in memory. (machine language in binary)

Task of control unit is to execute programs by:
* Fetch: from memory the next instruction
* Decode: instruction to determine what to do
* Execute: issuing signals to ALU, memory and IO systems.

Repeats until HALT instruction.

# Typical Machine Instructions
MOV: move data from a to b
ADD: add numbers
SUB: subtract numbers
JMP: transfers program control flow to the indicated instruction

![[example-machine-lang.png]]

# CPU Time vs IO Time
Total time required to run program is: CPU Time + IO Time

Typical time to read from IO: 20ms
Typical time to run instruction: 20ns
CPU can execute up to 200 million instructions while a block is read from a hard disk.

Conclusion: While I/O is executed, CPU is idling.

![[cpu-vs-io.png]]

Were waiting a lot on IO time to finish, very inefficient. We can solve this using multitasking!

# Multitasking
To speed up computers we overlap CPU time and IO Time.

While a program waits for IO, other programs can use CPU. This solution requires multiple programs to be loaded into memory, hence the name multitasking.

Multitasking overlaps IO time of a program with CPU time of other program.

# Multitasking with multiple processors
If computer has a single CPU, programs should take turns in using it.

If computer has multiple CPUS, each task can be given a different CPU.
	- If the number of tasks is more than available cpu's, we still take turns.
	
when program issues IO command, cpu is granted to the next program.

# Concurrent vs Parallel
**Concurrent**: Fast switching from a program to the next program (context switch) can create the illusion that they are being executed at the same time. -> **Logically Simultaneous**

**Parallel**: If the computer has multiple CPU's or Cores, the programs run in parallel. -> **Physically simultaneous**

![[conc-parallel.png]]

# Sharing Resources
Sometimes different programs (or same program) may share resources.

If data is **sequentially** accessible, programs should take turns accessing resource/data.

Fast shared resource access can create **concurrent** access.

# Concurrency
Unlike parallelism, concurrency is not always about running faster.
- Single cpu/core computers may also use concurrency.

Useful for:
- App responsiveness.
- Processor utilization (hide IO time)
- Failure isolation