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HOW TRANSISTORS RUN CODE?

HOW TRANSISTORS RUN CODE?

Core Dumped

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[00:00]

this video is sponsored by brilliant

[00:02]

transistors are very simple components

[00:05]

they are basically electronic switches

[00:07]

when we apply current to one of its

[00:09]

terminals a transistor lets electricity

[00:11]

pass through but how can this simple

[00:14]

Behavior make computers

[00:15]

possible in today's video we are going

[00:18]

to learn how transistors can be used to

[00:20]

achieve more complex

[00:22]

tasks like doing math and even

[00:24]

interpreting

[00:27]

instructions hi friends my name is

[00:30]

George and this is core dumped before we

[00:33]

begin just a reminder that you can find

[00:35]

me on social media and our Discord

[00:36]

server where I'm available to answer

[00:38]

your questions and by the way I keep

[00:41]

getting requests to use my own voice

[00:42]

instead of using text to speech the

[00:44]

reason I don't record myself is because

[00:46]

I grew up in South America and I'm not a

[00:48]

native English speaker so I hope you

[00:50]

like modern family cuz once I start

[00:52]

recording myself that's what it will

[00:53]

sound

[00:55]

like Anyway let's start a single

[00:58]

transistor typically has three terminals

[01:01]

a collector an emitter and a base in a

[01:04]

circuit it can act as an insulator

[01:06]

preventing electricity from flowing

[01:07]

between the collector and emitter

[01:09]

terminals but if we apply a small

[01:11]

current to the base terminal it acts as

[01:13]

a conductor allowing electricity to

[01:16]

flow essentially a transistor can be

[01:18]

seen as a switch but instead of

[01:20]

mechanical movement it operates by using

[01:22]

electrical

[01:24]

signals in this example circuit we are

[01:26]

using a transistor to turn on and off an

[01:28]

LED by utilizing the base terminal as an

[01:31]

input and the emitter terminal as an

[01:33]

output signal we can mimic the input

[01:36]

signal with a switch and visually

[01:37]

represent the output signal with the

[01:41]

LED let's dub this a simple gate in a

[01:44]

simple gate when the input is zero the

[01:46]

output is zero when the input is one the

[01:49]

output is

[01:51]

one now let's tweak things a bit here

[01:54]

when the input is zero the LED is on due

[01:57]

to the way it is arranged within the

[01:58]

circuit but pay attention to this

[02:01]

setting the input to one causes the LED

[02:03]

to turn off indicating to us the output

[02:06]

is a zero this setup is commonly

[02:08]

referred to as an inverter or a not

[02:11]

gate this may seem a bit confusing this

[02:14]

video I found on Twitter is a perfect

[02:16]

example of this

[02:24]

effect and if you want more details you

[02:26]

can watch this video by Ben eer where he

[02:29]

explains all this using real

[02:31]

components we're not limited to just one

[02:34]

transistor by using multiple transistors

[02:36]

we can achieve more complex Behavior if

[02:39]

two transistors are connected in series

[02:41]

when both inputs are zero the output

[02:43]

will be zero because both transistors

[02:45]

act as insulators similarly if either

[02:48]

input is zero the output will be zero

[02:52]

the only way to obtain a one in the

[02:53]

output is by having both transistors act

[02:55]

as conductors which happens when both

[02:57]

inputs are set to one

[03:00]

this is where we begin to apply a

[03:01]

powerful concept called abstraction

[03:04]

instead of focusing on the individual

[03:06]

transistors in the circuit we can

[03:07]

abstract this into a white box a box

[03:10]

that consistently outputs a specific

[03:12]

value based on two given

[03:15]

inputs this is known as an and gate an

[03:18]

and gate outputs a value of one if and

[03:21]

only if both inputs are one otherwise

[03:23]

the output will be

[03:27]

zero if we connect the transistors in

[03:29]

parallel when both transistors act as

[03:32]

insulators electricity cannot

[03:34]

flow but in this setup having any

[03:37]

transistor acting as conductor is enough

[03:39]

to allow electricity to

[03:41]

flow so in this arrangement to get an

[03:43]

output of one is not strictly necessary

[03:46]

to set both inputs to

[03:48]

one once more we can abstract this

[03:51]

circuit into a box known as an or gate

[03:55]

an or gate outputs a value of zero if

[03:57]

and only if both inputs are zero

[04:00]

otherwise it outputs a value of

[04:03]

one these circuits known as logic gates

[04:05]

are so fundamental that instead of

[04:07]

representing them with boxes each one is

[04:09]

assigned a dedicated

[04:11]

symbol notice that since inputs and

[04:14]

outputs are electrical signals we can

[04:16]

connect the output of one logic gate to

[04:18]

the input of another this allows us to

[04:21]

combine logic gates to achieve even more

[04:23]

complex

[04:24]

behavior for example if we desire this

[04:27]

particular Behavior we can combine logic

[04:29]

G Gates accordingly to achieve

[04:35]

it this is where we begin to see the

[04:37]

power of abstractions while this setup

[04:40]

is ultimately composed of transistors

[04:42]

it's much simpler to understand what's

[04:44]

happening by thinking in terms of logic

[04:46]

gates this circuit is known as an xor

[04:49]

gate and it is also very important in

[04:51]

computer science so it has its own

[04:54]

symbol and now that we understand what

[04:57]

logic gates are let's use them to create

[04:59]

more use ful things let's start with

[05:02]

adders adding binary numbers is actually

[05:04]

quite simple in fact binary addition

[05:06]

works just like decimal addition 0 + 0 =

[05:10]

0 0 + 1 = 1 1 + 0 = 1 and 1 + 1 = two

[05:17]

however the value two cannot be

[05:18]

represented with a single binary digit

[05:21]

when this occurs we say the addition has

[05:23]

overflowed meaning we require an

[05:25]

additional bit to represent the value so

[05:27]

what we're aiming for is a circuit that

[05:29]

takes two input values and produces two

[05:31]

outputs the sum and the

[05:34]

carry let's break down the

[05:36]

sum but before a quick message from

[05:39]

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have to be synonymous with mindlessly

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scrolling through a

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[06:00]

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aiming to enhance their problem solving

[06:04]

abilities brilliant is an ideal platform

[06:07]

it's latest course thinking in code lays

[06:10]

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[06:11]

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premium and a lifetime 20% discount when

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subscribing by accessing brilliant.org

[06:31]

dumped or by using the link in the

[06:34]

description below and now back to the

[06:36]

video let's break down the sum we

[06:39]

require a circuit that outputs zero when

[06:41]

both inputs are the same and one when

[06:43]

they differ does this sound familiar

[06:46]

it's precisely what an exor gate

[06:48]

accomplishes so we've already solved

[06:50]

half of the puzzle for the carry output

[06:53]

we need a circuit that outputs the value

[06:55]

one only when both inputs are

[06:57]

one this matches the behavior of and

[07:01]

gate and there we have it we've crafted

[07:04]

a circuit capable of adding two singled

[07:06]

digigit binary

[07:08]

numbers okay but what about multi-digit

[07:10]

binary

[07:11]

addition well let's try since we have to

[07:15]

add numbers in each row using one Adder

[07:17]

for each row seems logical it works well

[07:20]

for the first row but when we move to

[07:21]

the second row there's an

[07:24]

issue we need to consider that the

[07:26]

previous row might have created a carry

[07:28]

but because the adder circuit only

[07:29]

accepts two inputs it doesn't account

[07:31]

for this carry because of this

[07:34]

limitation this circuit is known as a

[07:36]

half adder and it is not useful in this

[07:39]

scenario what we need is a full adder a

[07:42]

circuit that can handle not only the two

[07:44]

bits being added but also take into

[07:46]

account the carry from a previous

[07:48]

addition here's the circuit we're

[07:49]

working towards think of it as a circuit

[07:52]

capable of adding three singled digigit

[07:54]

binary

[07:57]

numbers to simplify matters we can

[08:00]

encapsulate this in a box which we'll

[08:02]

call a full

[08:04]

adder with full adders we can now add

[08:07]

multi-digit binary

[08:09]

numbers the carry output of each full

[08:11]

adder feeds directly into the carry

[08:12]

input of the next full adder as shown

[08:14]

here in this

[08:17]

animation to add binary numbers of n

[08:19]

digits in one go n full adders are

[08:21]

needed for example if we aim to add two

[08:24]

8 bit numbers we'll need eight full

[08:27]

adders remember that values are

[08:29]

represent Ed here using electrical

[08:30]

signals since electricity moves at

[08:32]

incredible speed once we alter the input

[08:35]

the output changes almost instantly and

[08:38]

this is what makes transistors ideal for

[08:39]

this job while logic gates can be

[08:42]

crafted from other components like

[08:43]

relays and even fancy 3D printed Parts

[08:46]

powered by weird stuff like marbles or

[08:48]

even water none of this matches the

[08:50]

speed and compactness of

[08:52]

transistors before Things become overly

[08:55]

complex we can one more time package all

[08:57]

of this functionality into a special

[08:59]

component known as an 8bit

[09:01]

Adder an 8bit Adder takes two 8-bit

[09:04]

numbers as input and produces the sum of

[09:06]

the inputs as another 8bit number it

[09:08]

also provides an overflow signal which

[09:10]

is essentially the carry out output of

[09:12]

the last full adder inside this overflow

[09:15]

signal is crucial because it informs us

[09:17]

whether the storage capacity being

[09:19]

utilized is adequate to represent the

[09:20]

result of the

[09:22]

operation in this example both inputs

[09:24]

are one bite long but if we attempt to

[09:27]

store the output in just one bite we

[09:29]

will miss information resulting in an

[09:31]

incorrect

[09:32]

value by monitoring the Overflow output

[09:35]

we can recognize the need for an extra

[09:36]

bite to accurately store the

[09:39]

output believe it or not neglecting to

[09:42]

manage operation overflows can lead to

[09:44]

undefined Behavior sometimes with severe

[09:46]

consequences like this rocket accident

[09:48]

in

[09:53]

1996 and we can continue to move to

[09:55]

higher levels of abstraction if we want

[09:57]

to make a circuit that increments an

[09:59]

input value we can simply use an adder

[10:02]

and set the second input to always be

[10:04]

one we've only talked about adders in

[10:07]

detail but in the end it's all about

[10:09]

logic gates with them we can make more

[10:11]

useful things like a full subtractor

[10:13]

that then can be used to build an 8 bit

[10:17]

subtractor and from there we could keep

[10:20]

going and make even more complicated

[10:22]

stuff as you may have guessed inside the

[10:25]

CPU there's a special component that

[10:27]

houses all these circuits for now let's

[10:30]

call it our mysterious

[10:32]

component the question we want to answer

[10:35]

now is when a CPU reads an instruction

[10:37]

how does it identify which one of these

[10:39]

circuits corresponds to that specific

[10:41]

instruction how does the computer

[10:43]

discern adding numbers upon encountering

[10:45]

a particular instruction and subtract

[10:47]

them upon encountering

[10:48]

another I mean some instructions aren't

[10:51]

even arithmetic

[10:53]

operations the last type of component we

[10:55]

are covering today are binary

[10:57]

decoders let's take a look at this

[10:59]

circuit and examine the output for every

[11:01]

input combination the first thing we can

[11:03]

notice here is that each combination

[11:05]

triggers a specific output to activate

[11:07]

while deactivating all other

[11:10]

outputs another way to see it is that

[11:12]

the circuit receives the binary number

[11:14]

that corresponds to the position of the

[11:16]

output we wish to

[11:18]

activate this is what binary decoders do

[11:22]

when it receives an input one and only

[11:24]

one output has the value of one with all

[11:26]

others outputting the value of zero

[11:30]

if we have a decoder with three inputs

[11:32]

we can control which of eight outputs

[11:33]

turns

[11:34]

on four inputs well we can control 16

[11:38]

outputs and so

[11:40]

on this is huge because it means that we

[11:43]

are also capable of creating circuits

[11:45]

that can select among multiple

[11:48]

options now remember that assembly code

[11:51]

is just a humanfriendly representation

[11:52]

of machine code the actual code

[11:55]

consisting of ones and zeros that

[11:57]

computers comprehend

[11:59]

not all instructions are arithmetic

[12:01]

operations some of them are instructions

[12:03]

dedicated to fetch and write data to

[12:04]

memory and other stuff like that let's

[12:07]

imagine a very basic architecture where

[12:09]

if the first two bits of an instruction

[12:11]

are zeros the computer interprets them

[12:13]

as arithmetic operation

[12:15]

instructions in this example to verify

[12:18]

this we could employ nor Gates given the

[12:21]

scope of this video at the moment we are

[12:22]

not concerned with instruction that

[12:24]

signifies something else but at least we

[12:26]

know how to identify between them

[12:29]

in this example architecture the third

[12:31]

and fourth bits will determine the type

[12:33]

of arithmetic operation to be executed

[12:35]

for instance if those bits are 0 0 it

[12:38]

means addition if 01 it represents

[12:41]

subtraction and so forth this is

[12:43]

commonly known as an OP code each op

[12:46]

code is associated with one and only one

[12:48]

kind of arithmetic

[12:50]

operation when the CPU has determined

[12:52]

that the current instruction is an

[12:53]

arithmetic operation Our Mysterious

[12:56]

component receives this op code and

[12:58]

internally links those two bits to a

[12:59]

decoder which is used to identify the

[13:02]

desired internal

[13:04]

operation the straightforward approach

[13:06]

here would be by allowing all circuits

[13:08]

to receive the inputs and generate their

[13:10]

respective outputs but the outputs of

[13:12]

the decoder are interconnected in a way

[13:14]

that allows only the output of the

[13:15]

selected operation to pass through this

[13:20]

component keep in mind that there are

[13:22]

more efficient ways to do this but here

[13:24]

we focus on

[13:25]

Simplicity Our Mysterious component can

[13:28]

also be enclosed with within a box this

[13:30]

is a rudimentary and somewhat incomplete

[13:32]

version of something known as an

[13:33]

arithmetic logic

[13:35]

unit we'll talk about this component in

[13:38]

more detail in a future episode where we

[13:40]

discuss how CPUs execute instructions

[13:42]

but beforehand an arithmetic logic unit

[13:45]

takes input values and an OP code that

[13:47]

tells the internal circuitry what

[13:49]

arithmetic operation to perform between

[13:51]

those values it then produces the result

[13:53]

of the specified operation along with

[13:55]

additional information such as whether

[13:57]

the result is negative 0 or if it has

[14:01]

overflowed and this was a very very very

[14:03]

brief introduction to how computers use

[14:05]

transistors to do math and follow

[14:08]

instructions well sort of because we

[14:10]

completely avoided an important concept

[14:13]

memory but that's a topic for a future

[14:15]

video so make sure to subscribe because

[14:18]

you don't want to miss it and that's it

[14:20]

for this episode don't forget to hit

[14:22]

that like button if you enjoyed this

[14:24]

video or learned something it's free and

[14:26]

that would help me a lot

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