Speaker 1: Inside the computer or the phone you're using right now.
Speaker 1: There are literally billions of microscopic water faucets.
Speaker 2: Yeah, billions of them.
Speaker 1: Right, And because we have spent decades engineering the pipes
Speaker 1: to be narrower and narrower, I mean down to just
Speaker 1: a few atoms wide, the water is actually starting to
Speaker 1: physically leak through the closed valves. We're basically hitting a
Speaker 1: hard limit on the laws of physics.
Speaker 2: Well, we are talking about electrons obviously, rather than actual water,
Speaker 2: but yeah, the physical reality of quantum tunneling and modern
Speaker 2: processors is frankly one of the most pressing issues in
Speaker 2: hardware design today. It's well, how to think about it
Speaker 2: really is. I mean, we abstract so much of this
Speaker 2: away when we use technology. It is incredibly easy to
Speaker 2: forget that we're ultimately just pushing physical electrons around on
Speaker 2: a piece of.
Speaker 1: Silicon, which is exactly our mission for you in this
Speaker 1: deep dive. We're peeling back that abstraction. Because you write code,
Speaker 1: you deploy servers, you run software every day. But today
Speaker 1: we're going to demystify the physical reality of how a
Speaker 1: computer actually.
Speaker 2: Computes right from the ground up exactly.
Speaker 1: We're going on a journey from a single microscopic electronic
Speaker 1: switch to a fully automated machine that can perform complex math.
Speaker 1: And to do this, we're using Douglas Comber's textbook Essentials
Speaker 1: of Computer Architecture, which is.
Speaker 2: A fantastic resource, by the way.
Speaker 1: It really is. It bridges that massive gap between the
Speaker 1: high level software you are used to and the incredibly
Speaker 1: fast microscopic hardware operating underneath it all.
Speaker 2: And you know, I think hardware can seem really impenetrable
Speaker 2: from the outside. This sheer scale of it, billions of
Speaker 2: components operating in fractions of a nanosecond, it's intimidating.
Speaker 1: Oh totally, it feels like magic.
Speaker 2: Right, But underneath all that complexity, hardware is actually built
Speaker 2: on a surprisingly small set of beautifully simple, repeatable principles.
Speaker 1: Okay, so to get to those principles, we have to
Speaker 1: start at the foundational layer. Right. Representing information, yes, because
Speaker 1: we are dealing with digital computation here, and that relies
Speaker 1: on discrete, precise values ones and zero.
Speaker 2: Ros exactly as opposed to the continuously varying signals of
Speaker 2: older analog computers.
Speaker 1: Right. But getting a machine to reliably represent a binary
Speaker 1: state took some serious trial in error. I mean we
Speaker 1: used mechanical relays originally, which were physically well, just too slow.
Speaker 2: Yeah, they literally had physical moving parts, right.
Speaker 1: And then we moved to vacuum tubes in the nineteen forties, which.
Speaker 2: To be fair, provided a massive leap in switching speed,
Speaker 2: but the physical drawbacks were just severe because of the heat.
Speaker 1: Heat.
Speaker 2: Yes, but also they required a glowing filament, so they
Speaker 2: generated immense heat and burned out continuously. I mean a
Speaker 2: team running a large tube based machine would have to
Speaker 2: halt computation constantly just to replace blown out components, like.
Speaker 1: Changing light bulbs in the middle of a math problem basically.
Speaker 1: But then came nineteen forty seven and the invention of
Speaker 1: the transistor. Yea, yeah, no filament, minimal heat, virtually indestructible.
Speaker 1: It changed everything, it really did. But to really grasp
Speaker 1: the modern transistor, specifically the moss FETE or metiloxide semiconductive
Speaker 1: fuel effect rigis, we need a quick grounding in electrical physics.
Speaker 2: Right, voltage and current.
Speaker 1: Okay, let's unpack this. Using one of the classic analogies
Speaker 1: from Comer's text, we can visualize this basic circuit as.
Speaker 2: Plumbing right, a very helpful way to think about it.
Speaker 1: So, voltage is the potential energy which acts like water
Speaker 1: pressure in the pipes, and current is the actual flow
Speaker 1: of the water the electrons through.
Speaker 2: Those pipes exactly. And the moss fat then introduces three
Speaker 2: distinct terminals into that plumbing system. You have a source,
Speaker 2: a drain, and a gate. Okay, the sort and the
Speaker 2: drain act as the two ends of your main water
Speaker 2: pipe where the current actually wants to flow, and the
Speaker 2: gate is positioned between them, acting as a valve.
Speaker 1: Okay, but here's where my understanding gets a little fuzzy though.
Speaker 1: If the gate is a valve, what physically turns it?
Speaker 2: Ah?
Speaker 1: Because like with a mechanical relay, you have a physical
Speaker 1: electromagnet pulling a switch, and with the vacuum tube you
Speaker 1: have heat. But with a moss fat, how does electricity
Speaker 1: act as its own hand? To turn the valve off
Speaker 1: and on?
Speaker 2: It relies on an electric field, hence the name field
Speaker 2: effect transistor. Yeah. So when you apply a specific voltage
Speaker 2: to that gate terminal, it generates an electric field that
Speaker 2: physically alters the properties of the silicon below it.
Speaker 1: Wait, it physically changes the silicon.
Speaker 2: Well, electrically alters it. It pulls electrons into a channel
Speaker 2: and suddenly that lowers the electrical resistance between the source
Speaker 2: and the drain, so the current can now flow.
Speaker 1: Wow.
Speaker 2: And then when you drop the voltage at the gate,
Speaker 2: the field collapses, the resistance spikes back up, and the
Speaker 2: flour just starps. So it's a completely non mechanical switch
Speaker 2: controlled purely by potential energy.
Speaker 1: That is brilliant. It just eliminates the physical wear and
Speaker 1: tear entirely exactly. And modern chips use CMOS technology right,
Speaker 1: complimentary metaloxide semiconductor. My understanding is that this relies on
Speaker 1: pairing two different types of these transistors together to manage
Speaker 1: power efficiently.
Speaker 2: Yes, because power management is absolutely critical when you have billions.
Speaker 1: Of these things right, otherwise your phone would just melt literally.
Speaker 2: So in a CMOS setup, you pair a transistor that
Speaker 2: turns on when voltage is high with one that turns
Speaker 2: on when voltage is low. This complementary pairing guarantees that
Speaker 2: in any stable state, one of the transistors is.
Speaker 1: Always off oh ICEE.
Speaker 2: So it's like a seesaw exactly. And because one is
Speaker 2: always blocking the path to ground, the circuit draws virtually
Speaker 2: zero static power. It only consumes significant energy during the
Speaker 2: microscopic fraction of a second when it is actively switching steats.
Speaker 1: That is incredibly elegant. So okay, we have our highly
Speaker 1: efficient non mechanical switch. But a switch just lets current
Speaker 1: through or stops it, right, that is just routing. How
Speaker 1: do we cross the bridge from routing plumbing to actual logic.
Speaker 2: Well, we assign Boolean meaning to the physical voltage, okay.
Speaker 2: Explain that by convention, a lack of voltage zero volts
Speaker 2: physically represents a Booleon full or a binary zero. Got it,
Speaker 2: And a positive voltage typically something like five volts in
Speaker 2: older systems, or even less than a volt in modern processors,
Speaker 2: represents a Booleian true or a binary one. Okay.
Speaker 1: So by wiring these transistors together in specific physical configurations,
Speaker 1: we create logic gates, the fundamental building blocks, right like
Speaker 1: A and D or are a not. So a knot
Speaker 1: gate or an inverter just flips the input positive voltage
Speaker 1: in yield zero volts out and vice versa. And comer
Speaker 1: points out that a knot gate only requires two of
Speaker 1: those complementary transistors we just talked about.
Speaker 2: Yeah, it's very simple, But then you also have the
Speaker 2: a and D gate, requiring both inputs to be positive
Speaker 2: to output a positive voltage, and the O R gate,
Speaker 2: where either input being positive triggers a positive output. But
Speaker 2: what's fascinating here is a disconnect between software design and
Speaker 2: hardware design.
Speaker 1: Oh yeah, I noticed this in the text.
Speaker 2: Right, because software engineers think natively in d and or logic,
Speaker 2: but at the hardware level, engineer's strong prefer nand meaning
Speaker 2: not and nore gates.
Speaker 1: Yeah, it seemed entirely counterintuitive to me. I mean, why
Speaker 1: would you want to build an architecture based on negative logic?
Speaker 1: Just makes the boolean expressions far more difficult to read.
Speaker 2: It does, but the preference is strictly dictated by the
Speaker 2: physical reality of the transistors. Building a nandgate is physically
Speaker 2: simpler and faster than building an ang gate.
Speaker 1: Wait really faster?
Speaker 2: How well? A nandgate only requires four transistors, But because
Speaker 2: an angate naturally outputs the inverted signal based on how
Speaker 2: the CMOS transistors are arranged, building a true andy gate
Speaker 2: actually requires building a nangate first.
Speaker 1: Oh wow.
Speaker 2: Yeah, and then you have to wire an additional two
Speaker 2: transistor not gate to the end of it just to
Speaker 2: flick the signal back to positive logic.
Speaker 1: So it's six transistors instead of four exactly, So it
Speaker 1: takes more physical components, more space, and more power just
Speaker 1: to get the positive logic right. That physical cost directly
Speaker 1: shapes the logical architecture.
Speaker 2: That is so interesting. It actually reminds me of the
Speaker 2: classic seventy four hundre undred family of TTL chips, the
Speaker 2: Transistor Logic series. Oh classic, yeah, for anyone who has
Speaker 2: ever built a hobbyist circuit board, these are the little
Speaker 2: black rectangular plastic chips with metal legs sticking out fourteen
Speaker 2: pin dip or duel in line package.
Speaker 1: Right. The seventy four hundred chip is the quintessential example
Speaker 1: of early digital.
Speaker 2: Logic packaging because inside that single tiny plastic box you
Speaker 2: literally just have four independent man gates.
Speaker 1: You have pins for power and ground to run the chip,
Speaker 1: and the remaining pins are simply the physical inputs and
Speaker 1: outputs for those four gates. It makes the abstract concept
Speaker 1: of a truth table very real.
Speaker 2: It really does, because you.
Speaker 1: Can physically measure the voltage on pin three based on
Speaker 1: what voltage you applied to pins one.
Speaker 2: And two, And those truth tables are the map engineers
Speaker 2: used to verify that the physical layout of these transistors
Speaker 2: will perfectly execute a specific boolean expression like checking your
Speaker 2: math exactly. You map every possible combination of high and
Speaker 2: low voltage inputs to get guarantee the output matches your
Speaker 2: logical intent.
Speaker 1: Which we desperately need because having dates that can perform
Speaker 1: basic logic like if a is true and b is
Speaker 1: false isn't quite enough to run software.
Speaker 2: No, it's not.
Speaker 1: At some level, the computer must be able to perform
Speaker 1: actual arithmetic. I mean, it has to add binary numbers together.
Speaker 2: Right, And this moves us into combinatorial circuits, where we
Speaker 2: combine multiple gates to create a more complex direct output.
Speaker 2: So to add two single binary bits together, say a
Speaker 2: one in a one, which in binary results in a
Speaker 2: zero with a carried one, we use a circuit called
Speaker 2: a half adder.
Speaker 1: Okay, So the half adder takes two bits as input
Speaker 1: and needs to output a some bit and a carry
Speaker 1: bit correct, So it splits the input signal down two paths.
Speaker 1: One path goes into an XR gate an exclusive or gate.
Speaker 2: Right, and remember the xor only outputs true if one
Speaker 2: input is true, but not both.
Speaker 1: Okay, So one closed zero outputs a one yes, but
Speaker 1: one plus one outputs a zero exactly.
Speaker 2: That handles the sum portion, got it, But what about
Speaker 2: the carry well Well, simultaneously, the other path feeds those
Speaker 2: same two inputs into a standard A and D gate
Speaker 2: to compute the carry bit.
Speaker 1: Ah, because a binary edition only carries a one to
Speaker 1: the next column if both input A and input B
Speaker 1: are true precisely. Okay, so a half adder handles a
Speaker 1: single column perfectly, but any column past the first one
Speaker 1: might have to deal with a carry bit coming over
Speaker 1: from the right.
Speaker 2: Right, So it needs to add three inputs bit A,
Speaker 2: bit B and the carry.
Speaker 1: In bit, which means we need something more complex.
Speaker 2: Yes, that requires a full adder. Oh and it is
Speaker 2: constructed by physically wiring two half adders together along with
Speaker 2: an O R gate to resolve the final carryout signal.
Speaker 1: That makes sense.
Speaker 2: And if we connect this to the bigger picture, this
Speaker 2: specific arrangement of logic gates represents a profound conceptual threshold.
Speaker 2: How so we are no longer just manipulating water pressure
Speaker 2: in a pipe. By layering truth tables and combining gates,
Speaker 2: we have actually engineered a machine.
Speaker 1: That computes Wow. Yeah, the modularity of it is what
Speaker 1: strikes me, because if you are designing a thirty two
Speaker 1: bit processor. You don't have to invent a monolithic, wildly
Speaker 1: complex circuit to add thirty two bit numbers. Oh not
Speaker 1: at all. You just take that single full add or blueprint,
Speaker 1: physically replicate it thirty two times on the silicon, and
Speaker 1: chain them side by side. The carry out wire of
Speaker 1: column one connects directly to the carrying wire of column.
Speaker 2: Two, exactly. It is endlessly scalable.
Speaker 1: That's incredible.
Speaker 2: The architecture scales beautifully, and the sum cascades down the
Speaker 2: chain of adders almost instantaneously.
Speaker 1: But wait here is a critical flaw. We have a
Speaker 1: circuit that can add two thirty two bit numbers. The
Speaker 1: inputs are active, the voltage campcades through, and the sum
Speaker 1: appears on the output wires right. But the second you
Speaker 1: drop the voltage on those input pins, the sum vanishes.
Speaker 1: It does the circuit has total amnesia because combinatorial circuits
Speaker 1: only reflect their current inputs. So how can a computer
Speaker 1: possibly function if it can't remember the result of its
Speaker 1: own math?
Speaker 2: Ah? Well, memory requires there's a different kind of circuit
Speaker 2: entirely called a sequential circuit. Okay, and creating memory out
Speaker 2: of logic gates relies on a really fascinating physical quirk
Speaker 2: of the hardware called propagation delay.
Speaker 1: Wait, let me sell you there, Because if you wire
Speaker 1: and not gates output directly back into its own input,
Speaker 1: shouldn't that create a logical paradox that just fries the circuit?
Speaker 2: It seems like it would, right, yeah, Because.
Speaker 1: If the input is one, the output becomes zero, which
Speaker 1: feeds back and makes the input zero, which makes the
Speaker 1: output one. It should instantly short itself.
Speaker 2: Out right in a world of perfect instantaneous logic, it
Speaker 2: would absolutely be a paradox. But physical hardware is bound
Speaker 2: by the speed of electrons. When the input voltage changes
Speaker 2: on a gate, it takes a tiny fraction of the second,
Speaker 2: perhaps just a few peico seconds in modern chips, for
Speaker 2: the transistors to actually change state and the output voltage
Speaker 2: to settle.
Speaker 1: And that is propagation delay exactly.
Speaker 2: That is propagation delay.
Speaker 1: So, because it takes a microscopic moment for the water
Speaker 1: to travel through the newly open valve, the paradox doesn't
Speaker 1: destroy the circuit, yep, it causes it to oscillate. It
Speaker 1: physically flips back and forth between zero and one, generating a.
Speaker 2: Square wave yes, and we harness that physical delay to
Speaker 2: create a stable memory circuit called a latch. Okay, the
Speaker 2: most basic latch uses four nand gates arranged with a
Speaker 2: feedback loop. Two of the gates have their outputs wired
Speaker 2: directly back into each other's inputs, and it also features
Speaker 2: a data line and an enable line.
Speaker 1: Here's where it gets really interesting, because I find it
Speaker 1: helpful to visualize the latch as a VIP room at
Speaker 1: an exclusive club.
Speaker 2: Oh I like this.
Speaker 1: So the enable line acts as the bouncer at the door,
Speaker 1: and the data line is the VIP trying to get inside.
Speaker 1: When the bouncer opens the door, meaning when the enable
Speaker 1: line receives a high voltage, the data flows right through
Speaker 1: the output of the room perfectly matches whatever VIP is
Speaker 1: standing at the door exactly.
Speaker 2: It acts completely transparently as long as the enable line
Speaker 2: is held.
Speaker 1: High, right. But when the bouncer closes the door, when
Speaker 1: the enabled voltage drops back to zero, the data is
Speaker 1: trapped inside the VIP room.
Speaker 2: It's locked in.
Speaker 1: Yeah. Even if a totally different signal shows up on
Speaker 1: the data line outside, the output of the VIP room
Speaker 1: refuses to change. It is officially saved. The state.
Speaker 2: That's a great analogy because the feedback loop between those
Speaker 2: nangates locks them into a stable configuration.
Speaker 1: Wow.
Speaker 2: Once the enable line drops, they essentially hold each other
Speaker 2: in place infinitely, remembering that final voltage state until the
Speaker 2: enable line is opened again.
Speaker 1: That's just so clever.
Speaker 2: And if you wire sixty four of these one bit
Speaker 2: latches together in parallel, sharing a single enable line, you
Speaker 2: have just built a sixty four bit register, which is.
Speaker 1: The fast short term memory of a CPU.
Speaker 2: Exactly, You now have memory.
Speaker 1: Okay, So we have logic to process the data, adders
Speaker 1: to do the math, and registers to store the result.
Speaker 1: We basically have all the pieces for a computer. We do,
Speaker 1: But there's a glaring automation problem here. Oh yes, when
Speaker 1: you compile and run a program, a human being isn't
Speaker 1: sitting on the motherboard manually the enable line on these
Speaker 1: registers billions of times a second to move data from
Speaker 1: the adder into memory.
Speaker 2: No, they certainly aren't. And that's because a standard latch
Speaker 2: is level sensitive, meaning it stays open as long as
Speaker 2: the enable line is high. Okay. To automate the flow
Speaker 2: of data without human intervention, you need a circuit that
Speaker 2: reacts to a transition rather than a steady state. Got it,
Speaker 2: So we construct a more complex component called a flip flop.
Speaker 1: So how does a flip flop differ from a standard
Speaker 1: latch in practice?
Speaker 2: Well, a flip flop is edge triggered edge triggered.
Speaker 1: Right.
Speaker 2: It only captures the data at the exact microscopic moment
Speaker 2: the enable signal transitions from low to high.
Speaker 1: Oh I see.
Speaker 2: It ignores the data line completely when the enabled signal
Speaker 2: is resting at zero, and it ignores it when it
Speaker 2: is resting at one. It only opens and shuts its
Speaker 2: door on the upward strike of the voltage spike.
Speaker 1: Like a push button toggle rather than a sustained lever. Precisely. Okay,
Speaker 1: So by striking a series of flip flops together so
Speaker 1: the output of one feeds the input of the next,
Speaker 1: you create a binary count. Yes, every time a voltage
Speaker 1: pulse hits the first flip flop, the counter increments its
Speaker 1: binary value, so it can automatically step through a sequence
Speaker 1: of instructions.
Speaker 2: But this raises an important question regarding synchronization.
Speaker 1: Okay, that's that.
Speaker 2: Well, you have millions of logic gates, thousands of adders,
Speaker 2: and hundreds of registers and they are all physically scattered
Speaker 2: across a silicon die, so they all have slightly different
Speaker 2: propagation delays depending on how far the electrons literally have
Speaker 2: to travel. Oh man, yeah, So how do you guarantee
Speaker 2: the data has fully cascaded through the adder and settled
Speaker 2: on the correct sum before the register's flip flop is
Speaker 2: triggered to save it?
Speaker 1: Because if the flip flop fires too early, it saves
Speaker 1: the garbage data that is still mid calculation exactly.
Speaker 2: The entire system would just descend into chaos.
Speaker 1: So what's the solution.
Speaker 2: The solution is the ultimate coordinator, the clock.
Speaker 1: The clock. We hear about clock speed constantly when buying
Speaker 1: a computer, right, like three gigaherds, four gigarherds. Right, But
Speaker 1: it isn't keeping time of day.
Speaker 2: No, not at all. A computer's clock is an oscillating
Speaker 2: circuit acting as a digital heartbeat.
Speaker 1: Heartbeat.
Speaker 2: Yes, it sends out a continuous, perfectly regular pulse of
Speaker 2: alternating high and low voltage across the entire chip. Okay,
Speaker 2: every flipplop, every sequence in the processor is wired to
Speaker 2: listen to that single clock signal. They are strictly designed
Speaker 2: to only change state or latch data on the rising
Speaker 2: edge of that specific clock pulse.
Speaker 1: Wow. So it forces order onto the physical chaos of
Speaker 1: the electrons exactly. So, if a processor has a clock
Speaker 1: speat of four gigahertz, that heartbeat is pulsing four billion
Speaker 1: times a second, which means the physical electricity must flow
Speaker 1: through all the logic gates, compute the math, travel down
Speaker 1: the wire, and arrive at the memory register in less
Speaker 1: than zero point twenty five nanoseconds before the next clock
Speaker 1: pulse hits.
Speaker 2: It guarantees that all the combinatorial circuits have had enough
Speaker 2: time to finish their physical work before the sequential circuits
Speaker 2: lock in the results and the processor moves to the
Speaker 2: next instruction.
Speaker 1: That is stagger it is.
Speaker 2: It allows the machine to run totally on autopilot.
Speaker 1: So what does this all mean for you listening to
Speaker 1: this deep dive? We started by talking about water pressure
Speaker 1: and pipes, and we ended up with a four gigahertz
Speaker 1: digital heartbeat synchronizing millions of sequential operations. It's quite a journey,
Speaker 1: it is. But understanding this physical hardware reality makes you
Speaker 1: a tangibly better programmer.
Speaker 2: Oh absolutely.
Speaker 1: It ceases to be abstract magic when you realize every
Speaker 1: line of code you write must eventually route physical electricity
Speaker 1: through logic gates and wait for propagation delays. It changes
Speaker 1: how you architect systems.
Speaker 2: It definitely encourages tighter, more efficient code, right.
Speaker 1: And it provides vital insight when you are debugging complex
Speaker 1: performance issues.
Speaker 2: Because the efficiency of your code directly translates to the
Speaker 2: physical workload of the machine exactly. But you know it
Speaker 2: also leads us right back to the physical limits we
Speaker 2: discussed at the start of.
Speaker 1: The show, the quantum tunneling right.
Speaker 2: Because the text touches on Moore's law and heat dissipation.
Speaker 2: The entire strategy for making a computer compute faster is
Speaker 2: to increase the clock speed.
Speaker 1: You want the heartbeat to pulse faster, yes.
Speaker 2: But to achieve that without the system failing, you must
Speaker 2: reduce the propagation delay of the circuits. You have to
Speaker 2: make the transistor smaller and pack them closer together so
Speaker 2: the electrons have less physical distance to travel, which we've done.
Speaker 1: We have successfully shrunk these components down to the atomic scale.
Speaker 2: We have, but at that scale the walls of the
Speaker 2: pipes are so incredibly thin that electrons can bypass the
Speaker 2: closed gates through quantum tunneling.
Speaker 1: The microscopic faucets are leaking.
Speaker 2: Exactly and it generates massive heat and flips bits unpredictably,
Speaker 2: completely destroying the reliability of the logic.
Speaker 1: We are colliding with the ultimate physical boundaries of Boolean
Speaker 1: logic using silicon.
Speaker 2: We really are, and it forces us to ask a
Speaker 2: tough question. Once we can no longer shrink the physical switch,
Speaker 2: how do we continue to scale computation.
Speaker 1: That is something to think about next time you hit
Speaker 1: compile