Speaker 1: Welcome to tech Stuff, a production from iHeartRadio. Hey there,
Speaker 1: and welcome to tech Stuff. I'm your host Jonathan Strickland.
Speaker 1: I'm an executive producer with iHeartRadio. And how the tech
Speaker 1: are you? You know? Over the last few years, there's
Speaker 1: been a lot of conversation around microchips in general, and
Speaker 1: CPUs and GPUs in particular. The pandemic led to bottlenecks
Speaker 1: in the supply chain. Manufacturing facilities had to shut down
Speaker 1: multiple times, particularly in China, and the initial skyrocketing value
Speaker 1: of cryptocurrencies all had an effect on microchip supply. Meanwhile,
Speaker 1: multiple countries, including the United States, started looking into ways
Speaker 1: to shift away from depending so heavily on China for
Speaker 1: chip fabrication. And when we talk about chips like CPUs,
Speaker 1: we often will focus on two major factors. So first
Speaker 1: is the process used to actually fabricate discrete components on
Speaker 1: the chip. We typically reference this in terms of a
Speaker 1: nanometer process, and the fewer nanometers represents more advanced processes,
Speaker 1: so you're working backward in numbers. Secondly, is the chip's architecture,
Speaker 1: and that's really what we're going to focus on in
Speaker 1: this episode. But in order to do that, we also
Speaker 1: have to talk about the other stuff. So a quick
Speaker 1: word on the fabrication process part. You might hear that
Speaker 1: company used a seven nanometer process or a five or
Speaker 1: even a three nanometer process to make the chip. And
Speaker 1: you may know that a nanometer is one billionth of
Speaker 1: a meter. It's one scale up from the atomic scale.
Speaker 1: So a typical human hair measures between eighty thousand and
Speaker 1: one hundred thousand nanometers thick, as in, if you measured
Speaker 1: the diameter of the hair, that's the range you would
Speaker 1: be at. So when you're talking about seven or five
Speaker 1: or even three nanometers, that's super duper small, right, Well,
Speaker 1: it would be if the nanometer designation still referred to
Speaker 1: component size. Now, once upon a time the scale reference
Speaker 1: to a process actually did correspond with at least some
Speaker 1: component size on the chip itself, but that has not
Speaker 1: been the case for several generations. Now. Part of the
Speaker 1: reason for that comes down to the limitations of physics.
Speaker 1: As you shrink down to the bottom end of the
Speaker 1: nanoscale and into the atomic scale, you start to have
Speaker 1: to contend with quantum mechanics. Now, we don't encounter quantum
Speaker 1: mechanic effects on our normal scale like in our everyday lives.
Speaker 1: But at that tiny scale, things start to behave in
Speaker 1: a really wonky way, and relying on physical structures to
Speaker 1: rain in quantum silliness becomes a big challenge. I've done
Speaker 1: full episodes kind of about this. We're not going to
Speaker 1: dive too deeply into it, so instead, the scale really
Speaker 1: is more of a marketing strategy. When you hear it's
Speaker 1: a five nanometer process, it doesn't mean that anything on
Speaker 1: that chip actually measures five nanometers in size. It's a
Speaker 1: way of indicating this process is more advanced than the
Speaker 1: previous seven nanometer process. So it really means that when
Speaker 1: you get down to the process and the architecture, you
Speaker 1: start to converge on essentially the same meaning. So let's
Speaker 1: talk about that architecture. What does chip architecture actually mean. Well,
Speaker 1: we're going to stick with CPUs, also known as central
Speaker 1: processing units, and we can think of a CPU as
Speaker 1: having three major components. These are the registers, the arithmetic
Speaker 1: logic unit or ALU, and the control unit. So registers
Speaker 1: act kind of like memory, and that they hold information
Speaker 1: that the CPU needs in order to complete operations. Logic
Speaker 1: gates make up the quote unquote memory of registers, and
Speaker 1: a logic gate follows a specific rule. It creates an
Speaker 1: output based upon the input coming into the logic gate.
Speaker 1: I'll do a full episode just about logic gates in
Speaker 1: the future to kind of expand on that and explain
Speaker 1: how these logic gates work and how by combining logic
Speaker 1: gates you can create different outcomes. So registers operate faster
Speaker 1: than RAM, a random access memory, which I often at
Speaker 1: least will compare to short term memory in humans. RAM,
Speaker 1: in turn operates faster than a solid state drive or
Speaker 1: a hard drive, which I compare to long term memory
Speaker 1: with humans. So you've got registers, which are the fastest
Speaker 1: access of memory total, but it holds very little information.
Speaker 1: It's just tiny, tiny bits of information. Then you have RAM.
Speaker 1: Then you've got solid state drive or hard drive in registers.
Speaker 1: We actually we have five basic types, so let's list
Speaker 1: them off, shall we. The instruction register stores the address
Speaker 1: and random access memory of the instruction to be used
Speaker 1: in a given operation. So that instruction could be some
Speaker 1: basic arithmetic function for example like AD. Next, you've got
Speaker 1: the memory address register. This stores the address within RAM
Speaker 1: of the data that is to be processed. So this
Speaker 1: is the data that's going to be transformed by that
Speaker 1: instruction in some way. Your instruction register has the info
Speaker 1: on what operation to use. The memory address register has
Speaker 1: the info on which data is going to undergo that operation.
Speaker 1: Then you've got the memory data register. This stores the
Speaker 1: data that the CPU is actually processing at any given time.
Speaker 1: So while the other two registers are kind of like
Speaker 1: looking into the future like the next step, the memory
Speaker 1: data register is concerned with what's going on right now,
Speaker 1: gosh darn it. Then you've got the program counter. This
Speaker 1: stores the address and RAM of the next instruction coming up,
Speaker 1: so the next one down the line. Finally, you've got
Speaker 1: the accumulator that stores the results of the calculations that
Speaker 1: were just performed. So the registers are one part of
Speaker 1: CPU architecture. Now let's talk about the ALU or arithmetic
Speaker 1: logic unit. The ALU is the brains of the CPU.
Speaker 1: Within the ALU are logic circuits which actually carry out
Speaker 1: the operations on data. These operations span a wide range
Speaker 1: of arithmetic tasks like addition and subtraction, to things like
Speaker 1: incrementation and also comparison. So, for example, you might have
Speaker 1: a pair of operations that each produce a result and
Speaker 1: the ALU has to compare these results with one another
Speaker 1: to determine if they are the same or different. That's
Speaker 1: the kind of basic task the ALU handles, and it
Speaker 1: does this super fast. Finally, you have the control unit, which,
Speaker 1: as the name suggests, controls the process. The control unit
Speaker 1: receives instructions, decodes those to get to the meaning of
Speaker 1: the instructions, sends commands to the other components to carry
Speaker 1: out those instructions, et cetera. The control unit is kind
Speaker 1: of like a floor manager. It makes sure all the
Speaker 1: departments are responding appropriately given the program that's running at
Speaker 1: any given time. The control unit also has a clock,
Speaker 1: but that clock isn't meant to keep your computer's time
Speaker 1: accurate to local time. This clock oscillates a certain number
Speaker 1: of times per second, and we measure this in hurts,
Speaker 1: So one oscillation per second would be one hurts. Typically,
Speaker 1: with processors today, we're talking about the gigahertz range. A
Speaker 1: gigahertz would be a billion oscillations per second. So a
Speaker 1: three point two gigahertz CPU has a clock that in
Speaker 1: the control unit that oscillates three point two billion times
Speaker 1: every single So now the clock speed relates to how
Speaker 1: quickly the processor can actually complete these operations. Some operations
Speaker 1: require multiple oscillations, but that clock speed or frequency, if
Speaker 1: you prefer, gives you an idea of how fast or
Speaker 1: powerful your computer is. Now. Other factors also play into
Speaker 1: this too. It's not just clock speed, but that is
Speaker 1: one big component in it. If you're familiar with the
Speaker 1: term overclocking, then all of the stuff I'm talking to
Speaker 1: you about is old news to you, right. Overclocking is
Speaker 1: the practice of increasing that clock oscillation speed in the
Speaker 1: control unit beyond its default settings, which typically the manufacturer creates.
Speaker 1: Like they create default settings, they say this processor is
Speaker 1: rated at this particular clock speed, and going beyond that
Speaker 1: could potentially reduce the useful lifespan of the processor or
Speaker 1: cause it to overheat, et cetera. So elite gamers typically
Speaker 1: will use programs to boost the clock speed on CPUs
Speaker 1: to get past these limitations and to push it faster
Speaker 1: than what it was rated as in order to milk
Speaker 1: out higher performance in their gaming ricks. Doing this does
Speaker 1: come with some trade offs. I mean, it does mean
Speaker 1: that you might be burning through your CPU faster than
Speaker 1: you usually would. It also typically means that the computer's
Speaker 1: going to generate a lot more heat, so you need
Speaker 1: to have a good heat dispersal system in place to
Speaker 1: carry that heat away from the processor because, as we know,
Speaker 1: heat and electronics are not super friendly with one another.
Speaker 1: Connecting all these different components are wires called buses, So
Speaker 1: a bus might carry instructions, another bus might carry data.
Speaker 1: The capacity of buses also plays a part in how
Speaker 1: powerful a computer is. I'll have to do another episode
Speaker 1: to explain things like what is a thirty two bit
Speaker 1: machine versus a sixty four bit machine, or even with
Speaker 1: the old game consoles, an eight bit machine. We'll talk
Speaker 1: about bitwidth and that kind of stuff, but that kind
Speaker 1: of plays into things like buses. You can think of
Speaker 1: it sort of like roads. How wide is the road
Speaker 1: so how many vehicles can pass side by side at
Speaker 1: the same time. And one other thing that we will
Speaker 1: mention will be cores, and I'm going to get to
Speaker 1: that after we take this quick break. Okay, before the break,
Speaker 1: I teased that we're going to talk about cores. A
Speaker 1: CPU core is the smallest unit that can carry out
Speaker 1: all the jobs that a CPU does. So if you
Speaker 1: hear of a multicore CPU, that means each of those
Speaker 1: cores can do the job of a CPU, and they
Speaker 1: can have multiple cores. You'll hear things like dual core,
Speaker 1: which means there's two of them, or quad core, meaning
Speaker 1: there's four of them, and beyond, each core can carry
Speaker 1: out the duties of a CPU. So does that mean
Speaker 1: a dual core or quad core processor is automatically better
Speaker 1: than a single core processor. Not necessarily so. For some
Speaker 1: types of computational problems, you can actually divide up the
Speaker 1: problem into smaller tasks that could be completed simultaneously. So
Speaker 1: these are the types of problems that multicore processors are
Speaker 1: great at tackling because each core can tackle a different
Speaker 1: set of tasks and thus collectively they'll get to the
Speaker 1: answer faster. But if the problem cannot be broken down
Speaker 1: into smaller pieces, a very powerful single core processor might
Speaker 1: be better than a decently powerful multicore processor. And I
Speaker 1: use this analogy all the time. Longtime listeners are probably
Speaker 1: tired of it, and they've anticipated it, and yes, it's
Speaker 1: okay to skip ahead a little bit if you are
Speaker 1: one of those people. But I like to describe multicore
Speaker 1: processors versus a single core processor by talking about an
Speaker 1: advanced math class, And in this version of it, I'm
Speaker 1: going to say there are five students in this advanced
Speaker 1: math class. Now imagine four of those five students are
Speaker 1: all really good at math, right, they're gifted students. However,
Speaker 1: the fifth student is a genuine math genius. And the
Speaker 1: genius always completes any given problem faster than the other
Speaker 1: four students can. And one day the teacher presents a
Speaker 1: challenge to the class. It's a pop quiz that has
Speaker 1: four questions on the quiz. The genius has to try
Speaker 1: and complete all four problems, but the other four students
Speaker 1: can actually divide up the quiz and each student can
Speaker 1: tackle a single problem on there, so collectively they can
Speaker 1: solve the quiz together. So who is going to finish first? Well,
Speaker 1: if we assume that each problem is discreete and independent
Speaker 1: of the outcomes of the other problems, the four students
Speaker 1: are likely to finish their quiz collectively before the genius
Speaker 1: because each one's just doing one question, and the genius
Speaker 1: is still faster than all the individuals. But they have
Speaker 1: to do all four questions, whereas each smart student just
Speaker 1: has to do one. The multi core processor wins in
Speaker 1: that scenario, but Let's say you find out that problem
Speaker 1: two on the quiz actually depends upon the outcome of
Speaker 1: problem one, and you find out the problem three depends
Speaker 1: upon the outcome of problem two, and the problem four
Speaker 1: depends on the outcome of problem three. Well, now you
Speaker 1: can't just divide up the problems between the four students
Speaker 1: because the student working on problem two has to wait
Speaker 1: to find out what the answer to problem one is
Speaker 1: before they can get started. The genius in that case
Speaker 1: is going to win that race, right, because they're still
Speaker 1: faster than any individual is. So for certain types of
Speaker 1: computational problems and processes, multicore is the way to go,
Speaker 1: but not in every case, just in a lot of them.
Speaker 1: For a lot of computer users, it's more important to
Speaker 1: go multi corep because the typical uses that they rely
Speaker 1: upon with computers falls into that multi core set of problems.
Speaker 1: This includes gamers, So a multi core processor matched with
Speaker 1: a really good graphics processing unit that's more important than
Speaker 1: having just a single core super fast processor. But again,
Speaker 1: it all depends on how you can thread the computational problems.
Speaker 1: And that's the general description of what computer architecture means.
Speaker 1: The actual design and layout of these components is what
Speaker 1: sets one chip apart from another chip. Since it is
Speaker 1: increasingly challenging to shrink components down without getting into quantum
Speaker 1: effects or generating too much heat in a very small space,
Speaker 1: finding the best possible layout and orientation of components is critical.
Speaker 1: You know you're not going to be able to cram
Speaker 1: a whole lot more on, but you might be able
Speaker 1: to find an orientation that gets a little better performance
Speaker 1: out of the components you have now. Back in the day,
Speaker 1: Intel which which is one of two major companies behind
Speaker 1: the processors used in most computers these days, used a
Speaker 1: development approach and chip designed that the company referred to
Speaker 1: as the tick talk method. So you can think of
Speaker 1: the tick part of TikTok as taking the same chip
Speaker 1: layout design from the previous generation, but then shrinking everything
Speaker 1: down a little bit, which allows you to cram more
Speaker 1: components on the chip. So you're following the same architectural
Speaker 1: plan as the previous generation, but now all the components
Speaker 1: are slightly smaller so you can have more of them there.
Speaker 1: The talk sequence would involve creating a new architecture that
Speaker 1: better takes advantage of these smaller components, and then it
Speaker 1: would repeat tech talk Tick talk. So with tick you
Speaker 1: shrink stuff down, but you follow the same game plan
Speaker 1: as before. With talk, you create a new game plan,
Speaker 1: and then you do tick again. And so each generation
Speaker 1: of Intel fell into one of those two design principles,
Speaker 1: and in this way Intel would iterate its chip designs.
Speaker 1: Each generation would improve upon the last. At least that
Speaker 1: was the idea, either by adding more capability in the
Speaker 1: form of more components added to the chip, or finding
Speaker 1: a new way to arrange those components that improve performance.
Speaker 1: And by improved performance, I mean not just being faster
Speaker 1: or more capable, but also more power efficient or creating
Speaker 1: less heat, because these things do matter quite a bit.
Speaker 1: And that's our overview of chip architecture. I'll do more
Speaker 1: episodes about the basics of CPUs soon. Maybe i'll talk
Speaker 1: a bit about what makes an Intel chip different from say,
Speaker 1: an AMD chip. And you may know, if you've ever
Speaker 1: built a computer, the type of processor you want ends
Speaker 1: up mattering a big deal, because it will tell you
Speaker 1: what kind of motherboard you can use, for example, because
Speaker 1: a motherboard designed to work with an Intel chip is
Speaker 1: not going to work with an AMD chip. Thing. So
Speaker 1: we'll do another episode to talk a bit more about
Speaker 1: this in the future, and keep it nice and short
Speaker 1: and simple so that folks can listen, get a good understanding,
Speaker 1: and then know what to look for when they move
Speaker 1: forward if they ever decide to build their own computer.
Speaker 1: And I think we'll also, like I said, to an
Speaker 1: episode about things like logic gates to kind of understand
Speaker 1: at a very very very basic level, what is going
Speaker 1: on when a computer is processing information. That's it for
Speaker 1: this Tech Stuff Tidbits episode. I hope you are all well.
Speaker 1: Just a reminder next week, I am on vacation and
Speaker 1: I will be back the following week, so we will
Speaker 1: likely have some reruns playing next week, but I will
Speaker 1: be back and I'll talk to you again really soon.
Speaker 1: Tech Stuff is an iHeartRadio production. For more podcasts from iHeartRadio,
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