YouSaid · the spoken record

David Patterson

lines on the record: 127
first: 2020-06-27
most recent: 2020-06-27
sittings or episodes: 1
sources: podcast

Every line below is reproduced as it was said and linked to the record it came from. Nothing here is summarised or generated. Directory · Search · Corrections

“What Hennessy and I talked about in the title of our Turing Warrant speech is A New Golden Age. We see this as a very exciting decade, much like when we were assistant professors and the wrist stuff was going on. That was a very exciting time. It was where we were changing what was going on. We see this happening again. Tremendous opportunities of people because we're fundamentally changing how software is built and how we're running it.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“This looks like it's a very general purpose thing. So the timing is fortuitous that if we can perhaps, if we can keep building hardware that will accelerate machine learning, the neural networks, the timing will be right that that neural network revolution will transform software, the so-called software 2.0, and the software of the future will be very different from the software of the past. And just as our microprocessors, even though we're still going to have that same basic risk instructions to run a big pieces of the software stack like user interfaces and stuff like that, we can accelerate the small piece that's computationally pensive. It's not lots of lines of code. It takes a lot of cycles to run that code, that that's going to be the accelerator piece. So that's what makes this from a computer designer's perspective a really interesting decade.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“And remarkably, this gets used for all kinds of things very successfully. The image recognition, the language translation, the game playing, and it gets into pieces of the software stack like databases and stuff like that. We're not quite sure how journal purpose is, but that's going on independent of this hardware stuff. What's happening on the hardware side is Moore's law is slowing down right when we need a lot more cycles. It's failing us. It's failing us right when we need it because there's going to be a greater increase in computing and then this idea that we're going to do so-called domain specific, here's a domain that your greatest fear is you'll make this one thing work and that'll help 5% of the people in the world.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“So the thing that's interesting to point out these are not tied together. The enthusiasm about machine learning about creating programs driven from data that we should figure out the answers from data rather than kind of top down, which is classically the way most programming is done and the way artificial intelligence used to be done. That's a movement that's going on at the same time. Coincidentally And the first word in machine learning is machines, right? So that's going to increase the demand for computing because instead of programmers being smart writing those things down, we're going to instead use computers to examine a lot of data to kind of create the programs. That's the idea.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Turns out machine learning gets used for all kinds of things. So serendipitously we found something to accelerate that's widely applicable. And we don't even, we're in the middle of this revolution of machine learning. We're not sure what the limits of machine learning are. So this has been kind of a godsend. If you're going to be able to deliver on improved performance as long as people are moving their programs to be embracing more machine learning, we know how to give them more performance even as Moore's law is slowing down.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Is that we could figure out artificial intelligence by just writing the rules top down, or that was wrong. You had to look at data and infer what the rules are, the machine learning, and what's happened in the last decade or eight years is machine learning has won. And it turns out that machine learning, the hardware you build for machine learning is pretty much multiply. The matrix multiply is a key feature for the way machine learning is done. So that's a godsend for computer designers. We know how to make matrix multiply run really fast. So general purpose micro processors are slowing down. We're adding accelerators for machine learning that fundamentally are doing matrix multiplies much more efficiently than general purpose computers have done. So we have to come up with a new way to accelerate things. The danger of only accelerating one application is how important is that application.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“So since Morris Law is slowing down, we don't think general purpose computers are going to get a lot faster. So the Intel process of the world are not going to, haven't been getting a lot faster. They've been barely improved me like a few percent a year. It used to be doubling every 18 months, and now it's doubling every 20 years. So it's shocking. So to be able to deliver on what Morris Law used to do, we think what's going to happen what is happening right now is people adding accelerators to their microprocessors that only work well for some domains. And by sheer coincidence, at the same time that this is happening has been this revolution in artificial intelligence called machine learning. So with, as I'm sure your other guests have said, you know, AI had these two competing schools of thought.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“With the slowing down of Moore's law, that's no longer true, right? Now that desk side computers, but the laptops, I only get a new laptop when it breaks, right? I'll damn the disk broke or the display broke. I got to buy a new computer. But before you would throw them away because it just, they were just so sluggish compared to the latest computers. So that's, you know, that's a huge change of what's gone on. So, but since this lasted for decades, kind of programmers and maybe all of society is used to computers getting faster regularly. We now believe those of us who are in computer design, it's called computer architecture, that the path forward is to add accelerators that only work well for certain applications.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Doubling performance every 18 months. And if you weren't around then, what would happen is you had your computer and your friend's computer, which was like a year or year and a half newer. And it was much faster than your computer. And he or she could get their work done much faster than your computer because you were. So people took their computers, perfectly good computers and threw them away to buy a newer computer because the computer one or two years later was so much faster. So that's what the world was like in the 80s and 90s.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, so kind of if we go back to the history, when Moore's laws in full effect and you're getting twice as many transistors every couple of years, you know, kind of the challenge for computer designers is how can we take advantage of that? How can we turn those transistors into better computers, faster typically? And so there was an era. I guess in the 80s and 90s, where computers were.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I mean, that's kind of what I said. I was interested to see. I had another more senior faculty colleague and he had written something in Scientific American. And his 25 years in the future and his turned out about when I was a young professor, and he said, yep, I checked it. I was interested to see how that was going to turn out. For me, it's pretty held out pretty well. But yeah, so there's probably something fundamental about those instructions that we're capable of creating intelligence from pretty primitive operations and just doing them really fast.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Surprising to me that it's complicated as it is to build these things, a microprocessors where the line widths are narrower than the wavelength of light is this amazing technology at some fundamental level. The commands that software executes are really pretty straightforward and haven't changed that much in decades, which a surprising outcome.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“I think the surprising thing is still if we brought back the pioneers from the 1950s and showed them the instruction set architectures, they'd understand it. They'd say, wow, that doesn't look that different. I'm surprised. And maybe something, you know, to talk about philosophical things. I mean, there may be something powerful about those 40 or 50 instructions that all you need is these commands like these instructions that we talked about. And that is sufficient to build artificial intelligence. And so it's a remarkable.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Top of that. So, this idea of a core set of instructions that the software stack runs on and then optional features that if you turn them on, the compilers were used, but you don't have to, I think is a powerful idea. What's happened in the past for the proprietary instruction sets is when they add new instructions, it becomes required piece. And so that all microprocessors in the future have to use those instructions. So it's kind of like for a lot of people as they get older, they gain weight, right? That weight in age are correlated. And so you can see these instruction sets getting bigger and bigger as they get older. So RISC five lets you be as slim as you as a teenager and you only have to add these extra features if you're really going to use them rather than you have no choice and you have to keep growing with the instruction set.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“The software staff RISC 5 can run just on those 40 instructions. And then they provide optional features that could accelerate the performance instructions that if you needed them could be very helpful, but you don't need to have them. And that's a new, really a new idea. So RISC-V has right now maybe five optional subsets that you can pull in, but the software runs without them. If you just want to build the just the core 40 instructions, that's fine. You can do that. So this is fantastic educationally is you can explain computers. You only have to explain 40 instructions and not thousands of them. Also, if you invent some wild and crazy new technology like biological computing, you'd like a nice simple instruction set and you can risk five if you implement those core instructions. You can run really interesting programs on top.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“I was always attracted to the idea of small is beautiful is that the temptation in engineering, it's kind of easy to make things more complicated. It's harder to come up with more difficult, surprisingly, to come up with a simple, elegant solution. And I think there's a bunch of small features of risk in general that where you can see this examples of keeping it simpler makes it more elegant. Specifically in RISC 5, which I was kind of the mentor in the program, but was really driven by Christosanovich and two graduate students, Andrew Waterman Jensipli, is they hit upon this idea of having a subset of instructions, a nice simple subset instructions like 40-ish instructions that all software”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“So the instructions sets are the same, the specifications are the same, but they're hardware design is much more efficient than And that's given Apple an advantage in the marketplace, and that the iPhones tend to be the faster than most everybody else's phones that are there.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“How's that happen? Yeah. So, what ARM pioneered was a new business model. They said, well, here's our proprietary instruction set. We'll give you two ways to do it. We'll give you one of these implementations written in things like C called Verilog, and you can just use ours. You have to pay money for that. We'll give you, will license you do that? Or you could design your own. And so we're talking about numbers like tens of millions of dollars to have the right to design your own since the instruction set belongs to them. So Apple got one of those the right to build their own. Most of the other people who build like Android phones just get one of the designs from ARM to do it themselves. So Apple developed a really good microprocessor design team. They acquired a very good team that was building other microprocessors and brought them into the company to build their design.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Limiting resource isn't the number of transistors you can fit in the chip. It's how much power can you dissipate for your application. So by having a reduced instruction set, that's possible to have simpler hardware which is more energy efficient. An energy efficiency is incredibly important in the cloud when you have tens of thousands of computers in a data center. You want to have the most energy efficient ones there as well. And of course for embedded things running off of batteries, you want those to be energy efficient and the cell phones too. So I think it's believed that there's an energy disadvantage of using these more complex instruction set architectures.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, part of it is. For these old CIS construction sets, like in the x86. It was more expensive to these for, you know, they're older, so they have disadvantages in them because they were designed 40 years ago. But also they have to translate in hardware from SIS constructions to risk constructions on the fly. And that costs both silicon area. The chips are bigger to be able to do that. And it uses more power. So ARM, which has followed this risk philosophy, is seen to be much more energy efficient. And in today's computer world, both in the cloud and the cell phone and Internet of Things, it isn't.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“That you'd think be the more difficult one. But if RISV really catches on, you could in a period of a decade, you can imagine that's changing over too.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“The first arm goes back, I don't know, 86 or so. So Berkeley instead did their work in the early 80s. The arm guys needed instruction set and they read our papers and it heavily influenced them. So, getting back my story, what about Internet of Things? Well, software is not shipped in Internet of Things, it's the embedded device people control that software stack. So the opportunities for RISC-V, everybody thinks, is in the Internet of Things embedded things because there's no dominant player like there is in the cloud or the smartphones. And it doesn't have a lot of licenses associated with, and you can enhance the instruction set if you want. And people have looked at instruction sets and think it's a very good instruction set. So it appears to be very popular there. It's possible that in the cloud people, those companies control their software stacks. So it's possible that they would decide to use RISC-V if we're talking about 10 and 20 years in the future. One of the be harder would be the cell phones.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, it's a risk based instruction. It's a proprietary one. ARM stands for. Advanced risk machine, ARM is the name where the company is. So it's a proprietary risk architecture. And it's been around for a while, and it's surely the most popular instruction set in the world right now. Every year, billions of chips are using the ARM design in this post-PC era.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“So, what's different about those three categories is for the cloud, the software that runs in the cloud is determined by these companies, Alibaba, Amazon, Google, Microsoft. So they control that software stack. For the cell phones, for Android and Apple, the software they supply, but both of them have marketplaces where anybody in the world can build software. And that software is translated or compiled down and shipped in the vocabulary of ARM. So that's what's referred to as binary compatible because the actual, it's the instructions are turned into numbers, binary numbers, and shipped around the world.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Those sales are dwindling. You know, there's maybe 200 million PCs a year, and there's one and a half billion phones a year. There's numbers like that. So for the phones, that's dominated by ARM. And a reason that I talked about the software stacks and that the third category is Internet of Things, which is basically embedded devices, things in your cars and your microwaves everywhere.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, part of it, a big piece of it is the software stack. And right now, looking forward, there seem to be three important markets. There's the cloud, and the cloud is simply companies like Alibaba and Amazon and Google, Microsoft having these giant data centers with tens of thousands of servers in maybe 100 of these data centers all over the world. And that's what the cloud is. So the computer that dominates the cloud is the x86 instruction set. So the instructions are the instruction sets used in the cloud are the x86, almost 100% of that today is x86. The other big thing are cell phones and laptops. Those are the big things today. I mean, the PC is also dominated by the x86 instruction set, but...”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“There's a bunch. I think the thing you point out, there's these very popular proprietary instruction sets, the x86. And so how do”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“January of 2015, and the one that was just last December, and it had 50 people at it. And this one last December had, I don't know, 1,700 people were at it, and the companies excited all over the world. So predicting into the future, if we were doing 25 years, I would predict that risk five will be possibly the most popular instruction set architecture out there because it's a pretty good instruction set architecture and it's open and free and there's no reason lots of people shouldn't use it and there's benefits just like Linux is so popular today compared to 20 years ago and the fact that you can get access to it for free you can modify it you can improve it for all those same arguments and so people collaborate to make it a better system for all everybody to use and that works in software and I expect”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“What we do with our instructions. And then when we talk to him, we found out there was this thirst for this idea of an open instruction set architecture. And they had been looking for one. They stumbled upon ours at Berkeley, thought it was, boy, this looks great. We should use this one. And so once we realized there is this need for an open instruction-set architecture, we thought, that's a great idea. And then we started supporting it and tried to make it happen. So this was kind of, we accidentally stumbled into this and to this need and our timing was good. And so it's really taking off. Universities are good at starting things, but they're not good at sustaining things. So, like Linux has a Linux foundation, there's a RISC-V foundation that we started. There's an annual conferences, and the first one was done, I think.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“People are, people are. So, what happened to us, the story was this was developed here for our use to do our research. And we made it, we licensed under the Berkeley Software Distribution License, like a lot of things get licensed here. So other academics use it. They wouldn't be afraid to use it. And then about 2014, we started getting complaints that we were using it in our research and in our courses. And we got complaints from people in industry is why did you change your instruction set between the fall and the spring? Semester, and well, we get complaints from your time. Why the hell do you care?”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, and so just to make it clear, because this is confusing, the specification of RISC-V is something that's like in a textbook. There's books about it. So that's defining an interface. There's also the way you build hardware is you write it in languages. They're kind of like C, but they're specialized for hardware that gets translated into hardware. And so these implementations of this specification are what are the open source. So they're written in something that's called Verilog or VHDL, but it's put up on the web just like you can see the C++ code for Linux on the web. So that's the open instruction set enables open source implementations of RISC-V.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“So there's five is another instruction set of vocabulary. It's learn from the mistakes of the past, but it still has, if you look at the, there's a core set of instructions that's very similar to the simplest architectures from the 1980s. And the big difference about RISC-V is it's open. So I talked earlier about proprietary versus open. Software. So, this is an instruction set. So it's a vocabulary. It's not hardware. But by having an open instruction set, we can have open source implementations, open source processors that people can use.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“So, in fact, going way back in the stack, back to, you know, we did four risk projects at Berkeley in the 1980s. They did a couple at Stanford in the 1980s. In 2010, we decided we wanted to do a new instruction set learning from the mistakes of those risk architectures of the 1980s. And that was done here at Berkeley almost exactly 10 years ago. The people who did it, I participated, but Krista Sanovich and others drove it. They called it RISC-V to honor those, the four risk projects of the 1980s.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Can do something smarter than human beings can do. But if you go down that very basic level, the instructions are the keys on the calculator plus the ability to make decisions of these conditional branch instructions.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“So that's memory in loads and stores. But the big thing, the difference between a computer and a calculator is that the computer can make decisions. And amazingly, decisions are as simple as, is this value less than zero? Or is this value bigger than that value? So there's, and those instructions, which are called conditional branch instructions, is what give computers all its power. If you were in the early days of computing before what's called the general purpose microprocessor, people would write these instructions kind of in hardware, but it couldn't make decisions. It would just do the same thing over and over again. With the power of having branch instructions, they can look at things and make decisions automatically. And it can make these decisions billions of times per second. And amazingly enough, we can get, thanks to advances machine learning, we can create programs that...”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, I told you there were five pieces of a computer. And if you remember in a calculator, there's a memory key. So you want to have intermediate calculation and bring it back later. So you'd hit the memory plus key, M plus maybe, and it would put that into memory. And then you'd hit an RM recurrent instruction, and it'd bring it back into display. So you don't have to type it. You don't have to write it down and bring it back again. So that's exactly what memory is. You can put things into it as temporary storage and bring it back when you need it later.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“So the things that are in a calculator are in a computer. So any of the buttons. So, there's a memory function key, and like I said, those turns into putting something in memory is called a store, bring something back, it's going to load.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, Marr's Law was going to go on. We thought for 25 more years, who knows? But kind of the surprising thing, in fact, Hennessy and I won the ACM AM Touring Award for both the risk construction set contributions and for that textbook I mentioned. But we're surprised that here we are 35. 40 years later after we did our work. And the conventionalism of the best way to do instruction sets is still those risk instruction sets that look very similar to what we looked like we did in the 1980s. So those surprisingly, there hasn't been some radical new idea, even though we have a million times as many transistors as we had back then. But”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Okay, 1995, I was asked to predict the future of what microprocessor. So as I'd seen these predictions, and usually people predict something outrageous just to be entertaining, right? And so my prediction for 2020 was, you know, things are going to be pretty much, they're going to look very familiar to what they are. And they are. And if you were to read the article, you know, the things I said are pretty much true. The instructions that have been around forever are kind of the same.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“And so we went from it was outrageously controversial in 1982 that maybe probably by 1984 or so people said, oh, yeah, technically they've got a good argument.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“But what turned out that the way they would do these complex instructions is they would actually build what we would call an interpreter in a simpler, a very simple hardware interpreter. But it turned out that for the sys constructions, if you had to use one of those interpreters, it would be like 10 clock cycles per instruction where the risk instructions could be two. So there'd be this factor of five advantage in clock cycles per instruction. We have to execute, say, 25 or 50 percent more instructions. So that's where the win would come. And then you could make an argument whether the clock cycle times are the same or not. But pointing out that we could divide the benchmark results time per program into three factors. And the biggest difference between risk consists was the clock cycles per, you execute a few more instructions, but the clock cycles per instruction is much less. And that was what this debate. Once we made that argument, then people said, oh, okay, I get it.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Parallelism, which has to do with, say, how many structures could execute in parallel and things like that, you could think of that as affecting the clock cycles per instruction because it's the average clock cycles per instruction. So when you're running a program, if it took 100 billion instructions and on average it took two clock cycles per instruction and they were four nanoseconds, you could multiply that out and see how long it took to run. And there's all kinds of tricks to try and reduce the number of clock cycles per instruction.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“They would concentrate on, but risk needs to take more instructions. And we'd argue what maybe the clock cycle is faster, but what the real big difference was was the number of clock cycles per instruction”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“The next question is how long did each instruction take to run on average? So you multiply the number of instructions times how long it took to run. And that gets you time. Okay, so that's, but now let's look at this metric of how long did it take the instruction to run. Well, it turns out the way we could build computers today is they all have a clock. And you've seen this if you buy a microprocessor. It'll say 3.1 gigahertz or 2.5 gigahertz and more gigahertz is good. Well, what that is, is the speed of the clock. So 2.5 gigahertz turns out to be four billionths of instruction or four nanoseconds. So that's the clock cycle time. But there's another factor, which is what's the average number of clock cycles that takes per instruction? So it's number of instructions, average number of clock cycles in the clock cycle time. So in these risk cyst debates, we would”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“If I can do a formula orally so fundamentally the way you measure performance is how long does it take a program to run program if you have 10 programs and typically these benchmarks were sweet because you'd want to have 10 programs so they could represent lots of different applications so for these 10 programs how long did it take to run well now when you're trying to explain why it took so long you could factor how long it takes a program to run into three factors one of the first one is how many instructions did it take to execute so that's the that's the that's what we've been talking about you know the instructions of algebra how many did it take all right”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, let's talk about the metrics. During these debates, we actually had kind of a hard time explaining, convincing people the ideas. And partly we didn't have a formula to explain it. And a few years into it, we hit upon the formula that helped explain what was going on. And I think if we can do this, see how it works orally.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“When you say these programs run this fast, well, that's kind of interesting, but how do you know it's better? Well, you compare it to other computers at the same time. So the best way we know how to turn it into kind of more science and experimental and quantitative is to compare yourself to other computers of the same era that have the same access, the same kind of technology, uncommonly agreed benchmark programs.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“And it's the thing, it had a pretty big impact in the field because we went from textbooks that kind of listed, so here's what this computer does, and here's the pros and cons, and here's what this computer does in pros and cons to something where there were formulas and equations where you could measure things. So specifically for instruction sets, what we do in some other fields do is we agree upon a set of programs, which we call benchmarks, and a suite of programs. And then you develop both the hardware and the compiler, and you get numbers on how well your computer does given its instruction set and how well you implemented it in your microprocessor. And how good your compilers are. And computer architecture, using professors' terms, we grade on a curve rather than grade on absolute scale.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“A big change, kind of what happened, I think, from Hennessy's in my perspective in the 1980s, what happened was going from kind of really Taste and hunches to quantifiable. And in fact, he and I wrote a textbook at the end of the 1980s called Computer Architecture, a quantitative approach.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source
“It's not that hard to build an instruction set, but to build one that catches on and people use, you know, you have to be fortunate to be the right place in the right time or have a design that people really like.”
2020-06-27 · Lex Fridman Podcast · #104 – David Patterson: Computer Architecture and Data Storage · IDENTIFIED FROM THE TRANSCRIPT · source