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So hi there, everyone.

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My name is Chandler Carruth.

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I work for Google

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I work on our C++ language platform

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I work on our C++ compilers

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specifically the Clang and LLVM teams at Google

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And I'm here to talk to you a little about performance.

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and efficiency, and making code fast,

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and all the different things that go into that.

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But before I do too much

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I want to give actually give you guys a little bit of

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one might say are expectations.

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Because I have been reading the twitter feed

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from all these folks, that talk about

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all these crazy good questions

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I just want you guys to essentially know

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this is my view

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of what Performance 101 should be.

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Okay? This is going to be kind of an intro talk.

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You guys are hard core, really deep performance nuts.

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You may be a little bit bored, and please be kind,

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because I'm going to gloss over some things

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you could heckle me thoroughly if you really want to

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We're going to talk about efficiency, performance,

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algorithms and data structures.

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And the first thing we are going to do is we're not going to talk about them.

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We're going to talk about why anyone cares about them.

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How many folks here think it's really important

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to have high performance in C++?

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Raise your hand if think that it's super important.

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Everyone thinks it's important!

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And the folks here who have a really clear idea why performance is important.

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Now, all the people who didn't raise their hands the second time,

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Please reconsider raising your hand the first time.

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We actually need to understand why performance is important in C++,

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before we actually decide it's important, we're going to care a lot about it.

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I'm going to tell you why I care about performance in C++.

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Most of it comes down to a quote from Nicolas Werth.

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Which I will try to pronounce correctly but fail miserably.

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I actually really like a lot of our stuff,

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I think he encapsulates a lot of my thoughts,

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what's core to my philosophy here.

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The software is getting slower more rapidly than

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hardware becomes faster.

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This is particularly in contrast to

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the kind of normal Moore's Law approach:

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Hardware's getting faster, all the time

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it's okay, we don't need to make software faster,

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because the hardware will catch up.

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And it turns out that's not really true.

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We're really good at writing slow software.

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Even in C++, we're really good at writing slow software.

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It's hard to write fast software,

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and it takes a lot of effort.

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And so it's important to think about

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why that might matter no matter how fast

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the processors get.

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And to give you an idea of just how much

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I think Nicholas Werth is on the same page

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I just have to mention he actually wrote a book

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entitled Algorithms + Data Structures = Programs.

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I did not realize this as I was picking

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the title of the topic.

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Anyways, we're going to come back

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to the title of this book.

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Because he predicted some whole elements

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of this talk in this book.

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So how many folks here have read this book?

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Anyone? All right! A long time ago.

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It's a good book. It's a good book.

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Okay, so I actually think the idea that

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software is getting slower too quickly, right?

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is really getting slower at an astonishing

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rate is even more important than before.

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And for pretty specific reasons.

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There was a very seminal event that

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happened in the technology world some time ago

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that changed, in my opinion and a lot of

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other peoples' opinion, how we look at

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computing devices, the performance of

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computing devices, the challenges we face

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running software for computing devices.

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And this event was the iPhone. Okay?

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And when Steve Jobs introduced the iPhone,

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he was not doing anything particular to C++

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but he was changing how we

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think about computing.

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Mobile was now a first class compute citizen.

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It took the world a little while to even

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realize that that was what had happened that day.

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But that's what happened.

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We now have to care about mobile.

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We have to care about things that are small.

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Right? things that are hard and challenging

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to fit big bulky systems into.

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And we essentially get into this annoying

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situation of, we have small, we have fast

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machines. We have to choose one.

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We don't get to choose though.

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We're going to choose small almost every time.

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But it gets worse.

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Because the other problem that the iPhone

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introduced that people weren't

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really focused on at the time

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was the problem of a battery.

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What do we do about the battery in your phone?

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You phone's battery, I mean my phone's

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battery is about dead. Right?

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How many folks here have charged their

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phone today? (Laughter from audience) Okay?

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That's a problem. That's not a feature.

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That's a bug. (Laughter from audience) Okay?

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Yes, How many folks are charging their phone now?

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(Laughter from audience) Okay so we kind of

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entered this new problem domain, suddenly

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power became relevant.

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There's some kind of shady research I want

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to push back against.

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There's some research into power efficient

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instructions. If you ever read about power

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efficient instructions or optimizing

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power usage, you should become very suspicious.

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And you should probably run the other direction.

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Because this is mostly total junk science. Okay?

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Here's the number one leading theory

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about how to save this, how to save

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battery life. Finish running the program.

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(Audience laughter) Seriously, race to sleep.

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That's the actual technical term, race to sleep.

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The faster your software runs, the less

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power it consumes. Now people get really

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upset about this. No, no if I run

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software really fast, then it heats up my

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processor, all that excess heat, that's the

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wasted power. But it's not, okay? Here's

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the thing, we've never really figured out

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how to run processors and do work

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on processors in a

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power efficient way. Do you know what we

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have figured out how to do with processors

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that has made our battery lives improve

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over time? We figured out how to turn them off.

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This is literally how your phone, your

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laptop, like if you have your computer

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on your desk. Every single

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microprocessor, general purpose

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microprocessors you can get today.

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The way it conserves power is by

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turning itself off as rapidly and as

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frequently as possible for as long a

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period time as possible. The more

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your processor turns on, the less this

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little green goes yellow and then red.

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Bad stuff right? So we actually want to

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make code faster in order to save battery

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life. Universally, this is true.

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There are some extreme exceptions to it

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There'e some really weird stuff around

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out on the fringe. But 99.999999% of the time

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You want to run code faster to save

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battery. But batteries aren't the only

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story when it comes to saving power.

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This is one of Google's data centers.

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You'll note that this is a very large building

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and the only thing it is doing is taking

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electricity and turning it into heat.

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That is it's job. And it's really good

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at it's job. And unfortunately,

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electricity costs a lot of money.

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And in fact, it's a finite resource.

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There's a certain point at which the cost

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goes away, you simply cannot have any

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more electricity at a particular point

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in time. And so power becomes very, very

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important in a data center as well.

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And I find it interesting that it's on the

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two extremes of computing platforms that

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we find convergence. Right? When you drop

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to a phone, or you go up to a data center

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all of a sudden power dominates. Right?

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We'll talk about compute per watt.

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This is another picture of the data center

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by the way. I just want to clarify what

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this is. This is one of my favorite pictures

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Those are enormous vents blowing out stem vapor.

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I don't know much about this but

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apparently when you can see the water vapor

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the data center is operating at peak

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efficiency because it means it's not too hot,

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its not too cool, its actually efficiently

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cooling the ?. Anyway this is trivia.

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So the compute per watt tends to

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dominate in the data canter and this is

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actually kind of the same thing we're trying

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to pull off on a phone or anything else.

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We want to maximize how much compute

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we can get out of the watts we're going

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to burn when the chip is turned on.

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Makes sense? Alright? Now I say raw speed

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isn't everything because when we talk

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about performance is really important

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you'll get some mixed messages from people.

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How many folks have heard this adage:

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After all, Java is faster than C++

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how many folks have heard it?

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Oh, you can be honest, I've heard it!

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All right, I had James Gosling sit across

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from the table and tell me

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I was a complete moron because I didn't

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believe Java that was faster than C++.

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And at the time he was right.

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And I learned better.

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So it turns out that Java is faster than C++

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in certain areas and scenarios.

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For example if you have a specific application

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and your specific application is going to

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run for a long period of time

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and you're concerned about the ?

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of the application and you have a

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very well tuned virtual machine

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for your Java, and you've tuned

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the garbage collector to precisely match

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the desired kind of garbage collection

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interruption frequency for your application

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If you get all of that, Java will

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very often