쉐도잉 연습: Mind-bending new programming language for GPUs just dropped... - 영상으로 영어 말하기 배우기

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Yesterday, the clouds opened up, and a weird new programming language came down to Earth, with a promise of parallelism for all thou who writeth code.

This is big if true, because parallel computing is a superpower.

It allows a programmer to take a problem that could be solved in a week, and instead solve it in seven days using seven different computers.

Unfortunately, running code in parallel is like conducting a symphony.

One wrong note, and the entire thing becomes a total disaster.

But luckily, Bend offers hope by making a bold promise.

Everything that can run in parallel, will run in parallel.

You don't need to know anything about CUDA, blocks, locks, mutexes, or regexes to write algorithms that take advantage of all 24 of your CPU cores,

or even all 16 ,000 of your GPU cores.

You just write some high -level

Python -looking code, and the rest is magic.

It is May 17th, 2024, and you're watching the Code Report.

When you write code in a language like

Python, your code runs on a single thread.

That means only one thing can happen at a time.

It's like going to a KFC with only one employee who takes the order, cleans the toilets, and cooks the food in that order.

Now, on a modern CPU, you might have a clock cycle around 4 gigahertz, and if it's handling one instruction per cycle,

you're only able to perform 4 billion instructions per second.

Now, if 4 Gips is not enough, you can modify your Python code to take advantage of multiple threads,

but it adds a lot of complexity to your code.

And there's all kinds of gotchas, like race conditions, deadlocks, thread starvation, and may even lead to conflicts with demons.

Even if you do manage to get it working, you might find that your CPU just doesn't have enough juice at

which point you look into using the thousands of CUDA cores on your GPU.

But now you'll need to write some C++ code and likely blow your leg off in the process.

Well, what if there is a language that just knew how to run things in parallel by default?

That's the promise of Bend.

Imagine we have a computation that adds two completely random numbers together.

In Python, the interpreter is going to convert this into bytecode, and then eventually run it on the Python virtual machine.

Pretty simple, but in Bend, things are a little more complex.

The elements of the computation are structured into a graph, which are called interaction combinators.

You can think of it as a big network of all the computations that need to be done.

When two nodes run into each other, the computation progresses by following a simple set of rules

that rewrite the computation in a way that can be done in parallel.

It continues this pattern until all computations are done, then merges the result back into whatever expression was returned from the function.

This concept of interaction combinators goes all the way back to the 1990s, and is implemented in a runtime called the higher -order virtual machine.

HVM is not meant to be used directly, and that's why they built

Bend, a high -level language, to interface with it.

And the language itself is implemented in Rust.

Its syntax is very similar to Python, and we can write a hello world by defining a main function that returns a string.

Now to execute this code, we can pull up the terminal and use the ben run command.

By default, this is going to use the Rust interpreter, which will execute it sequentially, just like any other boring language.

But now here's where things get interesting.

Imagine we have an algorithm that needs to count a bunch of numbers and then add them together.

The first thing that might blow your mind is that bend does not have loops.

Like, we can't just do a for loop like we would in Python.

Instead, bend has something entirely different called a fold that works like a search and replace for data types.

And any algorithm that requires a loop can be replaced with a fold.

Basically, a fold allows you to consume recursive data types in parallel, like a list or a tree.

But first, we need to construct a recursive data type.

And for that, we have the bend keyword, which is like the opposite of fold.

Now, if that's a little too mind -bending, maybe check out my back catalog for recursion in 100 seconds.

But now let's see what this looks like from a performance standpoint.

When I try to run this algorithm on a single thread, it takes forever, like 10 minutes or more.

However, I can run the same code without any modification whatsoever with the bend run C command.

When I do that, it's now utilizing all 24 threads on my CPU.

And now it only takes about 30 seconds to run the computation.

That's a huge improvement, but I think we can still do better.

Because I'm a baller, I have an NVIDIA RTX 4090, and once again, I can run this code without any modification on CUDA with bendrun -cu.

And now this code only takes one and a half seconds to run, and I'll just go ahead and drop the mic right there.

This has been the Code Report, thanks for watching, and I will see you in the next one.

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이 레슨의 어휘와 말하기 포인트

이 말하기 레슨은 영상 “Mind-bending new programming language for GPUs just dropped..”을(를) 바탕으로 합니다. 가장 자주 반복되는 단어는 다음과 같습니다: code, bend, computation, Python, parallel. 이 영상에는 섀도잉할 문장 60개와 단어 904개가 있습니다. 말하는 구간의 길이는 4:00입니다. 화자는 분당 약 226단어로 빠르게 말하므로 연음과 약하게 발음되는 소리가 많습니다. 영어에서 가장 많이 쓰이는 3,000단어에 속하는 단어가 77%뿐이라 어휘가 어려운 편입니다.

이 영상의 핵심 어휘

영상에 나오는 익혀 둘 만한 단어 15개를 발음, 뜻과 함께 정리했습니다.

단어	발음	뜻
bend 동사	/bɛnd/	구부리다
parallel 형용사	/ˈpæ.ɹəˌlɛl/	평행의
thread 명사	/ˈθɹɛd/	실
fold 동사	/ˈfəʊld/	개다, 접다
algorithm 명사	/ˈælɡəɹɪðm̩/	알고리즘, 알고리듬
loop 명사	/luːp/	고리
solve 동사	/sɒlv/	해결하다
virtual 형용사	/ˈvɜɹt͡ʃuəl/	사실상의
default 명사	/dɪˈfɔlt/	디폴트
interaction 명사	/ˌɪn.təˈɹæk.ʃən/	상호작용
execute 동사	/ˈɛksɪˌkjuːt/	처형하다
cloud 명사	/ˈklaʊ̯d/	구름
element 명사	/ˈɛləmənt/	요소
string 명사	/stɹɪŋ/	끈
disaster 명사	/dɪˈzɑːs.təː/	재난, 재앙

이 영상의 문법

화자가 가장 많이 쓰는 문형을 영상 속 실제 표현과 함께 정리했습니다.

문형	영상 속 표현
수동태 be + 과거분사 — 누가 하는지보다 무슨 일이 일어나는지에 초점	could be solved · are structured · be done
관계절 who / which + 절 — 사람이나 사물에 대한 추가 정보	graph, which are · interpreter, which will · keyword, which is

주의할 발음

화자는 you're, can't, doesn't 같은 축약형과 약화된 형태를 8번 사용합니다. 들리는 대로 짧게 발음하세요.

“th” 소리: thread /ˈθɹɛd/, algorithm /ˈælɡəɹɪðm̩/
“sh”와 “zh” 소리: interaction /ˌɪn.təˈɹæk.ʃən/, instruction /ɪnˈstɹʌkʃən/, modification /ˌmɑdɪfɪˈkeɪʃən/, starvation /stɑɹˈveɪʃən/, computation /ˌkɑmpjʊˈteɪʃn̩/
긴 단어 — 강세 위치에 주의: interaction /ˌɪn.təˈɹæk.ʃən/, modification /ˌmɑdɪfɪˈkeɪʃən/, interpreter /ɪnˈtɝ.pɹɪ.tɚ/, complexity /kəmˈplɛk.sɪ.ti/, whatsoever /ˌ(h)wʌtsoʊˈɛvɚ/

한국어 화자가 어려워하는 소리:

/f/ — ㅍ(/p/)으로 바꾸지 말고 윗니를 아랫입술에 대기: fold /ˈfəʊld/, default /dɪˈfɔlt/, modification /ˌmɑdɪfɪˈkeɪʃən/, define /dɪˈfaɪn/, interface /ˈɪn(t)ɚˌfeɪs/
/v/ — ㅂ(/b/)과 구별하기: solve /sɒlv/, virtual /ˈvɜɹt͡ʃuəl/, convert /kənˈvɝt/, whatsoever /ˌ(h)wʌtsoʊˈɛvɚ/, starvation /stɑɹˈveɪʃən/
/z/ — ㅈ이 아니라 성대를 울리는 /s/: disaster /dɪˈzɑːs.təː/, utilize /ˈjuː.tɪ.laɪz/, parallelism /ˈpaɹəlɛlɪz(ə)m/

이 영상으로 연습하는 방법

먼저 말하지 않고 영상을 끝까지 듣고 모르는 단어를 적어 둡니다.
0.75배속으로 한 문장씩 섀도잉을 시작하고, 익숙해지면 보통 속도로 돌아갑니다.
자신의 목소리를 녹음해 원본과 비교하고, bend, parallel, thread 같은 단어에 특히 주의합니다.

쉐도잉이란? 영어 실력을 빠르게 키우는 과학적 방법

쉐도잉(Shadowing)은 원래 전문 통역사 훈련을 위해 개발된 언어 학습 기법으로, 다언어 학자인 Dr. Alexander Arguelles에 의해 대중화된 방법입니다. 핵심 원리는 간단하지만 매우 강력합니다: 원어민의 영어를 들으면서 1~2초의 짧은 지연으로 즉시 소리 내어 따라 말하는 것——마치 '그림자(shadow)'처럼 화자를 따라가는 것입니다. 문법 공부나 수동적인 청취와 달리, 쉐도잉은 뇌와 입 근육이 동시에 실시간으로 영어를 처리하고 재현하도록 훈련합니다. 연구에 따르면 이 방법은 발음 정확도, 억양, 리듬, 연음, 청취력, 말하기 유창성을 크게 향상시킵니다. IELTS 스피킹 준비와 자연스러운 영어 소통을 원하는 분들에게 특히 효과적입니다.

섀도잉 방법: 단계별 전체 가이드 읽기 →

쉐도잉 연습: Mind-bending new programming language for GPUs just dropped... - 영상으로 영어 말하기 배우기

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