Shadowing Practice: Mind-bending new programming language for GPUs just dropped... - Learn English Speaking with Video
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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.
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This is big if true, because parallel computing is a superpower.
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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.
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Unfortunately, running code in parallel is like conducting a symphony.
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One wrong note, and the entire thing becomes a total disaster.
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But luckily, Bend offers hope by making a bold promise.
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Everything that can run in parallel, will run in parallel.
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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,
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or even all 16 ,000 of your GPU cores.
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You just write some high -level
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Python -looking code, and the rest is magic.
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It is May 17th, 2024, and you're watching the Code Report.
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When you write code in a language like
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Python, your code runs on a single thread.
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That means only one thing can happen at a time.
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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.
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Now, on a modern CPU, you might have a clock cycle around 4 gigahertz, and if it's handling one instruction per cycle,
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you're only able to perform 4 billion instructions per second.
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Now, if 4 Gips is not enough, you can modify your Python code to take advantage of multiple threads,
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but it adds a lot of complexity to your code.
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And there's all kinds of gotchas, like race conditions, deadlocks, thread starvation, and may even lead to conflicts with demons.
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Even if you do manage to get it working, you might find that your CPU just doesn't have enough juice at
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which point you look into using the thousands of CUDA cores on your GPU.
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But now you'll need to write some C++ code and likely blow your leg off in the process.
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Well, what if there is a language that just knew how to run things in parallel by default?
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That's the promise of Bend.
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Imagine we have a computation that adds two completely random numbers together.
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In Python, the interpreter is going to convert this into bytecode, and then eventually run it on the Python virtual machine.
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Pretty simple, but in Bend, things are a little more complex.
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The elements of the computation are structured into a graph, which are called interaction combinators.
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You can think of it as a big network of all the computations that need to be done.
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When two nodes run into each other, the computation progresses by following a simple set of rules
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that rewrite the computation in a way that can be done in parallel.
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It continues this pattern until all computations are done, then merges the result back into whatever expression was returned from the function.
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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.
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HVM is not meant to be used directly, and that's why they built
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Bend, a high -level language, to interface with it.
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And the language itself is implemented in Rust.
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Its syntax is very similar to Python, and we can write a hello world by defining a main function that returns a string.
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Now to execute this code, we can pull up the terminal and use the ben run command.
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By default, this is going to use the Rust interpreter, which will execute it sequentially, just like any other boring language.
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But now here's where things get interesting.
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Imagine we have an algorithm that needs to count a bunch of numbers and then add them together.
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The first thing that might blow your mind is that bend does not have loops.
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Like, we can't just do a for loop like we would in Python.
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Instead, bend has something entirely different called a fold that works like a search and replace for data types.
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And any algorithm that requires a loop can be replaced with a fold.
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Basically, a fold allows you to consume recursive data types in parallel, like a list or a tree.
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But first, we need to construct a recursive data type.
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And for that, we have the bend keyword, which is like the opposite of fold.
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Now, if that's a little too mind -bending, maybe check out my back catalog for recursion in 100 seconds.
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But now let's see what this looks like from a performance standpoint.
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When I try to run this algorithm on a single thread, it takes forever, like 10 minutes or more.
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However, I can run the same code without any modification whatsoever with the bend run C command.
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When I do that, it's now utilizing all 24 threads on my CPU.
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And now it only takes about 30 seconds to run the computation.
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That's a huge improvement, but I think we can still do better.
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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.
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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.
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This has been the Code Report, thanks for watching, and I will see you in the next one.
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Vocabulary and speaking notes for this lesson
This speaking lesson is built on the video “Mind-bending new programming language for GPUs just dropped..”. The speaker keeps coming back to these words: code, bend, computation, Python, parallel. This video has 60 sentences and 904 words to shadow. The speech runs for 4:00. The speaker talks fast, about 226 words per minute, so expect linked and reduced sounds. Only 77% of the words are among the 3,000 most common in English, so the vocabulary is demanding.
Key vocabulary in this video
15 words from the video worth learning, with pronunciation and meaning:
| Word | Pronunciation | Meaning |
|---|---|---|
| bend verb | /bɛnd/ | To cause (something) to change its shape into a curve, by physical force, chemical action, or any other means. |
| parallel adjective | /ˈpæ.ɹəˌlɛl/ | Equally distant from one another at all points. |
| thread noun | /ˈθɹɛd/ | A cord formed by spinning or twisting together textile fibers or filaments into one or more continuous strands, typically used in needlework. |
| fold verb | /ˈfəʊld/ | To bend (any thin material, such as paper) over so that it comes in contact with itself. |
| algorithm noun | /ˈælɡəɹɪðm̩/ | A collection of ordered steps that solve a mathematical problem. A precise step-by-step plan for a computational procedure that possibly begins with an input… |
| loop noun | /luːp/ | A length of thread, line or rope that is doubled over to make an opening. |
| solve verb | /sɒlv/ | To find an answer or solution to a problem or question; to work out. |
| virtual adjective | /ˈvɜɹt͡ʃuəl/ | In effect or essence, rather than in fact or reality; also, imitated, simulated. |
| default noun | /dɪˈfɔlt/ | The condition of failing to meet an obligation. |
| interaction noun | /ˌɪn.təˈɹæk.ʃən/ | The situation or occurrence in which two or more things act upon one another to produce an effect; the effect resulting from such a situation or occurrence. |
| implement verb | /ˈɪmpləmənt/ | To bring about; to put into practice; to carry out. |
| instruction noun | /ɪnˈstɹʌkʃən/ | The act of instructing, teaching, or providing with information or knowledge. |
| execute verb | /ˈɛksɪˌkjuːt/ | To kill, especially as punishment for a capital crime. |
| modification noun | /ˌmɑdɪfɪˈkeɪʃən/ | The change undergone by a word when used in a construction. |
| interpreter noun | /ɪnˈtɝ.pɹɪ.tɚ/ | A person or thing that interprets the meaning of something for another, particularly |
Phrasal verbs you will hear
| Word | Pronunciation | Meaning |
|---|---|---|
| check out verb | To record the departure or withdrawal of someone or something (such as guests, employees, books, etc.). | |
| come down to verb | To reach by moving down or reducing. | |
| go ahead verb | /ˌɡoʊ əˈhɛd/ | To proceed with; to begin. |
| open up verb | To open. | |
| pull up verb | /ˌpʊl ˈʌp/ | To lift upwards or vertically. |
Grammar in this video
The structures the speaker uses most, with the exact words from the video:
| Structure | In the video |
|---|---|
| Passive voice be + past participle — the focus is on what happens, not who does it | could be solved · are structured · be done |
| Relative clauses who / which + clause — extra information about a person or thing | graph, which are · interpreter, which will · keyword, which is |
Pronunciation to watch
The speaker uses 8 contractions and reduced forms, such as you're, can't, doesn't. Say them the short way, as you hear them.
- The “th” sounds: thread /ˈθɹɛd/, algorithm /ˈælɡəɹɪðm̩/
- The “sh” and “zh” sounds: interaction /ˌɪn.təˈɹæk.ʃən/, instruction /ɪnˈstɹʌkʃən/, modification /ˌmɑdɪfɪˈkeɪʃən/, starvation /stɑɹˈveɪʃən/, computation /ˌkɑmpjʊˈteɪʃn̩/
- Long words — get the stress right: interaction /ˌɪn.təˈɹæk.ʃən/, modification /ˌmɑdɪfɪˈkeɪʃən/, interpreter /ɪnˈtɝ.pɹɪ.tɚ/, complexity /kəmˈplɛk.sɪ.ti/, whatsoever /ˌ(h)wʌtsoʊˈɛvɚ/
How to practise with this video
- Listen to the whole video once without speaking and note the words you do not know.
- Start at 0.75× speed, shadow it sentence by sentence, then go back to normal speed once it feels easy.
- Record yourself and compare with the original, paying attention to words like bend, parallel, thread.
What is the Shadowing Technique?
Shadowing is a science-backed language learning technique originally developed for professional interpreter training and popularized by polyglot Dr. Alexander Arguelles. The method is simple but powerful: you listen to native English audio and immediately repeat it out loud — like a shadow following the speaker with just a 1–2 second delay. Unlike passive listening or grammar drills, shadowing forces your brain and mouth muscles to simultaneously process and reproduce real speech patterns. Research shows it significantly improves pronunciation accuracy, intonation, rhythm, connected speech, listening comprehension, and speaking fluency — making it one of the most effective methods for IELTS Speaking preparation and real-world English communication.