تدريب Shadowing: Mind-bending new programming language for GPUs just dropped... - تعلم التحدث بالإنجليزية عبر الفيديو
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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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المفردات وملاحظات التحدث لهذا الدرس
هذا الدرس في المحادثة مبني على الفيديو “Mind-bending new programming language for GPUs just dropped..”. أكثر الكلمات تكرارًا في الفيديو: code, bend, computation, Python, parallel. يحتوي هذا الفيديو على 60 جملة و904 كلمة للتدرب على الترديد. مدة الكلام 4:00. يتكلم المتحدث بسرعة، نحو 226 كلمة في الدقيقة، لذا ستسمع كثيرًا من وصل الكلمات واختزال الأصوات. 77% فقط من الكلمات ضمن أكثر 3,000 كلمة شيوعًا في الإنجليزية، فالمفردات صعبة نسبيًا.
أهم المفردات في هذا الفيديو
15 كلمة من الفيديو تستحق التعلّم، مع النطق والمعنى:
| الكلمة | النطق | المعنى |
|---|---|---|
| bend فعل | /bɛnd/ | ثَنَى |
| parallel صفة | /ˈpæ.ɹəˌlɛl/ | مُوَازٍ |
| thread اسم | /ˈθɹɛd/ | خَيْط, خيط |
| fold فعل | /ˈfəʊld/ | طَوَى |
| algorithm اسم | /ˈælɡəɹɪðm̩/ | خَوَارِزْمِيَّة |
| loop اسم | /luːp/ | عُرْوَة, عُقْدَة |
| solve فعل | /sɒlv/ | ذَابَ, حَلَّ |
| interaction اسم | /ˌɪn.təˈɹæk.ʃən/ | تَآثُر, تَفَاعُل |
| implement فعل | /ˈɪmpləmənt/ | نَفَّذَ, نَجَزَ |
| instruction اسم | /ɪnˈstɹʌkʃən/ | تَعْلِيم |
| execute فعل | /ˈɛksɪˌkjuːt/ | أَعْدَمَ |
| cloud اسم | /ˈklaʊ̯d/ | سَحَاب, غَيْم |
| element اسم | /ˈɛləmənt/ | عُنْصُر |
| string اسم | /stɹɪŋ/ | وَتَر |
| disaster اسم | /dɪˈzɑːs.təː/ | كَارِثَة, مُصِيبَة |
القواعد في هذا الفيديو
أكثر التراكيب التي يستخدمها المتحدث، مع العبارات نفسها من الفيديو:
| التركيب | في الفيديو |
|---|---|
| المبني للمجهول be + اسم المفعول — التركيز على ما يحدث لا على من يفعله | could be solved · are structured · be done |
| جمل الوصل who / which + جملة — معلومة إضافية عن شخص أو شيء | graph, which are · interpreter, which will · keyword, which is |
نطق يحتاج إلى انتباه
يستخدم المتحدث 8 من الصيغ المختصرة، مثل you're, can't, doesn't. انطقها بصيغتها القصيرة كما تسمعها.
- أصوات “th”: thread /ˈθɹɛd/, algorithm /ˈælɡəɹɪðm̩/
- أصوات “sh” و“zh”: interaction /ˌɪn.təˈɹæk.ʃən/, instruction /ɪnˈstɹʌkʃən/, modification /ˌmɑdɪfɪˈkeɪʃən/, starvation /stɑɹˈveɪʃən/, computation /ˌkɑmpjʊˈteɪʃn̩/
- الكلمات الطويلة — انتبه لموضع النبر: interaction /ˌɪn.təˈɹæk.ʃən/, modification /ˌmɑdɪfɪˈkeɪʃən/, interpreter /ɪnˈtɝ.pɹɪ.tɚ/, complexity /kəmˈplɛk.sɪ.ti/, whatsoever /ˌ(h)wʌtsoʊˈɛvɚ/
أصوات يجدها متحدثو العربية صعبة:
- /p/ — ليس /b/: انطقه مع نفخة هواء: parallel /ˈpæ.ɹəˌlɛl/, loop /luːp/, implement /ˈɪmpləmənt/, interpreter /ɪnˈtɝ.pɹɪ.tɚ/, complexity /kəmˈplɛk.sɪ.ti/
- /v/ — ليس /f/: مع اهتزاز الأوتار الصوتية: solve /sɒlv/, virtual /ˈvɜɹt͡ʃuəl/, convert /kənˈvɝt/, whatsoever /ˌ(h)wʌtsoʊˈɛvɚ/, starvation /stɑɹˈveɪʃən/
- تتابع الصوامت — لا تضف حركة بينها: bend /bɛnd/, thread /ˈθɹɛd/, fold /ˈfəʊld/, solve /sɒlv/, default /dɪˈfɔlt/
كيف تتدرب بهذا الفيديو
- استمع إلى الفيديو كاملًا مرة واحدة دون أن تتكلم، ودوّن الكلمات التي لا تعرفها.
- ابدأ بسرعة 0.75×، وردّد جملة جملة، ثم عُد إلى السرعة العادية عندما يصبح الأمر سهلًا.
- سجّل صوتك وقارنه بالأصل، مع الانتباه إلى كلمات مثل bend, parallel, thread.
ما هي تقنية التظليل الصوتي؟
التظليل الصوتي (Shadowing) تقنية تعلم لغة مدعومة علمياً، طُورت أصلاً لتدريب المترجمين الفوريين المحترفين. الطريقة بسيطة لكنها قوية: تستمع لصوت إنجليزي أصلي وتكرره فوراً بصوت عالٍ — كظل يتبع المتحدث بتأخير 1-2 ثانية. تُظهر الأبحاث تحسناً كبيراً في دقة النطق والتنغيم والإيقاع وربط الأصوات والاستماع والطلاقة.