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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Bu dersin kelimeleri ve konuşma notları
Bu konuşma dersi “Mind-bending new programming language for GPUs just dropped..” videosuna dayanıyor. En çok tekrarlanan kelimeler: code, bend, computation, Python, parallel. Bu videoda gölgeleme çalışması için 60 cümle ve 904 kelime var. Konuşma bölümü 4:00 sürüyor. Konuşmacı hızlı konuşuyor, dakikada yaklaşık 226 kelime; bu yüzden birbirine bağlanan ve zayıflayan sesler duyacaksınız. Kelimelerin yalnızca %77’i İngilizcede en sık kullanılan 3.000 kelime arasında, bu yüzden kelime dağarcığı zorlayıcı.
Bu videodaki önemli kelimeler
Videodan öğrenmeye değer 15 kelime, telaffuzu ve anlamıyla:
| Kelime | Telaffuz | Anlam |
|---|---|---|
| bend fiil | /bɛnd/ | bükmek |
| parallel sıfat | /ˈpæ.ɹəˌlɛl/ | paralel |
| thread isim | /ˈθɹɛd/ | iplik |
| fold fiil | /ˈfəʊld/ | katlamak |
| algorithm isim | /ˈælɡəɹɪðm̩/ | algoritma |
| loop isim | /luːp/ | ilik |
| solve fiil | /sɒlv/ | çözmek, halletmek |
| virtual sıfat | /ˈvɜɹt͡ʃuəl/ | sanal |
| default isim | /dɪˈfɔlt/ | temerrüt |
| implement fiil | /ˈɪmpləmənt/ | tatbik etmek, uygulamak |
| execute fiil | /ˈɛksɪˌkjuːt/ | idam etmek |
| cloud isim | /ˈklaʊ̯d/ | bulut |
| element isim | /ˈɛləmənt/ | öğe, eleman |
| string isim | /stɹɪŋ/ | ip, tel |
| disaster isim | /dɪˈzɑːs.təː/ | afet, felaket |
Duyacağınız deyimsel fiiller
| Kelime | Anlam |
|---|---|
| check out fiil | gözden geçirmek |
Bu videodaki dil bilgisi
Konuşmacının en çok kullandığı yapılar, videodaki sözcüklerin aynısıyla:
| Yapı | Videoda |
|---|---|
| Edilgen yapı be + fiilin üçüncü hâli — kimin yaptığı değil, ne olduğu önemli | could be solved · are structured · be done |
| İlgi cümlecikleri who / which + cümle — bir kişi ya da şey hakkında ek bilgi | graph, which are · interpreter, which will · keyword, which is |
Dikkat edilecek telaffuzlar
Konuşmacı you're, can't, doesn't gibi kısaltılmış biçimleri 8 kez kullanıyor. Bunları duyduğunuz gibi kısa söyleyin.
- “th” sesleri: thread /ˈθɹɛd/, algorithm /ˈælɡəɹɪðm̩/
- “sh” ve “zh” sesleri: interaction /ˌɪn.təˈɹæk.ʃən/, instruction /ɪnˈstɹʌkʃən/, modification /ˌmɑdɪfɪˈkeɪʃən/, starvation /stɑɹˈveɪʃən/, computation /ˌkɑmpjʊˈteɪʃn̩/
- Uzun kelimeler — vurguyu doğru yere koyun: interaction /ˌɪn.təˈɹæk.ʃən/, modification /ˌmɑdɪfɪˈkeɪʃən/, interpreter /ɪnˈtɝ.pɹɪ.tɚ/, complexity /kəmˈplɛk.sɪ.ti/, whatsoever /ˌ(h)wʌtsoʊˈɛvɚ/
Türkçe konuşanların zorlandığı sesler:
- /w/ — dudaklar yuvarlak, /v/ değil: whatsoever /ˌ(h)wʌtsoʊˈɛvɚ/, keyword /ˈkiː.wɜːd/, sequentially /səˈkwɛntʃəli/
- Kelime başındaki ünsüz kümesi — araya ünlü eklemeyin: thread /ˈθɹɛd/, cloud /ˈklaʊ̯d/, clock /klɑk/, string /stɹɪŋ/, graph /ɡɹæf/
- /æ/ — “e”den daha açık: parallel /ˈpæ.ɹəˌlɛl/, algorithm /ˈælɡəɹɪðm̩/, interaction /ˌɪn.təˈɹæk.ʃən/, graph /ɡɹæf/, catalogue /ˈkæt.əˌlɔɡ/
Bu videoyla nasıl çalışılır
- Videonun tamamını konuşmadan bir kez dinleyin ve bilmediğiniz kelimeleri not edin.
- 0,75× hızla başlayın, cümle cümle tekrar edin ve kolaylaşınca normal hıza dönün.
- Kendinizi kaydedin ve orijinaliyle karşılaştırın; bend, parallel, thread gibi kelimelere özellikle dikkat edin.
Gölgeleme Tekniği Nedir?
Gölgeleme, başlangıçta profesyonel tercüman eğitimi için geliştirilen ve çok dilli Dr. Alexander Arguelles tarafından popüler hale getirilen, bilim destekli bir dil öğrenme tekniğidir. Yöntem basit ama güçlüdür: ana dili İngilizce olan bir sesi dinler ve hemen yüksek sesle tekrar edersiniz — konuşmacıyı 1-2 saniye gecikmeyle takip eden bir gölge gibi. Pasif dinleme veya dilbilgisi alıştırmalarının aksine, gölgeleme beyninizi ve ağız kaslarınızı gerçek konuşma kalıplarını eşzamanlı olarak işlemeye ve yeniden üretmeye zorlar. Araştırmalar, telaffuz doğruluğu, tonlama, ritim, bağlı konuşma, dinleme anlama ve konuşma akıcılığını önemli ölçüde geliştirdiğini göstermektedir — bu da onu IELTS Konuşma hazırlığı ve gerçek dünya İngilizce iletişimi için en etkili yöntemlerden biri yapar.