シャドーイング練習: Wrote My Own Memory Allocator (and ran DOOM with It) - 動画で英語スピーキングを学ぶ
レッスンを作成中...
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One day I was outside, doing normal human activities like touching grass and listening to birds.
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When the blazing sun gave me a strange idea.
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What if I wrote my own malloc?
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So as soon as I got home I started building.
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And in this video I'll show you how I wrote my own memory allocator in PUC from scratch
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and how I used to run a real application.
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Before we start programming it's important to understand what malloc actually does.
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The standard malloc function is used to allocate memory dynamically.
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For example, you can use it to create a dynamic array, precisely known at runtime.
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But because this is C, there is always some problem with memory hiding somewhere.
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As you probably know, C doesn't have a built-in garbage collector, so managing memory is the programmer's responsibility.
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For the allocation, C has a special free function.
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It takes a pointer to a previously allocated memory block and marks that block as free.
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So the system can reuse it later.
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And that means I also need to create my own free function.
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First I had to choose the names.
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I remembered the name of my channel and decided to call them podalloc and pod3.
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But before we continue, let's take a look at how memory allocation actually works.
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Every process has its own memory space.
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This space is divided into several zones.
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At the top we have the stack, which is used for function calls and local variables.
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Below it we have the heap, which is used exactly for dynamic user data.
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And this is the part that malloc works with.
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Below that there are other memory regions used for global variables, program code and other things that are not really important for us right now.
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In this layout the stack grows downward, while the heap grows upward.
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And it's better to keep these two zones from overlapping, unless you really want to meet a segmentation fold.
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Another question is how we can actually use this heap for our needs.
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We need some way to request memory from the operating system.
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There are a few ways to do this, but for me the best is MMAP.
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It works kinda similar to malloc.
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You tell it how much memory you need and it's returned a pointer to the beginning of that memory region.
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But the important difference is that malloc reserves memory inside an already existing area.
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While MMAP asks the iOS for a new memory region of their requested size.
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Now we can use this to write a simple version of the allocator.
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To free allocated memory we need to know its size.
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For that I added a mem block structure with a size field and a data pointer, which points to the beginning of the memory available to the user.
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In POT-A-LOG we simply call a map to request some memory from the operating system.
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Then at the beginning of the memory region we place our mem block structure.
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It works like a header for the allocated block.
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Later in POT-3 we use this header with monMap monMap does the opposite of mmap.
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It releases the memory back to the OS.
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For this to work it needs a pointer to the beginning of the memory region and its size, exactly what we keep in the header.
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After this we can finally test how it actually works.
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As you can see I allocated some memory, wrote some text into it and printed it.
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And works fine!
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But of course it can't be that easy.
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Right now this is basically just a wrapper around M-map and Moonmap.
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The main problem with this approach is time.
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I wrote a simple test that allocates and frees memory, and then compares it with the malloc from C.
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As you can see, the difference is really big.
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My allocator is 435 times slower.
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It's even slower than me understanding hints.
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Using this in a real program would seriously slow it down.
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The reason is M-Map and MoonMap.
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Every allocation and every free requires a system call.
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And they are pretty slow.
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Sometimes they are so slow that you forget why you even call them.
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To make our allocator faster, we need to reduce the number of M-Map calls as much as possible.
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A common approach is to call a map once to allocate a large chunk of memory.
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Usually at least one virtual memory page in your system.
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If you're wondering what page I'm talking about, here's a quick reminder of what virtual memory is.
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It's a memory abstraction provided by the operating system.
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Every process gets its own virtual address space, which is divided into small, fixed-sized parts called pages.
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The program works with virtual addresses, and the system translates these addresses to real physical memory in RAM.
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Because of this, variables in different programs can even have the same addresses.
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But that doesn't mean they are stored in the same place in RAM.
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Each address just belongs to its own process virtual memory space.
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So, with a new approach we allocate one big chunk of memory
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and then filled step by step whenever someone calls for tolog.
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When this page fills up, we allocate another one.
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As you can see, in this example we have 8 memory allocations, but only 2 mmap calls.
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This is one of those cases where the number doesn't matter, but matters how you use it.
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To implement this I changed the mem block structure a little bit.
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Now each block works like part of doubly linked list.
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And I also added a free flag to show whether the block is available for allocation or not.
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Also because we now use pages, I added a page structure.
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It works like another list, but instead of linking memory blocks, it links different pages together.
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This will come in handy later.
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After this I change the allocator function.
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Now it searches for a free block with enough space.
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If it can't find one, we create another memory page.
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You may notice that if the user asks for only 100 bytes, we allocate an entire page for it.
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We use a much bigger block.
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We are just wasting memory.
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To deal with this, we split the memory block.
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One part is given to the user and the other part remains free for future allocations.
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With this new approach I also changed port 3.
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If we split large memory blocks during allocation, we need to merge them back during their allocation.
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Then the merged block can be reduced later.
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And now we only return memory to the system when the whole page becomes free.
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So this approach reduces main map calls too.
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Well, let's test this with some allocations.
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And as you can see it somehow become worse.
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Now it is 1823 times slower, which doesn't really look like a better solution.
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Without previous changes, it looks more like a waste of time.
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But if we look at the number of mMAP calls, it becomes much smaller, so that means the problem is not the system calls.
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After a bit of investigation, I found that most of the time is spent searching for a free block.
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More precisely, it takes 99.3% of the total time.
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On one hand, that's good, because system calls are no longer the main problem.
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On other hand, now we need some fancy data structure to make it faster.
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The current version searches through a list of all memory blocks.
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It has to check each block until it finds a free one.
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So this takes about 0 and time.
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Looking at this layout, we can see that free blocks are scattered randomly around the page.
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At the end of the page, there is also some unused space that has not been allocated yet.
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What if we move free blocks into a separate list?
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That's where we can quickly get a free block without searching through all allocated blocks.
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But there is another problem.
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We need to find a block with the right size.
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For example, if we need a block of 100 bytes or more, we may have to skip smaller blocks before finding one that actually fits.
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This can be fixed too.
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Instead of using one free list, we create 8 of them.
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Each list stores memory blocks of a certain size category.
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When a block is freed, it's added to the appropriate list.
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The benefit is that this is much faster than the previous approach.
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Usually programs allocate small chunks of memory, so most allocation will fit into one of those eight categories.
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Another question is how to do this in code.
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First I added three list pointers to our structures.
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Then I added functions for inserting blocks into three lists and removing blocks from them.
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Now when a new page is created, its first free block is automatically added to the appropriate free list.
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I also changed how splitting works.
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Now when we split a block, we remove the original block from the free list, give one part to the user and add the remaining part back to the correct free list.
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And in pod3 I now use the same insert and remove function to keep all free lists updated.
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At this point it can already works, but there is always some hidden problem in a low level program.
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And this time the problem is not even the program itself, it's the machine where the program runs.
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Right now I can allocate 3 bytes and then 4 bytes.
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And as you can see the second address is not aligned.
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On some systems this can cause an error, because some processes don't like unaligned addresses.
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Also, aligned memory is usually faster to read and write.
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So, to fix this we need to round up the requested amount of memory.
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We can do it with simple math, but that would be too slow and I need somehow to justify all the time I spent learning bit operators.
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This version works much faster.
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We start by adding this to move the number into the next alignment range.
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For example, if the number is 12 and the alignment is 8, it becomes 19.
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When we take that, which is 7, in binary it looks like this, exactly the lowest 3 bits.
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After that we use the tilde operator to flip the bits and create a mask.
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Finally we use the end operator to raise the lowest 3 bits.
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As a result 19 becomes 16, which is perfectly aligned to 8 bytes.
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Pretty easy, as you can see.
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So after crawling through the depths of C, we can finally run it.
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And this version actually works better than all previous ones.
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Of course it's still not as fast as the original Mylock, but further improvements would be much harder and would probably give us a smaller performance gain.
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Testing only with benchmarks is boring, so let's see how it works in a real program.
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For the target I chose Doom.
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I replaced its original allocation function with my own, added some logs to track memory usage and wrote a small python script to visualize it.
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After playing for some time, everything worked fine for me, no crashes or anything like that.
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For me, this was a really interesting project, And I hope you enjoy it too.
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I recommend you trying to write your own allocator as well.
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It really helps you understand how memory works and improves your understanding of low-level programming.
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If you enjoyed this video and want to see more, please subscribe, leave a like and write a comment with your ideas or questions.
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Thanks for watching!
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この動画で身につくスキル
この動画を使ったシャドーイング練習では、技術的な内容を明確に説明するスピーチのリズムと、専門用語を自然に組み込んだ会話の流れ、そして長文を聞き取りながら要点をつかむ能力が身につきます。IELTSスピーキング対策にも役立つ、論理的な説明力が向上しますよ。
聞き取りに注意するポイント
動画の中では、連結発音やリダクションが多く見られます。例えば、"what if"が"/wɒtɪf/"となるのや、"because"が"/bɪ'kəz/"に短縮されるのが特徴的です。また、"mmap"や"munmap"などの略語の発音も、正確に聞き取ることが重要です。シャドーイングサイトで繰り返し練習することで、これらの音の繋がりが自然に口に出せるようになります。
ネイティブのように話すコツ
スピーカーのリズムは、技術的な説明でも抑揚をつけながら話すことがポイントです。"But of course, it can't be that easy."のようなフレーズでは、"but"を強調し、"easy"を低く抑えることで、驚きのニュアンスを表現します。また、長い文を話す際は、句読点の位置でちょっと息を吸うことで、聞き手が追いやすくなります。shadow speechの練習でこれらのリズムを真似ることで、自然な発音が身につきます。
この動画は、シャドーイングの素材として最適で、英語シャドーイングのスキルを向上させるだけでなく、コンピューターの基礎知識も学べる一石二鳥の内容です。shadowspeaksのような方法で繰り返し練習して、ネイティブ並みのスピーキング力を目指しましょう！
シャドーイングとは？英語上達に効果的な理由
シャドーイング（Shadowing）は、もともとプロの通訳者養成プログラムで開発された言語学習法で、多言語習得者として知られるDr. Alexander Arguelles によって広く普及されました。方法はシンプルですが非常に効果的：ネイティブスピーカーの英語を聞きながら、1〜2秒の遅延で声に出してすぐに繰り返す——まるで「影（shadow）」のように話者を追いかけます。文法ドリルや受動的なリスニングと異なり、シャドーイングは脳と口の筋肉が同時にリアルタイムで英語を処理・再現することを強制します。研究により、発音精度、抑揚、リズム、連音、リスニング力、そして会話の流暢さが大幅に向上することが確認されています。IELTSスピーキング対策や自然な英語コミュニケーションを目指す方に特におすすめです。