쉐도잉 연습: Wrote My Own Memory Allocator (and ran DOOM with It) - 영상으로 영어 말하기 배우기
레슨 만드는 중...
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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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이번 레슨에서 배울 것
이 비디오는 C 언어로 메모리 할당기를 직접 만드는 과정을 설명하며, 도움되는 기술 용어와 자연스러운 구어체 표현이 가득합니다. 영어 쉐도잉 연습에 좋은 자료로, 기술적 내용을 설명하는 발음과 속도, 논리적인 흐름을 따라가는 연습을 할 수 있습니다. 특히 "malloc", "free function"과 같은 프로그래밍 용어의 발음과 사용법, 일상적인 이야기와 기술 설명이 섞인 문장 구조를 익힐 수 있습니다.
핵심 어휘 및 표현
- malloc: 동적 메모리 할당 함수로, "mælɒk"이라고 발음합니다.
- garbage collector: 가비지 컬렉터, 메모리 관리 기능을 하는 프로그램 요소입니다.
- segmentation fault: 세그먼테이션 폴트, 메모리 접근 오류로 인한 프로그램 오류입니다.
- system call: 시스템 콜, 운영체제에 서비스를 요청하는 함수입니다.
- virtual memory: 가상 메모리, 물리 메모리를 추상화한 메모리 공간입니다.
쉐도잉 연습 팁
이 비디오는 기술적 내용을 설명하면서도 화자의 목소리가 자연스럽고 속도가 적당하여 쉐도잉에 적합합니다. shadowing site나 shadowspeak을 이용해 연습할 때는 다음과 같은 점을 주의하세요. 먼저, "What if I wrote my own malloc?"와 같은 질문 형태의 문장은 높은 음조로 끝나는 것을 확인하고 따라하세요. 둘째, "mmap"이나 "munmap"과 같은 약어의 발음은 명확하게 하되, 주변 단어와의 연결을 자연스럽게 만들어야 합니다. 셋째, 긴 설명문에서 논리적인 구분을 하는 "First, I had to choose the names."와 같은 표현은 강조하여 발음하여, 흐름을 따라가기 쉽게 만드세요. 마지막으로, 영어 발음 교정에 집중하면서도 내용을 이해하려고 노력하면, 발음 뿐만 아니라 리스닝 능력도 함께 향상시킬 수 있습니다. 쉐도잉을 반복하면서 자연스러운 발화 속도와 억양을 익혀보세요!
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.