https://source.chromium.org/chromium/chromium/src/+/main:tes...
6,885 karma · joined June 7, 2011
evan.martin@gmail.com
My posts on HN: https://news.ycombinator.com/from?site=neugierig.org
https://source.chromium.org/chromium/chromium/src/+/main:tes...
Given that a crate is the unit of build parallelization in Rust, there's a benefit to more crates especially when they don't cost much cognitive overhead. You could imagine using crates in the way you'd typically use separate mods in a normal Rust project.
I dug around in their code search to find some examples but didn't see much Rust in there, seems still early. I think https://source.chromium.org/chromium/chromium/src/+/main:tes... has ~4 Rust files that end up separate crates though. (One of them defines a proc macro so even in a Cargo built Rust project it would need to be in its own separate crate, I think!)
If I have to drive to the store to get it, I wouldn’t have shopped with them! It feels like every time I don’t order with Amazon the stores remind me why I ought to.
As we talked about this very isolation problem he told me about his neighbors who kept inviting him over and offering to watch the kids for him and how he thought it was just weird and couldn’t trust them. It broke my heart — I could just imagine the neighbors trying to be good to their community and that very behavior is met with distrust.
(I read half the book he mentioned and asked him about it the next time I saw him. Turns out he hadn’t read the book, just heard about it on a podcast. My quest to meet someone who reads continues.)
As they observe, Ninja gets to be fast mostly by cheating: it avoids a lot of work by saying many things are just out of scope for Ninja to do, and that means it is a useful a target to race against. (Funny thing: when I wrote Ninja I was misremembering how fast an earlier build system was so I kept trying to make it faster. So don't treat it as a lower bound, I just made it up!)
I comment here to say I find the explanation for 'why' in this post unsatisfying. They mention three design decisions.
The first one is a criticism of CMake, not Ninja (?), so I don't think it can be why. I might have misunderstood?
The second reason given is doing some work like header dependencies in multiple threads. This is the most plausible reason to me but it still feels unlikely. It's a very small amount of work: the post mentions 300 compiles, so maybe parsing 300 small text files?
The third is that they run the compiler up front an additional time to gather headers, which is strictly more work than Ninja. There is some hand waving about file access patterns but I am skeptical; if the end-to-end build time is 3 seconds then the project is small enough to all fit in kernel caches. They also mention doing other things like invoking the compiler to get version information. This seems like it would dwarf any performance gain from number 2.
Maybe it's just my own curiosity, I think this post would be better if it had a better explanation for the reason. I'm not disputing the result, I just think the result should make you suspicious that something else is going on, and you might learn something from that! You could for example explore whether it's the header dependency thing by profiling the Ninja invocation and seeing if it's waiting for CPU or waiting for tasks to execute.
(If I had to guess without looking at any of the involved code, I would predict it's something about how CMake generates the build, like it introduces serialization in a place where build2 is parallel, or it adds some extra build steps like gathering the current git hash into a header file or something.)
(I don't think Google's often capricious ranking changes really succeed at this, but the outcomes in this post seems like something hypothetically good?)
Think of variable width characters and kerning and ligatures and hyphenation and justification. Imagine computers had been won by a CJK language, which have none of these problems. You could imagine a similar article about how exotic and difficult English layout is.
I've gone in circles a few times with how to think about image buffer management because I also support DirectDraw, which is designed to be backed by accelerated graphics, with operations like scaling bitblit. (Currently the Theseus implementation uses a shared "Surface" type as the backing store for both GDI Windows and DirectX Surfaces.)
It's a bit complicated by a few things. (1) DirectX surfaces can be "locked" to access as pixel buffers, so any accelerated surface indirection I guess would need to be able to copy pixels back down into emulator memory. Which I guess I could just implement. (2) There's a bunch of different modes for operations like bitblit like setting a color key for transparency that I can't implement with the canvas API, so I think I'd need to use GL shaders if I want acceleration, not just canvas.
The doc you linked has two forms of use, sync and async.
For sync: it seems the idea is for the worker to render into an OffscreenCanvas, then postMessage an ImageBitmap created with transferToImageBitmap from worker to main thread for drawing. It seems like it would need to allocate a new bitmap for each frame. Currently Theseus puts the pixel data in shared memory and the main thread copies it out (required to create an ImageData), which at least in principle could reuse the copy buffer (though it currently doesn't), which seems better? https://github.com/evmar/theseus/blob/a5a849dbcf8046a2d1837a...
For async: in this the idea is have the worker render into an OffscreenCanvas linked to the on-screen one. But it seems to get an OffscreenCanvas in a worker, the main thread canvas must .transferControlToOffscreen() it to the worker. Under the current synchronization model[1] the only time the worker can receive a message is during startup, because the rest of the time it's deep in its own wasm call stacks. This means that if the worker needs to resize its canvas and then paint to it, it's stuck.
[1] I wrote "current" because after writing this post I learned about JSPI which might help with this.
This is slower than a direct jmp (which doesn’t use the table) but also indirect jumps were slower in the original program to begin with and typically don’t occur in performance-critical loops.
I was also surprised by how much goop there is between startup and main. In retrowin32 I just implemented it all, though I wonder how much I could get away with not running it in the Theseus replace-some-parts model.
I mostly relied on my own x86 emulator, but I also implemented the thunking between 64-bit and 32-bit mode just to see how it was. It definitely was some asm but once I wrapped my head around it it wasn't so bad, check out the 'trans64' and 'trans32' snippets in https://github.com/evmar/retrowin32/blob/ffd8665795ae6c6bdd7... for I believe all of it. One reframing that helped me (after a few false starts) was to put as much code as possible in my high-level language and just use asm to bridge to it.
In the post there is a godbolt link showing a compiler inlining a simple add, but a real implementation of x86 add would be much more complex.
I have read other projects where the authors put some effort into getting exactly the machine code they wanted out. For example, maybe you want the virtual regs.eax to actually exist in a machine register, and one way you might be able to convince a compiler to do that is by passing it around as a function parameter everywhere instead as a struct element. I have not investigated this myself.