Comment by VPenkov
16 days ago
They seem to have a blog post on that: https://trynova.dev/blog/why-build-a-js-engine
It reads like an experimental approach because someone decided to will it into existence. That and to see if they can achieve better performance because of the architectural choices.
> Luckily, we do have an idea, a new spin on the ECMAScript specification. The starting point is data-oriented design (...)
> So, when you read a cache line you should aim for the entire cache line to be used. The best data structure in the world, bar none, is the humble vector (...)
> So what we want to explore is then: What sort of an engine do you get when almost everything is a vector or an index into a vector, and data structures are optimised for cache line usage? Join us in finding out (...)
The impetus for the engine design is indeed, as you say, "someone decided to will it into existence."
A friend of mine who works in the gaming industry told me about the Entity Component System architecture and I thought: Hey, wouldn't that work for a JavaScript engine? So I decided to find out.
Nova itself has already been created at that point and I was part of the project, but it was little more than a README. I then started to push it towards my vision, and the rest is not-quite-history.
A friend of mine who works in the gaming industry told me about the Entity Component System architecture and I thought: Hey, wouldn't that work for a JavaScript engine?
That was the first thing I thought of when I saw your description. But the reason ECS works well is cache coherence. (Why) would a general-purpose runtime environment like a JS engine benefit from ECS? Or alternatively, have you seen performance improvements as a result?
I guess the opposite could also be asked: Why would a game benefit from ECS? A player in the game can do basically anything, there's no guarantee that things are always perfectly accessed in a linear order.
It comes down to statistics: Large data sets in a general-purpose runtime environment are still created through parsing or looping, and they are consumed by looping. A human can manually create small data sets of entirely heterogenous data, but anything more than a 100 items is already unlikely.
Finally, the garbage collector is a kind of "System" in the ECS sense. So even if the JavaScript code has managed to create very nonlinear data sets, the garbage collector will still enjoy benefits. (Tracing the data is still "pointer chasing" but when tracing we don't need to trace in the data order but can instead gather a collection of heap references we've seen, sort them in order and then trace them.)
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I think you're on to something (important). Decomposing structs into separate arrays (heaps) is becoming a thing. eg Rust and others are introducing language features to manually (explicitly) do so. It could be cool if the runtime just handled it.
I stumbled across a new research language with new syntax for just this purpose, to better express iteration and lambdas. IIRC.
Sorry, I was looking for something else (got nerdsniped by u/hinkley's mention of Erlang's "set-theoric types" ), and didn't bookmark it. If I find it again, I'll forward the link.
Maybe someone else here knows what I'm talking about.
Wait, is there an RFC for Rust to support SOA?
This is cool, but I'm wondering
(1) Why doesn't V8, whose whole point is performance, lay out memory in an optimal way?
(2) Will Nova need to also implement all of V8's other optimizations, to see if Nova's layout makes any significant difference?
V8 could probably implement the backing object "trick" with some trouble. I'm half-hoping that Nova will show it to be worth their while and that they will eventually do it. It will be a major refactoring of the engine, however.
The heap vector "trick" is basically impossible, I believe. It wouldn't be a refactoring so much as it would be a complete rewrite of the engine. The entirety of V8 assumes it deals in pointers, and all of that would need to change to using indexes instead. I will eat my hat if they do it. Without heap vectors they can still split object data apart using pointer-keyed hash maps, so maybe they could take advantage of some of the ideas still.
V8 does offer ways to run code without optimisations, which we can use for a more apples-to-apples comparison. The most important optimisation that Nova really needs before any big performance comparisons become meaningful is property access inline caching, which requires implementing object shapes.
I'd say that once object shapes are done, then limited performance comparisons can probably be made, especially if V8's JIT is disabled.
To be fair, pointer compression is morally and memory-wise similar to indexing a vector.
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So is the whole point of this project to convince V8 to adopt a particular optimization?
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Optimal memory layout isn't something you can know in advance. The optimal way to lay out objects in memory is exactly in the order that they will be accessed, but the runtime doesn't know that until after the user program has accessed them.
And if the program accesses a set of objects in different orders at different times, there is no one optimal layout.
I did ask Lars Bak once if they spent a lot of time thinking about cache usage and organizing objects in memory to take best advantage of it and, if I recall correctly, his answer was basically "no". They definitely think about it terms of packing objects into small amounts of memory. But in a dynamically typed language like JavaScript where every property is a reference to some other object elsewhere in memory, using the cache well is just profoundly hard.
Hell, it's hard even in Java where at least you do know the set of fields any given class has.
1 it takes time and effort to make major architectural changes.
Certain design choices made for other reasons may conflict.
Isn't data-oriented design about organizing the data in a way that reflects the most common access patterns of the program? The approach of placing all numbers in a big number vector, all Arrays into a big Array vector, and so on, would be "data-oriented design" if it actually reflects the most common access patterns. So, is it the case that when you read a number you also want all those other numbers that come together with it in the cache line? Is that the case for Arrays? For DataViews? In other words, does this approach to allocating memory reflect the most common data access patterns in JavaScript programs? I'm not saying it's a bad approach, and I'm not even trying to imply that it's not DOD, I'm genuinely asking.
Edit: maybe a better question is: does it reflect the most common data access patterns of a JavaScript Engine?
Excellent question: In a theoretical sense the answer would be that we cannot know since it depends on the JavaScript being run. But: In practice I think that is indeed the case. Especially for the more common an object is, the likelier it is that it is used in conjunction with others around it. At the same time, the more important their memory placement becomes.
eg. Say you have a JS programs that has about a 100 DataViews: I'd say it's unlikely these are used in conjunction with others very often, but they're also only a small part of the program, so their placement is mostly whatever.
Now what if that number is a million instead? Now I'm betting they're mostly all created together, used together, and that their placement is critical to the program's performance.
So, I'm betting that making random memory access performance worse while guaranteeing that data created together stays together and improving linear memory performance will be an overall win.
Whether this is true data-oriented design is then in the eye of the beholder: Maybe someone will think I'm wrong, my assumptions are wrong, and I'm thus not doing things in a data-oriented way.