1. All data allocated on the JavaScript heap is placed into a type-specific vector. Numbers go into the numbers vector, strings into the strings vector, and so on.
2. All heap references are type-discriminated indexes: A heap number is identified by its discriminant value and the index to which it points to in the numbers vector.
3. Objects are also split up into object kind -specific vectors. Ordinary objects go into one vector, Arrays go into another, DataViews into yet another, and so on.
4. Unordinary objects' heap data does not contain ordinary object data but instead they contain an optional index to the ordinary objects vector.
5. Objects are aggressively split into parts to avoid common use-cases having to reading parts that are known to be unused.
If this sounds interesting, I've written a few blog posts on the internals of Nova over in our blog, you can jump into that here: https://trynova.dev/blog/what-is-the-nova-javascript-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 (...)
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.
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?
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.)
There's actually a guarantee that things are mostly going to be accessed in a linear order because player actions don't matter to the execution of the simulation. The whole simulation is run at 1/FPS intervals across the whole set of entities, regardless of player input (or lack thereof).
In an ECS the whole World is run by Systems, which operate on Components. This is why cache locality works there: when the Movement System is acting, it's operating on the Position Component for all (or at least many) Entities, so linear array access pattern is very favorable. Any other component in your cache is going to be unused until the next system runs (and then the Position Component will become the useless data in cache). That's why you'd rather have an array of Components in cache instead of an array of Entities.
This access pattern is very suitable for games because the simulation is running continuously in an infinite loop (the game loop) consisting of even more loops (the Systems running), but not so much for general purpose computation where access patterns are mostly random. (EDIT: or rather, local to each "entity".)
That is not to say that Nova's heap vectors will necessarily make sense: The two big possible stumbling blocks are 1) growing of heap vectors possibly taking too long, and 2) compacting of heap vectors during GC taking too long.
The first point basically comes down to the fact that, at present, each heap vector is truly a single Rust Vec. When it can no longer fit all the heap data into it, it needs to reallocate. Imagine you have 2 billion ordinary objects, and suddenly the ordinary objects vector needs to reallocate: This will cause horrible stalls in the VM. This can be mitigated at the cost of splitting each heap vector into chunks, but this of course comes at the cost of an extra indirection and some lack of linearity in the memory layout.
The second point is more or less a repeat of the first: Imagine you have 2 billion ordinary objects, and suddenly a single one at the beginning of the vector is removed by GC: The GC has to now move every object remaining in the vector down a step to make the vector dense again. This is something that I cannot really do anything about: I can make this less frequent by introducing a "minor GC" but eventually a "major GC" must happen and something like this can then be experienced. I can only hope that this sort of things are rare.
The alternative would be to do a "swap to tail", so the last item in the vector is moved to take the removed item's place. But that then means that linear access is no longer guaranteed. It also plays havoc on how our GC is implemented but that's kind of a side point.
Software engineering is architecture is full of trade-offs :) I'm just hoping that the ones we've made will prove to make sense.
Yes, but note this is still a different pattern of access (array of "entities"). V8 does this because it assumes that e.g. `foo.name` is very likely going to be accessed along with `foo.lastName` (which is likely the 99% case for general computing) whereas ECS assumes `foo.name` is very likely going to be accessed along with `foo2.name`, `foo3.name`, ..., `fooN.name` (which is the 99% case for videogame timestep loops).
> Software engineering is architecture is full of trade-offs :) I'm just hoping that the ones we've made will prove to make sense.
To clarify: my comment is not a criticism of Nova's design decisions. I was only trying to clarify the answer to "Why would a game benefit from ECS?" for those foreign to ECS's existential motive.
I'm sure Nova's tradeoffs make sense for some workloads and I wish you the best!
> Yes, but note this is still a different pattern of access (array of "entities").
I was referring to the `[foo, foo2, foo3]` objects themselves; V8 does use an "cache local" placement for those so you'll find them laid out in memory as:
> [foo_proto, foo_elems, foo_props, foo_name, foo_lastName, foo2_proto, foo2_elems, foo2_props, foo2_name, foo2_lastName, ...]
For what it's worth, I am interested in laying object properties out in an ECS like manner in Nova, so the properties would be laid out as `[foo.name, foo2.name, foo3.name, ...]`, but currently the properties are laid out similarly to V8, `[foo.name, foo.lastName]`. The only difference is that we do not have "in object properties".
That being said: I am obviously biased, but I do wonder if an ECS-like layout wouldn't be nearly universally beneficial. Thinking of the `foo.name` and `foo.lastName` access: If those are on the same cache line then accessing the two only reads one cache line. This is nice. But if there are more properties in the objects (and there often are), then those will pollute the cache. If you do this access once, it doesn't matter. If you do this a million times, now the cache pollution becomes a real issue: In Node.js even the optimal case would be that you read read 625,000 cache lines worth of data, only to discard 250,000 cache lines of it.
If instead we use an ECS-like layout, then accessing these two properties reads two 10100cache lines: That's bad, but on the other hand if this happens once then it won't even make a blip on the screen. If a million of these accesses are done, you could think that we'd suddenly be slow as molasses but now the ECS-like layout is probably going to help you: You're more likely reading the next `name` and `lastName` property values on each access. If you have it bad and only half of the property data you read is actually the `name` and `lastName` properties you want, then you read 750,000 cache lines and lose out to the traditional engine by 100,000 cache lines. If you get 67% "hit rate" then you break even. And that's comparing to the case where the objects only contain `name` and `lastName` and nothing more.
It of course all comes down to statistics but... I'm very interested in the potential benefits here :)
Again, thank you for your comments, I've enjoyed discussing and pondering this <3
No, my thinking is that properties would be stored into tables based on their size class: All objects that have 4-7 properties are in the same table, and all of their first property would be in the same slice, second property in another etc.
I know that ECS is treated as a silver bullet by a lot of people, but my experience is that it really only works well when the data you're working with is statically typed so that you can actually partition into arrays where each array does represent a single meaningful type.
It's not as ECS'ssy as one would hope but it's at least proven technology :D
Is there something which forces you to compact everything here? Or could you do what most GCs do and track that free entry in a free list?
Filling in empty slots would mean that likely unrelated data comes and pollutes the cache for the old data :(
I get your point but a few gaps here and there likely don't matter at all for performance. At least it's a lot better than making everything super compact all the time. Assuming you are splitting vectors at some points into chunks: In such a world you could choose to get rid of chunks with a lot of gaps and move the remaining entries into other chunks. At that point you really have a regular GC.
And the free list could be stored in the vector itself. E.g. if an entry is empty it would store the pointer to the next free entry. So all you need is a single head/tail index for each vector.
I also wonder how you handle pointers which could point into one of many vectors. E.g. a field could easily point either to an object or an array. Do you plan to pack this vector id into the 32-bit value? If so wouldn't there be a lot of dispatch like this as well:
if (index & VECTOR_ID_MASK == OBJECTS_VECTOR_ID) { return objects[index&VECTOR_INDEX_MASK]; } else { .. }
I hope it's clear what I mean with this.
A few gaps won't matter, and that to me speaks of a split between major and minor GC making sense. However, I'm not really sold on that meaning a free list making sense. For one, if I split the heap vectors into single value parts, then holding free slot data in any of them will become somewhat complicated. Hence at least for the foreseeable future I'm 100% in on the compacted heap vectors idea :) Time will tell if the aggressive compacting makes sense or not.
Our JavaScript Values are the full 8 bytes (yes, this is large and it pains me, but it does give us all integers on stack, most doubles on stack, and up to 7 bytes of string data on stack), so a field that can point to any kind of object stores a byte tag and a u32 index. I might pack this down to 1+3 bytes or so, at the cost of supporting smaller maximum number of objects in the engine. JS Value itself would still probably remain 8 bytes because of the stack data benefits.
There is indeed dynamic dispatching through match statements, though it generally happens at the specification method level. Eg. A specification method to get a property from an object will match on the tag and then dispatch to a concrete method with the index as parameter. The indexes are typed as well, so from this point on we statically know we're dealing with eg. an Array.
So there is dynamic dispatch yes, but we try to eliminate it at the earliest opportunity. We probably still have more of that than a traditional engine would have though: A traditional engine will keep the tag on the heap and there is some dynamic dispatch done based on that, but at least your data lookup isn't based on dispatch.
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.
(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?
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.
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.
If V8 copied all of Nova AND adopted Rust, I might consider laying Nova to rest and going into V8 development. But I'd probably also be really angry at V8 just taking all of Nova's good ideas and peddling them off as their own without crediting Nova. So probably I'd still keep developing Nova while stewing in my anger and inability to do anything about it :)
I hope Nova can be a spark that ignites the JavaScript world into a bit of a renaissance with some of its ideas, but the point is not to burn bright and burn out. The point is to burn bright and stay lit.
Who knows, maybe they'd even give you credit (while still taking the idea)?
Certain design choices made for other reasons may conflict.
Edit: maybe a better question is: does it reflect the most common data access patterns of a JavaScript Engine?
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.
In V8, and other production engines AFAIK, objects are variable-sized monoliths: All of their statically known data is contained in one slab. This means that for example in Node.js an empty ArrayBuffer is 96 bytes in size (IIRC).
Basically, they implement the ECMASCript specification defined inheritance chain using object-oriented class inheritance.
1. All data in V8 is allocated into one of many heap parts: Usually new data goes into a nursery space, and if it does not get GC'd it moves to the old space. Relative position of data isn't really guaranteed at this point.
2. All heap references in V8 are true pointers or, if pointer compression is used, offsets from the heap base.
3. All objects in V8 include all the data needed for them to act as objects, and all of their data is stored in a single allocation (with the exception of properties, with some exceptions). The more specialised an object is, say an ArrayBuffer, Uint8Array, or a DataView, the bigger it has to be as the specialisation requires more data to be stored.
- homogenous allocation means no alignment gaps - linear access win in garbage collection - indices smaller than pointers - type discriminated index can save some size
I haven’t verified whether those actually work out in the details. I’ll read your blog article.
Don’t bother with these comments immediately comparing it to V8 (a multi billion dollar venture). I don’t know how many creative projects they’ve done before.
You may be be interested in looking at Fabrice Bellard’s JS engine for ideas.
https://github.com/mbrock/wisp
GC is stop© which as a side effect compacts each of those arrays and improves locality. I think most lists should end up having their CDRs next to each other in memory making iteration very cache friendly. But I didn't verify any performance qualities, beyond making it efficient enough for basic use.
It also has delimited continuation control, compiles to WebAssembly, and hooks promises into the continuation system, among some other pretty cool features!
I'll definitely be taking a look at wisp, thank you very much for the link! If you ever have the time, I'd love seeing a comparison of this sort of engine design against a more traditional one.
Sorry, what is "CDR" in this context though?
There are like a dozen object types with different growing multiarrays. Words are 32 bit with 1 for GC state and 27 for index and the rest are the type tag. Ints are 28 bits. Byte arrays have their own heap too, as well as general 32 bit vectors.
On typed indexes: If we accept only about 2^24 possible index values then we could use a 32 bit integer for our Values, or at least for Objects (if we want to keep 7 bytes worth of stack data, which is pretty hard to pass on).
I love the comments comparing Nova to V8: That's what I want to aim for after all :) I'm not sure I've heard of Fabrice Bellard's JS engine, thanks, I'll take a look!
1. All performance issues arise in loops: I at least have never seen a performance problem that could be explained by a single thing happening once. It is always a particular thing happening over and over again.
2. All loops deal with collections of data, and the collections are usually created either created manually by a human being, or are created through parsing or looping many at a time.
3. A human being can manually create a collection of maybe a hundred items manually before they get bored and stop. A collection created this way may contain data from all over the place, with data access over it being nonlinear.
4. A collection created through parsing or looping will create its data in a mostly linear fashion. Accessing the data will then also be linear.
There are definitely cases where nonlinear collections exist, but these are usually either small or are created from smaller sets of linear data. eg. Think of dragging 10 lists of 1000 items to form a list of 10000 items. The entire 10000 items aren't going to be located linearly, but every 1000 items will be.
So in effect, I'm betting that most hot loops do deal with linear access over objects and that loops that work over nonlinear access are not particularly hot.
I have been following the Rust Boa project, but I think that it isn't production ready, yet. https://github.com/boa-dev/boa
A secondary aim is to have a bunch of feature flags that allows the engine to drop out support for specification parts that a particular embedder doesn't care about. That obviously fights with the "implement the entire ECMAScript specification" goal, but I just hate indexed property getters and setters with a passion and want to see them gone wherever I go.
Boa is a great project and I believe it is being used in some production systems. I've met and exchanged some ideas with the main developer, Jason Williams, and even received the greatest praise that I could imagine: Boa will (or did?) take some inspiration from Nova on its GC refactoring. Nova has also copied (with proper attribution of course) a few minor parts from Boa, like whitespace skipping code for some spec abstract operations.
I highly recommend keeping an eye out and using Boa if you have the chance.
Have you considered using NaN-boxing? Also, are the type-specific vectors compacted by the GC, or do they maintain a free list?
I answered about NaN boxing somewhere here but basically, we get quite a bit of mileage from our tagged union / enum / ADT based Value, so I don't think I'd change to NaN boxing now even if I could.
Sounds like this approach could be useful for games that embed a scripting engine. In that context it might be interesting to eventually see some benchmarks against usual suspects of game scripting like Lua.
In the short term, I am interested in one-shot script running scenarios where only very limited JavaScript type are needed. The engine already has a bunch of feature flags that can be turned off to disable things like ArrayBuffers and other "complex" features. I have a work-related system in mind where only JSON based types are needed, and garbage collection isn't really necessary: The code could be run once and afterwards the system could be wiped down to the initial state and re-run.
I also have half-a-mind to try running Nova on an STM32 board. But that could be called a hobby project within a hobby project :)
If I have `function X(a) { this.a = a; }` and then `function Y(b) { this.b = b; }` does that mean `new X(1)` and `new Y(2)` are considered objects of different kinds?
And what about creating objects with literals: are `{a: 1}` and `{b: 2}` considered objects of different kinds?
But objects that have different shapes do not end up in their own vectors, since the shape is a dynamic property.
Side note: I have a corollary on the "most objects die young" that is very much at the heart of Nova: Most objects live together. If they are created at the same time, then they're likely also used together. Hence why I don't swap items around in the heap vectors, or use a free list for allocation: It would mess up the temporal order of items in the vectors, leading to less chances at useful cache line sharing.
Without either a free list or compaction, I don’t really see how you’re collecting garbage at all.
The reasoning is that, according to my interpretation of talking with some folks working on JSC and SM, property lookup inline caching is the most important performance optimisation bar none. JIT compiling is an improvement on top, definitely, but it is not an massive step change.
Safari browser has a no-JIT mode that is fairly widely in use, and it is apparently fast enough that you don't really notice the change. Ladybird browser's LibJS has no JIT compiler, yet LibJS isn't really unbearably slow: The browser's biggest performance woes come from the browser around it and especially from having the simplest possible drawing algorithm possible.
From a "personal" experience, while the test262 compliance test set is no performance benchmark, Nova is for some reason consistently at the very top of the runtime list over at https://test262.fyi/#. This is of course partially just because we're really quick to do a controlled panic if an unsupported code path is called, and the remaining part is because the code is run so little that JIT doesn't get to kick in. Still, this meaningless number gives me some measure of hope: We're consistently 3 times as fast as V8 after all :)
So, safery properties are not being silenced: The indexes definitely _are_ Rust wise unreliable where a pointer wouldn't be so bounds checks need to be done. But memory safety is not under threat here.
This does mean that we have to take care of garbage collection ourselves, Rust will not do that for us, but that was the case anyhow since Rust doesn't have a garbage collector we could use (thank heavens). If we make mistakes here, it will lead to the JavaScript heap being corrupted from the JS code point of view but from the engine point of view the memory is still fully safe: The worst thing that can happen is a panic from out of bounds vector indexing.
We can still make mistakes, especially in the garbage collector, but that is again somewhat helped by code-sharing and coding conventions enabled by Rust ie. using destructuring in GC to make sure we don't forget any part of the heap data. (Coding conventions are not a solution, they are a mitigation at most. I _can_ write the heap GC as a map from one heap data of 'old lifetime to 'new, but that leads to worse code generation than mutating a 'static lifetime heap data :( )
Note I did not say memory safety. I said security safety.
If you refer to referential safety, so that your reference to object X still refers to X later on, then that is indeed something we "lose" because we need to implement GC ourselves. But that wouldn't actually really meaningfully change with using pointers either, as updating pointers after a move would need to be done manually as well.
Using references is right out because we cannot explain the JavaScript memory ownership model to Rust: The two are simply not compatible. There are of course safe GC crates that give you reference APIs but they do the pointer updating manually on the inside (if they have moving GC anyway), so the situation doesn't meaningfully change.
The biggest obstacle right now is that for any reasonably big benchmark, Nova will never finish as the GC cannot be run while JavaScript is running and in a big benchmark JS is always running.
I've started a large-scale work to make the engine safe for interleaved garbage collection, but it's a ton of work and will take some time unfortunately. Once it is done, I will start doing benchmarks and seeing what takes time and where.
From small-scale benchmarks I already know that our JS Value comparisons take too much time, our object property lookups are really expensive on larger objects (as it's a simple linear search), and our String interning is very slow (as it too is a dumb-as-rocks linear search).
True tail call recursion and lazy evaluation would enable truly functional JS.
The data sorting seems quite cleanly at first, but as I think more about it I don't quite get it. I guess you are saving a bit of space by segmenting by type... in another approach you might have the type on the pointer, and the pointer can point to anything, and so it's potentially a bit longer than having a type and pointer(/index) that points into a smaller portion of memory specific to that type. But enough to matter?
"No, pointers we do not want and cannot have, so the only real option is to use indexes. Indexes have a lot of benefits: They are small, work exceedingly well together with our heap vectors, enable using the same value to index into multiple heap vectors (or slices of the same heap vector), perform a form of pointer compression automatically, and offer great protection from safety vulnerabilities as reinterpreting an index as a different type changes both the type and the memory it indexes into."
That all just sounds like a pointer to me? The last case also seems like a security hole, not protection.
"Not all objects are the same: They differ in their usage and their capabilities. An object-oriented reading of JavaScript objects' capabilities and the ECMAScript specification would give you a clear and simple inheritance graph where the ordinary object is the base object class, and Arrays, DataViews, Maps, and others inherit from that. Not all objects are the same: They differ in their usage and their capabilities. An object-oriented reading of JavaScript objects' capabilities and the ECMAScript specification would give you a clear and simple inheritance graph where the ordinary object is the base object class, and Arrays, DataViews, Maps, and others inherit from that."
It seems like you are special-casing a specific set of object types (like Array), which is very justifiable. So sure.
"This is somewhat more of an aim for the future instead of current reality, but allow me to give some easy examples: The ArrayBuffer object in ECMAScript supports allocating up to 2^53 bytes of data. Most engines only allow a tad bit over 2^32 bytes but nevertheless, the fact of the matter is that you need more than 4 bytes to store that byte value. As a result, ArrayBuffer itself but also DataView and all the various TypedArray variants like Uint8Array must carry within them 8 byte data fields for byte offset, byte length, and even array length. Now ask yourself, how often do you deal with ArrayBuffers larger than 4 GiB? Not very often, obviously."
I'm guessing this is leading to a decision many languages have made about numbers and strings, where there's special types for small numbers and short strings (exposed only in the implementation). Or even more special types, where the pointers become values.
Also I can see a benefit to keeping track of "normal" Arrays and whatnot, so some of JavaScripts weird-but-not-usually-used behavior can be isolated, and normal behavior fast-tracked.
"In Nova we aim to split objects into parts to ensure that computationally unconnected parts are also stored separately in memory"
But this I don't get. If you are splitting things by type, how can you cluster them by how they are related? An object like {a: 1, b: 2} is an object with two strings and two numbers, presumably spread out over three different type-specific heaps?
A pointer is 64 bits, though carrying much less useful payload than that. A JavaScript engine only rarely deals with more than 4 GiB of memory, so a 32 bit integer would be enough to index the entire memory needed. If you turn that though into indexes, a 32 bit index can speak of 4 billion separate items: Most programs never have that many distinct heap items alive at the same time. Note that this index doesn't now really correspond to indexable memory so we're no longer bound by the 4 GiB limit.
We actually do keep the 64 bit Value though! We just use the massive amounts of data to store a lot of data on the stack, avoiding heap allocations altogether.
> That just sounds like a pointer.
A pointer points to one place and one place only: An index can points to as many places as there are "parallel vectors" associated with it. eg. Think of a table: A row index refers to as many cells as there are columns, whereas a cell pointer only identifies one cell.
> The last case also seems like a security hole, not protection.
Usually JS engines don't consider the JS-accessible contents of the JS heap itself part of the threat model: Any object in the heap is liable to be leaked by the JS code running in the engine anyway. eg. V8's object placement is fairly static and easy to exploit. The important thing for safety is to avoid type confusion which can be used to create read/write primitives to punch out of the sandbox. So; an attacker can freely read through the heap data by creating heap indexes out of thin air but they cannot use that to reinterpret one type of data as another type and then feed that back to the engine to cause it to misbehave.
> But this I don't get. If you are splitting things by type, how can you cluster them by how they are related? An object like {a: 1, b: 2} is an object with two strings and two numbers, presumably spread out over three different type-specific heaps?
Yes, this would split into the ordinary object vector, and the object property vector. If the keys were longer they'd end up in the strings vector and if the values were heap allocated doubles then they'd end up in yet another vector. Looking at it one thing at a time, it is split here and there.
That being said, this doesn't really much change from how traditional engines do it: Strings are not going to be near the objects that use them as keys, nor are heap numbers, and (added) properties also go into a separate backing store which is likely not next to the object. Worst of all, even if all of these were next to the object, they'd span multiple cache lines and wouldn't really benefit from being close to each other as they're pointer chased and thus wouldn't get much guarantees of prefetching.
When you look at multiple objects, however, then you'll see that Nova's object data is still found in those 4 vectors, whereas the traditional engine design... It may have tried it's best to keep the data together but it's probably still spread out here and there. And you're loading all unnecessary stuff like the elements pointer (for indexed properties) and any other inline properties etc. together with the properties that you actually wanted to read.
Sorry, this ended up a bit disjointed. Let me know if you have more questions! Thanks.
Fun coincidence that you started this project, I've had this exact same idea brewing for a few years, but did not bite the bullet yet :D
Have you considered using Bevy as a base ECS as they have an automatic archetype (shape) handling in the library? This was essentially my original idea, to implement a JS runtime on top of Bevy. (And over the years slap together a browser after the JS starts working)
I have not considered Bevy, no. I sort of assumed that it wouldn't be easy to adapt to (thinking that it is more of a game engine), though it might've well been an excellent option.
I _have_ thought about using Bevy as a rendering engine for some beautiful heap access animations. Imagine rows of little boxes, each row a heap vector and each box an item in it: The boxes blink as their memory is accessed. Oh what a sight it would be.
It's so gd versatile so people have done cool weird stuff with it: https://www.nikl.me/blog/2024/bevy_ecs_as_data_layer_in_lept...
I console myself with the knowledge that most engine names are unknown anyway, and even if known they are still unsearchable (looking at you two, V8 and JSC!)