With higher saturation the performance delta returns to normal. I do think specs could be more competitive for performance from where it stand. So it still has the advantage of being a Structure-of-Arrays rather then an Array-of-Structures. It seems like an obvious feature that could run when the system has idle time, otherwise the only way to order it would be to remove all the components and reinsert them. There are new ranks associated with most Legion Blacksmithing Recipes. How in that is that possible? If you are not used to the penalties of adding or removing components it will be a surprise how terrible the performance can be. As they are structured completely differently the areas that will hurt performance are different between the two implementations. Even if the table has its own primary means of knowing (think a HashTable). Just how bad is it? Specs does have BTreeMaps and Vec based storage, but one is slow, and the other wastes space on unused keys. Iteration speeds are really important and it sacrifices quite a bit to actually maximize iteration performance. With Legion Tailor, your skill goes from 1-800 and you do not need to return to train higher ranks. Each component is stored in a Storage that contains a collection of like elements. Keeps systems all running in parallel without the worry of two systems fighting over the same components. I microbenchmarked just the creation of entities and ended up trying a few different techniques. Important takeaway from this little intro, Legion doesn’t require any the definition of a Storage type like specs did. The key here is that we are always pushing the data values onto the end of the data array. After a world is created we need to build a Dispatcher which is used as the puppet master of this whole operation. I suspect there are some gains that can still be squeezed out of this data structure. A system works over one or more components and does something with them. HashMap performance also regresses as the dataset size gets large. Legion on the other hand provides an interface called par_for_each which is similar but hides the details of the Rayon implementation. All benchmarking was done on a Windows 10 using a AMD Threadripper 3960x with clocks fixed at 3.8Ghz for consistency reasons. Before I get to my conclusions I wanted to mention some of the strange performance weirdness I had seen while evaluating these libraries. With some of the downsides discussed, what is the main advantages of Legion’s archetype technique? I don’t think there is a miracle that could make its design faster than Legions for iteration speed. I added a few other entries vec-aos and vec-soa are array-of-structs and struct-of-array respectively. One of the strange things about Legion is that it does have an expensive setup overhead. Its iteration speeds seemed fast when it was introduced, but the competition was largely folk writing an ECS for the sake of getting their games design right not to wow people with performance. If you are re-learning Tailoring, you can pick up Forgotten Patterns of the Broken Isles to learn all the Legion recipes you previously had from quests. The question you should ask is “Does that matter to me?”. In Legion, this new entity is written by it’s archetype into a single table that contains entities which identical archetypes. Very cool! There is a way for us to work around to get an idea of how fast legion could be. Once again these are worst case performance. This has some neat advantages! When an entity is written in Specs, each component gets written to a different storage column. On the surface things look pretty similar. All components get’s treated equally even if they are more common than other components. Components are optional, entities can contain all of them, none of them, or any unique combination of components. Iteration performance should be similar to iteration over a vector, since internally it is. The performance delta is not small either, at peak its almost ~4 times faster. Here is a quick benchmark of what component density looks like. To demonstrate how bad this can be, I did a quick benchmark where I created entities with an even distribution of unique entity combinations. We can manually shard the data ourselves. Legion is also slow in places. Its performance regresses as the dataset gets more populated. This trait was a clever way that specs can use the compiler type system to keep track of and know statically the type of table. An Archetype is a collection of similar entities, similar defined by sharing the same set of components. Always up to date with the latest patch (9.0.1). Specs and Legion are not too different to the API user. Meaning components are pulled into the cached that won’t be read. I don’t imagine there will be hundreds of archetypes, because the API discourages (via performance) adding or removing components ad-hoc from entities. Meaning an Entity with Position and Velocity is a different archetype than one that just has Position or Velocity. With a warm cache both implementations start with similar overhead but specs quickly dominates being at best ~12 times faster. I wanted to show both libraries in the best light I could, I’d rather people be discussing their options on data structures then their opinions on my benchmarks. This is just iterating over a set of entities, Legion should be faster. Component storage in specs doesn’t perform the way my intuitive expectations would have been. Legion is a new upcoming ECS that uses something called an archetype. The magic of Legion is Archetypes. This looks something like this. With a single component legion is more than 3 times faster than specs. This is a little bit of an aside, but I can’t leave a mystery as to why DenseVec and Vec performed so closely. The first reason being that DenseVec internally has a lookup buffer that maps the entity index to the real index, this is a u32. Optimizations are the process of removing work, and that’s a huge amount of work removed. Always up to date with the latest patch (8.3.7). I like this API. Think velocity & position, or transform and material. In specs adding or removing a component from an entity is an O(1) operation, it’s just a matter of adding or removing a value from a table. In this example it modifies the position using the velocity. Legion requires copying the entire entity from one table to another table, adding or removing the entity in the process. You now unlocked the other Imbued patterns in which some are sold to you and others are achieved by completing a quest for the NPC holding the pattern. In general iterating over an array is kinda like the speed-of-light of iteration performance, assuming you are using all the values you should be bandwidth limited. The benchmark was designed to show both implementations in their best light for comparative reasons. If you only have a handful of items the time it takes to setup the iterator easily dominate the overhead from iteration over said dataset. Full disclosure, I worked on specs. This is a little annoying as there are lots of nice patterns that Rayon has supplied that you can chain with your iterator. I largely don’t see any major differences, both implementations do terrible compared to raw vectors with a cold cache, but the gap gradually declines as the dataset increases in size and they see the gains of pre-caching.

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