This PR implements a worked thread pool. It uses a fixed amount of threads in a pool and allows scheduling tasks
that can be run on threads (and then waited for). It satisfies the following use cases:
* HTML5 thread count is fixed (and similar restrictions are known in consoles) so we need to reuse threads.
* Thread spawning is slow in general, so reusing threads is faster anyway.
* This implementation supports recursive waiting for tasks, making it less prone to deadlocks if threads from the pool also run tasks.
After this is approved and merged, subsequent PRs will be needed to replace the ThreadWorkPool usage by this class.
Clean up and do fixes to hash functions and newly introduced murmur3 hashes in #61934
* Clean up usage of murmur3
* Fixed usages of binary murmur3 on floats (this is invalid)
* Changed DJB2 to use xor (which seems to be better)
* Map is unnecessary and inefficient in almost every case.
* Replaced by the new HashMap.
* Renamed Map to RBMap and Set to RBSet for cases that still make sense
(order matters) but use is discouraged.
There were very few cases where replacing by HashMap was undesired because
keeping the key order was intended.
I tried to keep those (as RBMap) as much as possible, but might have missed
some. Review appreciated!
Adds a new, cleaned up, HashMap implementation.
* Uses Robin Hood Hashing (https://en.wikipedia.org/wiki/Hash_table#Robin_Hood_hashing).
* Keeps elements in a double linked list for simpler, ordered, iteration.
* Allows keeping iterators for later use in removal (Unlike Map<>, it does not do much
for performance vs keeping the key, but helps replace old code).
* Uses a more modern C++ iterator API, deprecates the old one.
* Supports custom allocator (in case there is a wish to use a paged one).
This class aims to unify all the associative template usage and replace it by this one:
* Map<> (whereas key order does not matter, which is 99% of cases)
* HashMap<>
* OrderedHashMap<>
* OAHashMap<>
* Changed syntax usage for RD::Uniform to create faster with a single RID
* Converted render pass setup to use this in clustered renderer to test.
This is the first step into creating a proper uniform set cache system to simplify large parts of the codebase.
The same is done for `Vector` (and thus `Packed*Array`).
`begin` and `end` can now take any value and will be clamped to
`[-size(), size()]`. Negative values are a shorthand for indexing the array
from the last element upward.
`end` is given a default `INT_MAX` value (which will be clamped to `size()`)
so that the `end` parameter can be omitted to go from `begin` to the max size
of the array.
This makes `slice` works similarly to numpy's and JavaScript's.
Each file in Godot has had multiple contributors who co-authored it over the
years, and the information of who was the original person to create that file
is not very relevant, especially when used so inconsistently.
`git blame` is a much better way to know who initially authored or later
modified a given chunk of code, and most IDEs now have good integration to
show this information.
We prefer to prevent using chained assignment (`T a = b = c = T();`) as this
can lead to confusing code and subtle bugs.
According to https://en.wikipedia.org/wiki/Assignment_operator_(C%2B%2B), C++
allows any arbitrary return type, so this is standard compliant.
This could be re-assessed if/when we have an actual need for a behavior more
akin to that of the C++ STL, for now this PR simply changes a handful of
cases which were inconsistent with the rest of the codebase (`void` return
type was already the most common case prior to this commit).
Some platforms (*cough* web *cough*) have hard limits on the number of
threads that can be spawned.
Currently, ThreadPoolWork (mostly used in rendering/physics servers)
will spawn as many threads as CPUs available causing exception on
machines with high CPU count.
This commit adds a new overridable method to OS that returns the default
thread pool size (still the CPU count by default), and overrides it for
the JavaScript platform so it always allocate only one thread.
We can likely improve the whole ThreadPoolWork in the future to always
allocate X amount of threads, and assign jobs to them on the fly, but
that will require some more architectural changes.
reduz
Pedro J. Estébanez
bruvzg
Rémi Verschelde
Lyuma
Hendrik Brucker
Nathan Franke
Haoyu Qiu
AndreaCatania
Bartłomiej T. Listwon
Mark Riedesel
Rémi Verschelde
mashumafi
kobewi
lawnjelly
Anilforextra
Nathan Franke
Lightning_A
Fabio Alessandrelli
Ibrahn Sahir
Emmanuel Leblond
Kirill Diduk