Most versions are through `pre-commit autoupdate --freeze`, clang-format
was manually updated to the latest at
https://github.com/ssciwr/clang-format-wheel
My read of the style changes here are that they seem fine, none of them
look like regressions (which has caused me to delay/adjust updates in
the past).
Echoing what was added in #5608, updating existing uses. Unfortunately
there's divergent behavior for operators versus constructors, so keeping
the nolint on those.
Trying to make repeated `std::same_as` easier to write. Calling it
"concepts.h" because I figure we'll maybe have a couple more things like
this.
Was looking at this because I may add a couple more similar constructs.
Also makes the style guide explicitly comment on void, but this was the
intent IIRC because it matches Carbon's `-> ()` (and "always" versus
"except for void", which we definitely went back and forth on).
Includes adjusting function pointers, which I definitely forget this
syntax works sometimes.
Excludes utils/tree_sitter/src/scanner.c because it claims to be C, but
really we should probably fix that to be cpp.
This switches `DCHECK` and `FATAL` as well.
The goal is to reduce the code size impact of these assertions so that
we can keep more of them enabled. Currently, the largest cost I see from
`CHECK` is not the actual check or the cold code itself, but actually
the failure to inline trivial functions due to the presence of the cold
code. This means that our goal isn't to reduce apparent code size in the
final binary but the LLVM IR cost assessed for these routines in the
inliner, which closely correlates with code size but is a bit different.
As discussed in #4283, experimentation shows that a single function call
with a minimal number of arguments is the lowest cost model for these.
This is easily achieved with a format-string API that internally uses
`llvm::formatv`. This PR is essentially the `CHECK` version of #4283.
However, the check macros are substantially harder to make work with
both format strings and streaming because they also take a condition.
Also, unexpectedly, I was very successful at devising a regular
expression based automated rewrite from the streaming to the format
string form with only low 10s of manual fixes. This includes compacting
strings broken up across lines, etc. Given how well that went, I've
prepared this PR which just directly switches to the format string API
and migrate everything to use it.
One nice side-effect is that the format string approach ends up greatly
simplifying the implementation here as well.
This is ... *shockingly* effective. Parsing speeds up by more than 3%
with just this change. And checking speeds up by **8%** with this change
alone:
```
BM_CompileAPIFileDenseDecls<Phase::Parse>/256 86.3µs ± 1% 82.9µs ± 1% -3.94% (p=0.000 n=17+19)
BM_CompileAPIFileDenseDecls<Phase::Parse>/1024 431µs ± 1% 415µs ± 1% -3.76% (p=0.000 n=18+19)
BM_CompileAPIFileDenseDecls<Phase::Parse>/4096 1.77ms ± 1% 1.71ms ± 1% -3.18% (p=0.000 n=18+19)
BM_CompileAPIFileDenseDecls<Phase::Parse>/16384 7.44ms ± 1% 7.17ms ± 2% -3.56% (p=0.000 n=18+20)
BM_CompileAPIFileDenseDecls<Phase::Parse>/65536 30.7ms ± 1% 29.7ms ± 1% -3.15% (p=0.000 n=18+20)
BM_CompileAPIFileDenseDecls<Phase::Parse>/262144 131ms ± 1% 127ms ± 1% -2.81% (p=0.000 n=18+18)
BM_CompileAPIFileDenseDecls<Phase::Check>/256 878µs ± 2% 800µs ± 1% -8.91% (p=0.000 n=19+20)
BM_CompileAPIFileDenseDecls<Phase::Check>/1024 1.88ms ± 2% 1.72ms ± 1% -8.56% (p=0.000 n=19+20)
BM_CompileAPIFileDenseDecls<Phase::Check>/4096 5.78ms ± 2% 5.28ms ± 1% -8.70% (p=0.000 n=20+18)
BM_CompileAPIFileDenseDecls<Phase::Check>/16384 21.9ms ± 1% 20.1ms ± 1% -8.02% (p=0.000 n=18+20)
BM_CompileAPIFileDenseDecls<Phase::Check>/65536 90.4ms ± 2% 83.1ms ± 1% -8.04% (p=0.000 n=19+20)
BM_CompileAPIFileDenseDecls<Phase::Check>/262144 381ms ± 2% 352ms ± 1% -7.79% (p=0.000 n=19+19)
```
---------
Co-authored-by: Richard Smith <richard@metafoo.co.uk>
Co-authored-by: josh11b <15258583+josh11b@users.noreply.github.com>
This injects a customization point for hashtable-specific equality
testing that the key context uses by default. While this is rarely
needed, there are LLVM types where it is necessary and it seems a good
general tool to have to avoid unnecessary complexity from custom key
contexts when a simple customization of equality is all that is
required.
This also adds a CRTP mixin for implementing a common pattern of key
contexts where the context provides translation of some key types into
another type, potentially using state. Rather than having to implement
the entire key context API, code can derive from this template and
simply provide a set of overloads for the types it wants to translate.
Any key types used which can be passed to one of those overloads will
get translated before following the same logic as the default key
context. While this updates the only usage so far of this pattern, a
subsequent PR will add several more users making the pattern worth
abstracting here.
This lets copy and move assignment work. While it's a bit suboptimal to
do assignment with these tables, it still seems like an unreasonable
burden to not allow the basics to work. Even the toolchain ended up
doing this in a few places.
---------
Co-authored-by: Richard Smith <richard@metafoo.co.uk>
This adds two different growth APIs. This is instead of the more
conventional STL `reserve` method. One allows users that aren't trying
to grow in anticipation of an *exact* count of insertions, but generally
trying to size the table to the correct ballpark with a power-of-two
estimate.
The other API allows pre-growing to allow a specific number of
insertions to be performed without further growth. This API takes the
maximum load factor and other implementation details into account.
---------
Co-authored-by: josh11b <15258583+josh11b@users.noreply.github.com>
Previously we just looked at the raw count of probed keys. Now, we
compute the average and max of both the probe _distance_ measured in the
number of _groups_ probed, and the number of probe _compares_ measured
in the compares required _before_ finding the matching entry.
This lets us understand the relative impact of probe-distance vs. tag
collisions on a given set of benchmark keys. Some of this is motivated
by considering additional optimization techniques similar to those used
in Boost's table and the F14 table from Facebook/Meta.
---------
Co-authored-by: Richard Smith <richard@metafoo.co.uk>
The hash table design is heavily based on Abseil's ["Swiss
Tables"][swiss-tables] design. It uses an array of bytes storing
metadata about each entry and an array of entries where each is a pair
of key and value. The metadata byte consists of 7-bits of hash of the
key (distinct from the bits used to index the table), and one bit
indicating the presence of a special entry -- either empty or deleted.
[swiss-tables]: https://abseil.io/about/design/swisstables
There are a large range of optimizations and other nuanced aspects of
this hash table design and implementation, a good point to understand
that context is `raw_hashtable.h` which has an overview of the design
and references to various other files for relevant details.
---------
Co-authored-by: josh11b <15258583+josh11b@users.noreply.github.com>
Jon Ross-Perkins
Geoff Romer
