The runtime performance gains does not out weight the compilation speed from
building the custom allocators, which takes about a minute to build on
slower machines.
Consume multi-line comments faster.
* Initially search for `*/`, `\r`, `\n` or `0xE2` (first byte of
irregular line breaks).
* Once a line break is found, switch to faster search which only looks
for `*/`, as it's not relevant whether there are more line breaks or
not.
Using `memchr` for the 2nd simpler search, as it's efficient for a
search with only one "needle".
Initializing `memchr::memmem::Finder` is fairly expensive, and tried
numerous ways to handle it. This is most performant way I could find.
Any ideas how to avoid re-creating it for each Lexer pass? (it can't be
a `static` as `Finder::new` is not a const function, and `lazy_static!`
is too costly)
Lex string literals as bytes, using same techniques as for identifiers.
Handling escapes could be optimized a bit more, and maybe I'll return to that, but as escapes are fairly rare, it wouldn't be the biggest gain.
I've recently switched over from hacking on a fork to working directly
on upstream, in order to be able to use Graphite.
One thing I miss now is ability to create branches and run CodSpeed on
them while developing. Compared to running benches locally, CodSpeed has
the advantage of giving you a visual history, showing how each commit
you push moves the dials.
This PR makes the benchmarks run for any branch named `bench-*`, in
order to enable this workflow on upstream, without having to open a
draft PR for every experiment.
This was a bit of a whoopsie in last batch of PRs. This assertion shouldn't be there, because all reads are now via `source.position().read()`, so this assertion says "you can only read some byte values".
Only reason it didn't blow up conformance tests is that they run in release mode.
Sorry. Please merge soon as you can and cover my shame!
This PR re-implements lexing identifiers with a fast path for the most common case - identifiers which are pure ASCII characters, using the new `Source` / `SourcePosition` APIs.
Lexing identifiers is a hot path, and accounts for the majority of the time the Lexer spends. The performance bump from this change is (if I do say so myself!) quite decent.
I've spent a lot of time tuning the implementation, which gained a further 10-15% on the Lexer benchmarks compared to my first, simpler attempt. Some of the design decisions, if they look odd, are likely motivated by gains in performance.
### Techniques
This implementation uses a few different strategies for performance:
* Search byte-by-byte, not char-by-char.
* Process batches of 32 bytes at a time to reduce bounds checks.
* Mark uncommon paths `#[cold]`.
### Structure
The implementation is built in 3 layers:
1. ASCII characters only.
2. ASCII and Unicode characters.
3. `\` escape sequences (and all the above).
`identifier_name_handler` starts at the top layer, and is optimized for consuming ASCII as fast as possible. Each "layer" is considered more uncommon than the previous, and dropping down a layer is a de-opt.
I'm assuming that 95%+ of JavaScript code does not include either Unicode characters or escapes in identifiers, so the speed of the fast path is prioritised.
That said, once a Unicode character is encountered, the next layer does expect to find further Unicode characters, rather than de-opting over and over again. If an identifier *starts* with a Unicode character, it enters the code straight on the 2nd layer, so is not penalised by going through a `#[cold]` boundary. Lexing Unicode is never going to be as fast as ASCII, but still I felt it was important not to penalise it unnecessarily, so as not to be Anglo-centric.
### ASCII search macro
The main ASCII search is implemented as a macro. I found that, for reasons I don't understand, it's significantly faster to have all the code in a single function, even compared to multiple functions marked `#[inline]` or `#[inline(always)]`. The fastest implementation also requires some code to be repeated twice, which is nicer to do with a macro.
This macro, and the `ByteMatchTable` types that go with it, are designed to be re-usable. Next step will be to apply them for whitespace and strings, which should be fairly simple.
Searching in batches of 32 bytes is also designed to be forward-compatible with SIMD.
### Bye bye `AutoCow`
`AutoCow` is removed. Instead, a string-builder is only created if it's needed, when a `\` escape is first encountered. The string builder is also more efficient than `AutoCow` was, as it copies bytes in chunks, rather than 1-by-1.
This won't make much difference for identifiers, as escapes are so rare anyway, but this same technique can be used for strings, where they're more common.
