This undoes a previous change to unify them, and I think at my advice.
=[ Sorry about that, I think I was just wrong.
Specifically, I think I had suggested that it would be more efficient to
have a single shared hashtable of strings. The more I look at profiles
of the toolchain, the less likely that seems. Specifically for
identifiers and string literals it seems especially problematic.
Using a single, joint hashtable is likely a good idea when all of the
different querying code paths are equally likely, the strings follow the
same distribution of sizes, and either there is no clustering of access
to different sets of strings or none of the sets are meaningfully small
enough to fit into a lower level of resident cache.
I think essentially none of these predicates actually hold for
identifiers vs. string literals:
- Identifiers are *much* more hot
- They have wildly different size distributions.
- The access patterns are very clustered
Sorry for the misleading advice on that one.
While splitting them, I've worked to simplify the code a bit by building
a way to have the `StringRef` holding canonical value stores not require
specializations, and so we get a pretty large code cleanup in the
process here.
This works to leverage the capabilities of the hashtable as much as
possible, for example using the key context in the value stores.
However, there may still be opportunities to refactor more deeply and
use the functionality even better. Hopefully this is at least
a reasonable start and gets us a clean baseline.
On an Arm M1, this is a 15% improvement on my large lexing stress test,
but ends up a wash on my x86-64 server. This is a smaller benefit than
I expected, and it's because we're using a set-of-IDs and looking up
values with a key context for things like identifiers. This pattern has
a surprising tradeoff. The new hashtable uses significantly less memory,
a 10% peak RSS reduction just from the hashtable change. But indirecting
through the vector of values makes growing the hashtable dramatically
less cache-friendly: it causes growth to randomly access every key when
rehashing. On x86, everything gained by the faster hashtable is lost in
even slower growth. And even on Arm, this eats into the benefits.
But I have a plan to tweak how identifiers specifically work to avoid
most of the growth, and so I suspect this is the right tradeoff on the
whole. It gives us significant working set size reduction and we can
likely avoid the regressed operation (growth with rehash) in most cases
by clever reserving and if necessary by adding a hash caching layer to
the table infrastructure.
---------
Co-authored-by: Jon Ross-Perkins <jperkins@google.com>
Build a `Generic` object for generic functions. This object tracks the
generic parameters that are in scope for the generic entity. Eventually
it will track other information about the generic too.
Add basic SemIR formatting support for generic functions.
Following up on discussion from #3948, doing a general rename of
"enclosing scope" to "parent scope" (and "enclosing scopes" to "ancestor
scopes"). The intent is to improve understandability and collide less
with C++ terminology for "enclosing scope". Note this changes most uses
of "enclosing", but leaves behind a few like "enclosing function" and
"enclosing block".
Note this does create some "parent class" mentions for "adapt" and "var"
(the class they're within), which is maybe unfortunate, but we'd
probably say "base class" if we meant inheritance so perhaps that's
okay. Along the same lines, these are the only `parent_class` uses I see
now, and we do have a few `base_class`.
Use a level comparison during substitution to determine whether we're
substituting a particular binding. Evaluate symbolic bindings with the
same name and the same level to the same symbolic constant, for example
across redeclarations of a generic function.
In parse, form a list of methods that are defined inline, tracking where
they start, where they end, and which other inline methods are nested
within them.
In check, when we reach an inline method body, skip it and add it to a
worklist to be processed later. We also track when we reach the start
and end of a context in which inline method bodies are deferred, so that
we know when to replay the bodies.
When suspending a function definition to be processed later, the
`DeclNameStack` entry is moved to separate storage, including popping
the corresponding scopes from the scope stack and removing the
corresponding lexical names from lexical lookup. Later, when we return
to the function and parse its definition, the `DeclNameStack` entry is
restored. The same is done when we reach the end of a nested context
that can have inline methods, so that we can reenter the nested scope
before processing its members.
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Co-authored-by: Jon Ross-Perkins <jperkins@google.com>
Chandler Carruth
Richard Smith