This change tunes ahead-of-time codegening according to the amount of
concurrency available, rather than according to the number of CPUs on
the system. This can lower memory usage by reducing the number of
compiled LLVM modules in memory at once, particularly across several
rustc instances.
Previously, each rustc instance would assume that it should codegen
ahead of time to meet the demand of number-of-CPUs workers. But often, a
rustc instance doesn't have nearly that much concurrency available to
it, because the concurrency availability is split, via the jobserver,
across all active rustc instances spawned by the driving cargo process,
and is further limited by the `-j` flag argument. Therefore, each rustc
might have had several times the number of LLVM modules in memory than
it really needed to meet demand. If the modules were large, the effect
on memory usage would be noticeable.
With this change, the required amount of ahead-of-time codegen scales up
with the actual number of workers running within a rustc instance. Note
that the number of workers running can be less than the actual
concurrency available to a rustc instance. However, if more concurrency
is actually available, workers are spun up quickly as job tokens are
acquired, and the ahead-of-time codegen scales up quickly as well.
For better throughput during parallel processing by LLVM, we used to sort
CGUs largest to smallest. This would lead to better thread utilization
by, for example, preventing a large CGU from being processed last and
having only one LLVM thread working while the rest remained idle.
However, this strategy would lead to high memory usage, as it meant the
LLVM-IR for all of the largest CGUs would be resident in memory at once.
Instead, we can compromise by ordering CGUs such that the largest and
smallest are first, second largest and smallest are next, etc. If there
are large size variations, this can reduce memory usage significantly.
bjorn3