... so that it can be reused on current thread for subsequent
Scheduler instantiations (e.g. block_on) without the need to
reallocate internal data structures.
This commit improves threadshare timers predictability
by better making use of current time slice.
Added a dedicate timer BTreeMap for after timers (those
that are guaranteed to fire no sooner than the expected
instant) so as to avoid previous workaround which added
half the max throttling duration. These timers can now
be checked against the reactor processing instant.
Oneshot timers only need to be polled as `Future`s when
intervals are `Stream`s. This also reduces the size for
oneshot timers and make user call `next` on intervals.
Intervals can also implement `FusedStream`, which can help
when used in features such as `select!`.
Also drop the `time` module, which was kepts for
compatibility when the `executor` was migrated from tokio
based to smol-like.
Add a `tuning` feature which adds counters that help with performance
evaluation. The only counter added so far accumulates the duration a
Scheduler has been parked, which is pretty accurate an indication of
CPU usage of the Scheduler.
Using callgrind with the standalone test showed opportunities for
improvements for sub tasks addition and drain.
All sub task additions were performed after making sure we were
operating on a Context Task. The Context and Task were checked
again when adding the sub task.
Draining sub tasks was perfomed in a loop on every call places,
checking whether there were remaining sub tasks first. This
commit implements the loop and checks directly in
`executor::Task::drain_subtasks`, saving one `Mutex` lock and
one `thread_local` access per iteration when there are sub
tasks to drain.
The `PadSink` functions wrapper were performing redundant checks
on the `Context` presence and were adding the delayed Future only
when there were already sub tasks.
The I/O handle was dropped prior to removing it from the reactor,
which caused `Poller::delete` to fail due to an invalid file
descriptor. This used to happen silently unless the same fd was
added again, e.g. by changing states in the pipeline as follow:
Null -> Playing -> Null -> Playing.
In which case `Poller::add` failed due to an already existing file.
This commit makes sure the fd is removed from the reactor prior to
dropping the handle. In order to achieve this, a new task is spawned
on the `Context` on which the I/O was originally registered, allowing
it to access the proper `Reactor`. The I/O can then safely be dropped.
Because the I/O handle is moved to the spawned future, this solution
requires adding the `Send + 'static` bounds to the I/O handle used
within the `Async` wrapper. This appears not too restrictive for
existing implementations though. Other attempts were considered,
but they would cause deadlocks.
This new approach also solves a potential race condition where a
fd could be re-registered in a `Reactor` before it was removed.
When the iteration loop is throttling, the call to `abort` on the
`loop_abort_handle` returns immediately, but the actual `Future`
for the iteration loop is aborted only when the scheduler throttling
completes. State transitions which requires the loop to be aborted &
which are serialized at the pipeline level can incur long delays.
This commit makes sure the Task Context's scheduler is awaken as soon
as the task loop is aborted.
Previous version relied on a plain loop / match / break because
I experimented different strategies. The while variant is better
for the final solution.
The function `enter` is executed in a blocking way from the caller's
point of view. This means that we can guaranty that the provided
function and its output will outlive the underlying Scheduler Task
execution. This requires an unsafe call to
`async_task::spawn_unchecked`. See:
https://docs.rs/async-task/latest/async_task/fn.spawn_unchecked.html
The threadshare executor was based on a modified version of tokio
which implemented the throttling strategy in the BasicScheduler.
Upstream tokio codebase has significantly diverged from what it
was when the throttling strategy was implemented making it hard
to follow. This means that we can hardly get updates from the
upstream project and when we cherry pick fixes, we can't reflect
the state of the project on our fork's version. As a consequence,
tools such as cargo-deny can't check for RUSTSEC fixes in our fork.
The smol ecosystem makes it quite easy to implement and maintain
a custom async executor. This MR imports the smol parts that
need modifications to comply with the threadshare model and implements
a throttling executor in place of the tokio fork.
Networking tokio specific types are replaced with Async wrappers
in the spirit of [smol-rs/async-io]. Note however that the Async
wrappers needed modifications in order to use the per thread
Reactor model. This means that higher level upstream networking
crates such as [async-net] can not be used with our Async
implementation.
Based on the example benchmark with ts-udpsrc, performances seem on par
with what we achieved using the tokio fork.
Fixes https://gitlab.freedesktop.org/gstreamer/gst-plugins-rs/-/issues/118
Related to https://gitlab.freedesktop.org/gstreamer/gst-plugins-rs/-/merge_requests/604