e4b13b2aa6
Kick CPUs in the dispatch path only when needed (typically when tasks are bounced to other CPUs). Moreover, avoid to consume all the tasks dispatched at once. This seems to reduce the BPF overhead (according to bpftop), going from ~10% CPU usage down to ~6% CPU usage of rustland_dispatch() on an over commissioned system, without introducing any measureable performance regression. Tested-by: SoulHarsh007 <harsh.peshwani@outlook.com> Signed-off-by: Andrea Righi <andrea.righi@canonical.com> |
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assets | ||
src | ||
.gitignore | ||
bindings.h | ||
bpf_h | ||
build.rs | ||
Cargo.toml | ||
LICENSE | ||
meson.build | ||
README.md |
Framework to implement sched_ext schedulers running in user-space
sched_ext is a Linux kernel feature which enables implementing kernel thread schedulers in BPF and dynamically loading them.
This crate provides a generic layer that can be used to implement sched-ext schedulers that run in user-space.
It provides a generic BPF abstraction that is completely agnostic of the particular scheduling policy implemented in user-space.
Developers can use such abstraction to implement schedulers using pure Rust code, without having to deal with any internal kernel / BPF internal details.
API
The main BPF interface is provided by the BpfScheduler
struct. When this
object is initialized it will take care of registering and initializing the BPF
component.
The scheduler then can use BpfScheduler
instance to receive tasks (in the
form of QueuedTask
objects) and dispatch tasks (in the form of DispatchedTask
objects), using respectively the methods dequeue_task()
and dispatch_task()
.
Example usage (FIFO scheduler):
struct Scheduler<'a> {
bpf: BpfScheduler<'a>,
}
impl<'a> Scheduler<'a> {
fn init() -> Result<Self> {
let topo = Topology::new().expect("Failed to build host topology");
let bpf = BpfScheduler::init(5000, topo.nr_cpus() as i32, false, false, false)?;
Ok(Self { bpf })
}
fn schedule(&mut self) {
match self.bpf.dequeue_task() {
Ok(Some(task)) => {
// task.cpu < 0 is used to to notify an exiting task, in this
// case we can simply ignore it.
if task.cpu >= 0 {
let _ = self.bpf.dispatch_task(&DispatchedTask {
pid: task.pid,
cpu: task.cpu,
cpumask_cnt: task.cpumask_cnt,
slice_ns: 0,
});
}
}
Ok(None) => {
// Notify the BPF component that all tasks have been dispatched.
self.bpf.update_tasks(Some(0), Some(0))?
break;
}
Err(_) => {
break;
}
}
}
Moreover, a CPU ownership map (that keeps track of which PID runs on which CPU)
can be accessed using the method get_cpu_pid()
. This also allows to keep
track of the idle and busy CPUs, with the corresponding PIDs associated to
them.
BPF counters and statistics can be accessed using the methods nr_*_mut()
, in
particular nr_queued_mut()
and nr_scheduled_mut()
can be updated to notify
the BPF component if the user-space scheduler has still some pending work to do
or not.
Lastly, the methods exited()
and shutdown_and_report()
can be used
respectively to test whether the BPF component exited, and to shutdown and
report the exit message.