scx_rusty has logic in the scheduler to inspect the host to
automatically build scheduling domains across every L3 cache. This would
be generically useful for many different types of schedulers, so let's
add it to the scx_utils crate so it can be used by others.
Signed-off-by: David Vernet <void@manifault.com>
The buffer used to store struct queued_task_ctx items fetched from the
BPF ring buffer needs to be aligned to the architecture register size,
otherwise we may hit misaligned pointer dereference issues, such as:
thread 'main' panicked at src/bpf.rs:162:43:
misaligned pointer dereference: address must be a multiple of 0x8 but is 0x56516a51e004
note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace
Prevent this by making sure the buffer is always aligned to 64-bits.
Fixes: 93dc615 ("scx_rustland: use a ring buffer for queued tasks")
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
Switch from a BPF_MAP_TYPE_QUEUE to a BPF_MAP_TYPE_RINGBUF to store the
tasks that need to be processed by the user-space scheduler.
A ring buffer allows to save a lot of memory copies and syscalls, since
the memory is directly shared between the BPF and the user-space
components.
Performance profile before this change:
2.44% [kernel] [k] __memset
2.19% [kernel] [k] __sys_bpf
1.59% [kernel] [k] __kmem_cache_alloc_node
1.00% [kernel] [k] _copy_from_user
After this change:
1.42% [kernel] [k] __memset
0.14% [kernel] [k] __sys_bpf
0.10% [kernel] [k] __kmem_cache_alloc_node
0.07% [kernel] [k] _copy_from_user
Both the overhead of sys_bpf() and copy_from_user() are reduced by a
factor of ~15x now (only the dispatch path is using sys_bpf() now).
NOTE: despite being very effective, the current implementation is a bit
of a hack. This is because the present ring buffer API exclusively
permits consumption in a greedy manner, where multiple items can be
consumed simultaneously. However, libbpf-rs does not provide precise
information regarding the exact number of items consumed. By utilizing a
more refined libbpf-rs API [1] we may be able to improve this code a
bit.
Moreover, libbpf-rs doesn't provide an API for the user_ring_buffer, so
at the moment there's not a trivial way to apply the same change to the
dispatched tasks.
However, just with this change applied, the overhead of sys_bpf() and
copy_from_user() is already minimal, so we won't get much benefits by
changing the dispatch path to use a BPF ring buffer.
[1] https://github.com/libbpf/libbpf-rs/pull/680
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
Instead of using a BPF_MAP_TYPE_ARRAY to store which tasks are running
on which CPU we can simply use a global array, mapped in the user-space
address space.
In this way we can avoid a lot of memory copies and call to sys_bpf(),
significantly reducing the scheduler's overhead.
Keep in mind that we don't need to be 100% correct while accessing this
information, so we can accept some fuzziness in order to significantly
reduce the scheduler's overhead.
Performance profile before this change:
5.52% [kernel] [k] __sys_bpf
4.84% [kernel] [k] __kmem_cache_alloc_node
4.71% [kernel] [k] map_lookup_elem
4.10% [kernel] [k] _copy_from_user
3.51% [kernel] [k] bpf_map_copy_value
3.12% [kernel] [k] check_heap_object
After this change:
2.20% [kernel] [k] __sys_bpf
1.91% [kernel] [k] map_lookup_and_delete_elem
1.60% [kernel] [k] __kmem_cache_alloc_node
1.10% [kernel] [k] _copy_from_user
0.12% [kernel] [k] check_heap_object
n/a bpf_map_copy_value
n/a map_lookup_elem
With this change we can reduce the overhead of sys_bpf() by ~2x and
the overhead of copy_from_user() by ~4x.
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
Currently, the primary bottleneck in scx_rustland lies within its custom
memory allocator, which is used to prevent page faults in the user-space
scheduler.
This is pretty evident looking at perf top:
39.95% scx_rustland [.] <scx_rustland::bpf::alloc::RustLandAllocator as core::alloc::global::GlobalAlloc>::alloc
3.41% [kernel] [k] _copy_from_user
3.20% [kernel] [k] __kmem_cache_alloc_node
2.59% [kernel] [k] __sys_bpf
2.30% [kernel] [k] __kmem_cache_free
1.48% libc.so.6 [.] syscall
1.45% [kernel] [k] __virt_addr_valid
1.42% scx_rustland [.] <scx_rustland::bpf::alloc::RustLandAllocator as core::alloc::global::GlobalAlloc>::dealloc
1.31% [kernel] [k] _copy_to_user
1.23% [kernel] [k] entry_SYSRETQ_unsafe_stack
However, there's no need to reinvent the wheel here, rather than relying
on an overly simplistic and inefficient allocator, we can rely on
buddy-alloc [1], which is also capable of operating on a preallocated
memory buffer.
After switching to buddy-alloc, the performance profile under the same
workload conditions looks like the following:
6.01% [kernel] [k] _copy_from_user
5.21% [kernel] [k] __kmem_cache_alloc_node
4.45% [kernel] [k] __sys_bpf
3.80% [kernel] [k] __kmem_cache_free
2.79% libc.so.6 [.] syscall
2.34% [kernel] [k] __virt_addr_valid
2.26% [kernel] [k] _copy_to_user
2.14% [kernel] [k] __check_heap_object
2.10% [kernel] [k] __check_object_size.part.0
2.02% [kernel] [k] entry_SYSRETQ_unsafe_stack
With this change in place, the primary overhead is now moved to the
bpf() syscall and the copies between kernel and user-space (this could
potentially be optimized in the future using BPF ring buffers, instead
of BPF FIFO queues).
A better focus at the allocator overhead before vs after this change:
[before]
39.95% scx_rustland [.] core::alloc::global::GlobalAlloc>::alloc
1.42% scx_rustland [.] core::alloc::global::GlobalAlloc>::dealloc
[after]
1.50% scx_rustland [.] core::alloc::global::GlobalAlloc>::alloc
0.76% scx_rustland [.] core::alloc::global::GlobalAlloc>::dealloc
[1] https://crates.io/crates/buddy-alloc
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
In order to prevent duplicate PIDs in the TaskTree (BTreeSet), we
perform an O(N) search each time we add an item, to verify whether the
PID already exists or not.
Under heavy stress test conditions the O(N) complexity can have a
potential impact on the overall performance.
To mitigate this, introduce a HashMap that can be used to retrieve tasks
by PID typically with a O(1) complexity. This could potentially degrade
to O(N) in presence of hash collisions, but even in this case, accessing
the hash map is still more efficient than scanning all the entries in
the BTreeSet to search for the target PID.
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
Introduce a per-task generation counter to check the validity of the
cpumask at dispatch time.
The logic is the following:
- the cpumask generation number is incremented every time a task
calls .set_cpumask()
- when a task is enqueued the current generation number is stored in
the queued_task_ctx and relayed to the user-space scheduler
- the user-space scheduler can decide to dispatch the task on the CPU
determined by the BPF layer in .select_cpu(), redirect the task to
any other specific CPU, or redirect to the first CPU available (using
NO_CPU)
- task is then dispatched back to the BPF code along with its cpumask
generation counter
- at dispatch time the BPF code checks if the generation number is the
same and it discards the dispatch attempt if the cpumask is not valid
anymore (the task will be automatically re-enqueued by the sched-ext
core code, potentially selecting another CPU / cpumask)
- if the cpumask is valid, but the CPU selected by the user-space
scheduler is invalid (according to the cpumask), the task will be
transparently bounced by the BPF code to the shared DSQ (in this way
the user-space code can be completely abstracted and dispatches that
target invalid CPUs can be automatically fixed by the BPF layer)
This solution can prevent stalls due to dispatches targeting invalid
CPUs and it can also avoid redundant dispatch events, making the code
more efficient and the cpumask interlocking more reliable.
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
As described in [0], there is an open problem in load balancing called
the "infeasible weights" problem. Essentially, the problem boils down to
the fact that a task with disproportionately high load can be granted
more CPU time than they can actually consume per their duty cycle.
This patch implements a solution to that problem, wherein we apply the
algorithm described in this paper to adjust all infeasible weights in
the system down to a feasible wight that gives them their full duty
cycle, while allowing the remaining feasible tasks on the system to
share the remaining compute capacity on the machine.
[0]: https://drive.google.com/file/d/1fAoWUlmW-HTp6akuATVpMxpUpvWcGSAv/view?usp=drive_link
Signed-off-by: David Vernet <void@manifault.com>
Dispatch to the shared DSQ (NO_CPU) only when the assigned CPU is not
idle anymore, otherwise maintain the same CPU that has been assigned by
the BPF layer.
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
When the system is not being fully utilized there may be delays in
promptly awakening the user-space scheduler.
This can happen for example, when some CPU-intensive tasks are
constantly dispatched bypassing the user-space scheduler (e.g., using
SCX_DSQ_LOCAL) and other CPUs are completely idle.
Under this condition the update_idle() can fail to activate the
user-space scheduler, because there are no pending events, and only the
periodic timer will wake up the scheduler, potentially introducing lags
of up to 1 sec.
This can be reproduced, for example, running a video game that doesn't
use all the CPUs available in the system (i.e., Team Fortress 2). With
this game it is pretty easy to notice sporadic lags that are resumed
after ~1sec, due to the periodic timer kicking scheduler.
To prevent this from happening wake up the user-space scheduler
immediately as soon as a CPU is released, speculating on the fact that
most of the time there will be always another task ready to run.
This can introduce a little more overhead in the scheduler (due to
potential unnecessary wake up events), but it also prevents stuttery
behaviors and it makes the system much more smooth and responsive,
especially with video games.
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
Use scx_bpf_dispatch_cancel() to invalidate dispatches on wrong per-CPU
DSQ, due to cpumask race conditions, and redirect them to the shared
DSQ.
This prevents dispatching tasks to CPU that cannot be used according to
the task's cpumask.
With this applied the scheduler passed all the `stress-ng --race-sched`
stress tests.
Moreover, introduce a counter that is periodically reported to stdout as
an additional statistic, that can be helpful for debugging.
Link: https://github.com/sched-ext/sched_ext/pull/135
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
Print all the scheduler statistics before exiting. Reporting the very
last state of the scheduler can help to debug events that could trigger
error conditions (such as page faults, scheduler congestions, etc.).
While at it, fix also some minor coding style issues (tabs vs spaces).
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
SCX_KICK_IDLE is a new feature which isn't defined in older kernels. Add
compat wrapper and use it for idle CPU wakeups.
Signed-off-by: Tejun Heo <tj@kernel.org>
This is meant to be an example scheduler that won't necessarily run well
in production. Let's remove the 3 second timeout and use the system
default of 30.
Signed-off-by: David Vernet <void@manifault.com>
Let's make it clear that this scheduler isn't expected to perform well,
and instead point people to scx_rustland.
Signed-off-by: David Vernet <void@manifault.com>
Items in the task BTreeSet are stored by pid and vruntime. Make sure
that we never store multiple items with the same PID, so that
re-enqueued tasks are not dispatched multiple times.
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
Only scx_simple/qmap are in the kernel tree now. Drop the rest from the sync
script. Also update the sync script so that it can handle empty
rust_scheds variable.
Signed-off-by: Tejun Heo <tj@kernel.org>
Allow to scale the effective time slice down to 250 us. This can help to
maintain a good quality of the audio even when the system is overloaded
by multiple CPU-intensive tasks.
Moreover, always round up the time slice scaling factor to be a little
more aggressive and prioritize at scaling the time slice, so that we can
prioritize low latency tasks even more.
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
Evaluate the number of voluntary context switches per second (nvcsw/sec)
for each task using an exponentially weighted moving average (EWMA) with
weight 0.5, that allows to classify interactive tasks with more
accuracy.
Using a simple average over a period of time of 10 sec can introduce
small lags every 10 sec, as the statistics for the number of voluntary
context switches are refreshed. This can result in interactive tasks
taking a brief time to catch up in order to be accurately classified as
so, causing for example short audio cracks, small drop of 5-10 fps in
games, etc.
Using a EMWA allows to smooth the average of nvcsw/sec, preventing short
lags in the interactive tasks, while also preventing to incorrectly
classify as interactive tasks that may experience an isolated short
burst of voluntary context switches.
This patch has been tested with the usual test case of playing a
videogame while running a parallel kernel build in the background.
Without this patch the short lag every 10 sec is clearly noticeable,
with this patch applied the game and audio run smoothly.
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
Simplify the idle selection logic by relying only on the built-in idle
selection performed in the BPF layer.
When there are idle CPUs available in the system, tasks are dispatched
directly by the BPF dispatcher without invoking the user-space
scheduler. This allows to avoid the user-space overhead and get the best
system performance when CPU resources are not overcommitted.
Once the number of tasks exceeds the available CPUs, the user-space
scheduler takes over. However, by this time, the system is already
overcommitted, so there's little advantage in attempting to pinpoint the
optimal idle CPU through the user-space scheduler. Instead, tasks can be
executed on the first available CPU, consistently dispatching them to
the shared DSQ.
This allows to achieve the optimal performance both with system
under-utilization and over-utilization.
With this change in place the user-space scheduler won't dispatch tasks
directly to specific CPUs, but we still want to keep this as a generic
feature in the BPF layer, so that it can be potentially used in the
future by this scheduler or even by other user-space schedulers (once
the BPF layer will be moved to a more generic place).
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
When the user-space scheduler dispatches a task on a specific CPU, that
CPU might not be valid, since the user-space doesn't have visibility of
the task's cpumask.
When this happens the BPF dispatcher (that has direct visibility of the
cpumask) should automatically redirect the task to a valid CPU, but
instead of bouncing the task on the shared DSQ, we should try to use the
CPU assigned by the built-in idle selection logic.
If this CPU is also not valid, then we can simply ignore the task, that
has been de-queued and re-enqueued, since a valid CPU will be naturally
re-selected at a later time.
Moreover, avoid to kick any specific CPU when the task is dispatched to
shared DSQ, since the task can be consumed on any CPU and the additional
kick would simply add more overhead.
Lastly, rename dsq_id_to_cpu() to dsq_to_cpu() and cpu_to_dsq_id() to
cpu_to_dsq() for more clarity.
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
With commit c6ada25 ("scx_rustland: use custom pcpu DSQ instead of
SCX_DSQ_LOCAL{_ON}") we tried to introduce custom per-CPU DSQs, instead
of using SCX_DSQ_LOCAL and SCX_DSQ_LOCAL_ON to dispatch tasks.
This was required, because dispatching tasks using SCX_DSQ_LOCAL_ON
doesn't provide a guarantee that the cpumask, checked at dispatch time
to determine the validity of a target CPU, remains valid.
This method solved the cpumask validity issue, but unfortunately it
introduced a noticeable performance regression and a potential
starvation issue (that were probably caused by the same problem): if a
task is assigned to a CPU in select_cpu() and the scheduler decides to
dispatch it on a different CPU, the task will be added to the new CPU's
DSQ, but if no dispatch event happens there, the task may remain stuck
in the per-CPU DSQ for a long time, triggering the sched-ext watchdog
timeout that would kick out the scheduler, for example:
12:53:28 [WARN] FAIL: IPC:CSteamEngin[7217] failed to run for 6.482s (err=1026)
12:53:28 [INFO] Unregister RustLand scheduler
Therefore, we reverted this change with 6d89ece ("scx_rustland: dispatch
tasks only on the global DSQ"), dispatching all the tasks to the global
DSQ, completely delegating the kernel to distribute tasks among the
available CPUs.
This is not the ideal solution, because we still want to give the
possibility to the user-space scheduler to assign tasks to specific
CPUs.
Therefore, re-introduce distinct per-CPU DSQs, but also provide a global
shared DSQ. Tasks dispatched in the per-CPU DSQs are consumed from the
dispatch() callback of their corresponding CPU, tasks dispatched in the
global shared DSQ are consumed from any CPU.
In this way the BPF layer is able to provide an interface that gives
the flexibility to the user-space to dispatch a task on a specific CPU
or on the first CPU available, depending on the particular scheduler's
need.
If an invalid CPU (according to the cpumask) is selected the BPF
dispatcher will transparently redirect the task to a valid CPU, selected
using the built-in idle selection logic.
In the future we may want to improve this part, giving to the
user-space the visibility of the cpumask, in order to pick a valid CPU
in advance and in a proper synchronized way.
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
No functional change, just some refactoring to make the code more clear.
We have is_usersched_needed() and set_usersched_needed() that are doing
different things (the former is checkig if there are pending tasks for
the scheduler, the latter is setting the usersched_needed flag to
activate the dispatch of the user-space scheduler).
Rename is_usersched_needed() to usersched_has_pending_tasks() to make
the code more clear and understandable.
Also move dispatch_user_scheduler() closer to the other dispatch-related
helper functions.
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
If we are doing local dispatch, we can avoid enqueue() altogether by
dispatching from select_cpu()
Signed-off-by: Dan Schatzberg <schatzberg.dan@gmail.com>
This is a really minor optimization, but we don't need idle_smtmask to
schedule pinned tasks, so defer it so the nr_cpus_allowed == 1 path is
marginally faster.
Signed-off-by: Dan Schatzberg <schatzberg.dan@gmail.com>
idle_cpumask isn't used at all in pick_idle_cpu_from. The only need for
these cpumasks is to check if prev_cpu is a wholly idle CPU (and we only
do this when smt_enabled). idle_smtmask is sufficient for that check.
Signed-off-by: Dan Schatzberg <schatzberg.dan@gmail.com>
Prior to this patch, we only bump LSTAT_AFFN_BIOL when the target cpu
was idle, but in both cases it should be counted as AFFN_VIOL.
Signed-off-by: Dan Schatzberg <schatzberg.dan@gmail.com>
26ae1b0356
changed scx_exit_info which requires us to rebuild with a new vmlinux.h
This patch updates vmlinux.h to the current sched_ext branch in the
github repo.
Signed-off-by: Dan Schatzberg <schatzberg.dan@gmail.com>
Currently scx_layered outputs statistics periodically as info! logs. The
format of this is largely unstructured and mostly suitable for running
scx_layered interactively (e.g. observing its behavior on the command
line or via logs after the fact).
In order to run scx_layered at larger scale, it's desireable to have
statistics output in some format that is amenable to being ingested into
monitoring databases (e.g. Prometheseus). This allows collection of
stats across many machines.
This commit adds a command line flag (-o) that outputs statistics to
stdout in OpenMetrics format instead of the normal log mechanism.
OpenMetrics has a public format
specification (https://github.com/OpenObservability/OpenMetrics) and is
in use by many projects.
The library for producing OpenMetrics metrics is lightweight but does
induce some changes. Primarily, metrics need to be pre-registered (see
OpenMetricsStats::new()).
Without -o, the output looks as before, for example:
```
19:39:54 [INFO] CPUs: online/possible=52/52 nr_cores=26
19:39:54 [INFO] Layered Scheduler Attached
19:39:56 [INFO] tot= 9912 local=76.71 open_idle= 0.00 affn_viol= 2.63 tctx_err=0 proc=21ms
19:39:56 [INFO] busy= 1.3 util= 65.2 load= 263.4 fallback_cpu= 1
19:39:56 [INFO] batch : util/frac= 49.7/ 76.3 load/frac= 252.0: 95.7 tasks= 458
19:39:56 [INFO] tot= 2842 local=45.04 open_idle= 0.00 preempt= 0.00 affn_viol= 0.00
19:39:56 [INFO] cpus= 2 [ 0, 2] 04000001 00000000
19:39:56 [INFO] immediate: util/frac= 0.0/ 0.0 load/frac= 0.0: 0.0 tasks= 0
19:39:56 [INFO] tot= 0 local= 0.00 open_idle= 0.00 preempt= 0.00 affn_viol= 0.00
19:39:56 [INFO] cpus= 50 [ 0, 50] fbfffffe 000fffff
19:39:56 [INFO] normal : util/frac= 15.4/ 23.7 load/frac= 11.4: 4.3 tasks= 556
19:39:56 [INFO] tot= 7070 local=89.43 open_idle= 0.00 preempt= 0.00 affn_viol= 3.69
19:39:56 [INFO] cpus= 50 [ 0, 50] fbfffffe 000fffff
19:39:58 [INFO] tot= 7091 local=84.91 open_idle= 0.00 affn_viol= 2.64 tctx_err=0 proc=21ms
19:39:58 [INFO] busy= 0.6 util= 31.2 load= 107.1 fallback_cpu= 1
19:39:58 [INFO] batch : util/frac= 18.3/ 58.5 load/frac= 93.9: 87.7 tasks= 589
19:39:58 [INFO] tot= 2011 local=60.67 open_idle= 0.00 preempt= 0.00 affn_viol= 0.00
19:39:58 [INFO] cpus= 2 [ 2, 2] 04000001 00000000
19:39:58 [INFO] immediate: util/frac= 0.0/ 0.0 load/frac= 0.0: 0.0 tasks= 0
19:39:58 [INFO] tot= 0 local= 0.00 open_idle= 0.00 preempt= 0.00 affn_viol= 0.00
19:39:58 [INFO] cpus= 50 [ 50, 50] fbfffffe 000fffff
19:39:58 [INFO] normal : util/frac= 13.0/ 41.5 load/frac= 13.2: 12.3 tasks= 650
19:39:58 [INFO] tot= 5080 local=94.51 open_idle= 0.00 preempt= 0.00 affn_viol= 3.68
19:39:58 [INFO] cpus= 50 [ 50, 50] fbfffffe 000fffff
^C19:39:59 [INFO] EXIT: BPF scheduler unregistered
```
With -o passed, the output is in OpenMetrics format:
```
19:40:08 [INFO] CPUs: online/possible=52/52 nr_cores=26
19:40:08 [INFO] Layered Scheduler Attached
# HELP total Total scheduling events in the period.
# TYPE total gauge
total 8489
# HELP local % that got scheduled directly into an idle CPU.
# TYPE local gauge
local 86.45305689716104
# HELP open_idle % of open layer tasks scheduled into occupied idle CPUs.
# TYPE open_idle gauge
open_idle 0.0
# HELP affn_viol % which violated configured policies due to CPU affinity restrictions.
# TYPE affn_viol gauge
affn_viol 2.332430203793144
# HELP tctx_err Failures to free task contexts.
# TYPE tctx_err gauge
tctx_err 0
# HELP proc_ms CPU time this binary has consumed during the period.
# TYPE proc_ms gauge
proc_ms 20
# HELP busy CPU busy % (100% means all CPUs were fully occupied).
# TYPE busy gauge
busy 0.5294061026085283
# HELP util CPU utilization % (100% means one CPU was fully occupied).
# TYPE util gauge
util 27.37195512782239
# HELP load Sum of weight * duty_cycle for all tasks.
# TYPE load gauge
load 81.55024768702126
# HELP layer_util CPU utilization of the layer (100% means one CPU was fully occupied).
# TYPE layer_util gauge
layer_util{layer_name="immediate"} 0.0
layer_util{layer_name="normal"} 19.340849995024997
layer_util{layer_name="batch"} 8.031105132797393
# HELP layer_util_frac Fraction of total CPU utilization consumed by the layer.
# TYPE layer_util_frac gauge
layer_util_frac{layer_name="batch"} 29.34063385422595
layer_util_frac{layer_name="immediate"} 0.0
layer_util_frac{layer_name="normal"} 70.65936614577405
# HELP layer_load Sum of weight * duty_cycle for tasks in the layer.
# TYPE layer_load gauge
layer_load{layer_name="immediate"} 0.0
layer_load{layer_name="normal"} 11.14363313258934
layer_load{layer_name="batch"} 70.40661455443191
# HELP layer_load_frac Fraction of total load consumed by the layer.
# TYPE layer_load_frac gauge
layer_load_frac{layer_name="normal"} 13.664744680306903
layer_load_frac{layer_name="immediate"} 0.0
layer_load_frac{layer_name="batch"} 86.33525531969309
# HELP layer_tasks Number of tasks in the layer.
# TYPE layer_tasks gauge
layer_tasks{layer_name="immediate"} 0
layer_tasks{layer_name="normal"} 490
layer_tasks{layer_name="batch"} 343
# HELP layer_total Number of scheduling events in the layer.
# TYPE layer_total gauge
layer_total{layer_name="normal"} 6711
layer_total{layer_name="batch"} 1778
layer_total{layer_name="immediate"} 0
# HELP layer_local % of scheduling events directly into an idle CPU.
# TYPE layer_local gauge
layer_local{layer_name="batch"} 69.79752530933632
layer_local{layer_name="immediate"} 0.0
layer_local{layer_name="normal"} 90.86574281031143
# HELP layer_open_idle % of scheduling events into idle CPUs occupied by other layers.
# TYPE layer_open_idle gauge
layer_open_idle{layer_name="immediate"} 0.0
layer_open_idle{layer_name="batch"} 0.0
layer_open_idle{layer_name="normal"} 0.0
# HELP layer_preempt % of scheduling events that preempted other tasks. #
# TYPE layer_preempt gauge
layer_preempt{layer_name="normal"} 0.0
layer_preempt{layer_name="batch"} 0.0
layer_preempt{layer_name="immediate"} 0.0
# HELP layer_affn_viol % of scheduling events that violated configured policies due to CPU affinity restrictions.
# TYPE layer_affn_viol gauge
layer_affn_viol{layer_name="normal"} 2.950379973178364
layer_affn_viol{layer_name="batch"} 0.0
layer_affn_viol{layer_name="immediate"} 0.0
# HELP layer_cur_nr_cpus Current # of CPUs assigned to the layer.
# TYPE layer_cur_nr_cpus gauge
layer_cur_nr_cpus{layer_name="normal"} 50
layer_cur_nr_cpus{layer_name="batch"} 2
layer_cur_nr_cpus{layer_name="immediate"} 50
# HELP layer_min_nr_cpus Minimum # of CPUs assigned to the layer.
# TYPE layer_min_nr_cpus gauge
layer_min_nr_cpus{layer_name="normal"} 0
layer_min_nr_cpus{layer_name="batch"} 0
layer_min_nr_cpus{layer_name="immediate"} 0
# HELP layer_max_nr_cpus Maximum # of CPUs assigned to the layer.
# TYPE layer_max_nr_cpus gauge
layer_max_nr_cpus{layer_name="immediate"} 50
layer_max_nr_cpus{layer_name="normal"} 50
layer_max_nr_cpus{layer_name="batch"} 2
# EOF
^C19:40:11 [INFO] EXIT: BPF scheduler unregistered
```
Signed-off-by: Dan Schatzberg <schatzberg.dan@gmail.com>
Commit c6ada25 ("scx_rustland: use custom pcpu DSQ instead of
SCX_DSQ_LOCAL{_ON}") fixed the race issues with the cpumask, but it also
introduced performance regressions.
Until we figure out the reasons of the performance regressions, simplify
the dispatcher and go back at using only the global DSQ, relying on the
built-in idle cpu selection.
In this way we can still enforce task affinity properly
(`stress-ng --race-sched N` does not crash the scheduler) and we can
also provide a better level of system responsiveness (according to the
results of the stress tests done recently).
The idea of this change is to make the scheduler usable in certain
real-world scenarios (and as bug-free as possible), while we figure out
the performance regressions of the per-CPU DSQ approach, that will
likely be re-introduced later on in the future.
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
No functional change, simply rewrite the code a bit and update the
comment to clarify the logic to detect interactive tasks and apply the
priority boost.
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
Allow to specify `-b 0` to completely disable the slice boost logic and
fallback to standard vruntime-based scheduler with variable time slice.
In this way interactive tasks will not get over-prioritized over the
other tasks in the system.
Having this option can help to easily track down potential performance
regressions arising for over-prioritizing interactive tasks.
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
Make sure to re-schedule the user-space scheduler if it's preempted by a
task from a higher priority sched_class.
Signed-off-by: Andrea Righi <andrea.righi@canonical.com>
