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Message-ID: <6ece8405-650c-69a0-09eb-e7f1f84c0c3f@infradead.org>
Date: Mon, 20 Jan 2020 16:12:12 -0800
From: Randy Dunlap <rdunlap@...radead.org>
To: 王贇 <yun.wang@...ux.alibaba.com>,
Ingo Molnar <mingo@...hat.com>,
Peter Zijlstra <peterz@...radead.org>,
Juri Lelli <juri.lelli@...hat.com>,
Vincent Guittot <vincent.guittot@...aro.org>,
Dietmar Eggemann <dietmar.eggemann@....com>,
Steven Rostedt <rostedt@...dmis.org>,
Ben Segall <bsegall@...gle.com>, Mel Gorman <mgorman@...e.de>,
Luis Chamberlain <mcgrof@...nel.org>,
Kees Cook <keescook@...omium.org>,
Iurii Zaikin <yzaikin@...gle.com>,
Michal Koutný <mkoutny@...e.com>,
linux-fsdevel@...r.kernel.org, linux-kernel@...r.kernel.org,
linux-doc@...r.kernel.org,
"Paul E. McKenney" <paulmck@...ux.ibm.com>,
Jonathan Corbet <corbet@....net>
Subject: Re: [PATCH v7 2/2] sched/numa: documentation for per-cgroup numa,
statistics
Hi,
Documentation edits below...
On 1/18/20 10:09 PM, 王贇 wrote:
> Add the description for 'numa_locality', also a new doc to explain
> the details on how to deal with the per-cgroup numa statistics.
>
> Cc: Peter Zijlstra <peterz@...radead.org>
> Cc: Michal Koutný <mkoutny@...e.com>
> Cc: Mel Gorman <mgorman@...e.de>
> Cc: Jonathan Corbet <corbet@....net>
> Cc: Iurii Zaikin <yzaikin@...gle.com>
> Cc: Randy Dunlap <rdunlap@...radead.org>
> Signed-off-by: Michael Wang <yun.wang@...ux.alibaba.com>
> ---
> Documentation/admin-guide/cg-numa-stat.rst | 178 ++++++++++++++++++++++++
> Documentation/admin-guide/index.rst | 1 +
> Documentation/admin-guide/kernel-parameters.txt | 4 +
> Documentation/admin-guide/sysctl/kernel.rst | 9 ++
> init/Kconfig | 2 +
> 5 files changed, 194 insertions(+)
> create mode 100644 Documentation/admin-guide/cg-numa-stat.rst
>
> diff --git a/Documentation/admin-guide/cg-numa-stat.rst b/Documentation/admin-guide/cg-numa-stat.rst
> new file mode 100644
> index 000000000000..30ebe5d6404f
> --- /dev/null
> +++ b/Documentation/admin-guide/cg-numa-stat.rst
> @@ -0,0 +1,178 @@
> +.. SPDX-License-Identifier: GPL-2.0
> +
> +===============================
> +Per-cgroup NUMA statistics
> +===============================
> +
> +Background
> +----------
> +
> +On NUMA platforms, remote memory accessing always has a performance penalty.
> +Although we have NUMA balancing working hard to maximize the access locality,
> +there are still situations it can't help.
> +
> +This could happen in modern production environment. When a large number of
> +cgroups are used to classify and control resources, this creates a complex
> +configuration for memory policy, CPUs and NUMA nodes. In such cases NUMA
> +balancing could end up with the wrong memory policy or exhausted local NUMA
> +node, which would lead to low percentage of local page accesses.
> +
> +We need to detect such cases, figure out which workloads from which cgroup
> +have introduced the issues, then we get chance to do adjustment to avoid
> +performance degradation.
> +
> +However, there are no hardware counters for per-task local/remote accessing
> +info, we don't know how many remote page accesses have occurred for a
> +particular task.
> +
> +NUMA Locality
> +-------------
> +
> +Fortunately, we have NUMA Balancing which scans task's mapping and triggers
> +page fault periodically, giving us the opportunity to record per-task page
> +accessing info, when the CPU fall into PF is from the same node of pages, we
> +consider task as doing local page accessing, otherwise the remote page
> +accessing, we call these two counter the locality info.
counters
> +
> +On each tick, we acquire the locality info of current task on that CPU, update
> +the increments into its cgroup, becoming the group locality info.
> +
> +By "echo 1 > /proc/sys/kernel/numa_locality" at runtime or adding boot parameter
> +'numa_locality', we will enable the accounting of per-cgroup NUMA locality info,
> +the 'cpu.numa_stat' entry of CPU cgroup will show statistics::
> +
> + page_access local=NR_LOCAL_PAGE_ACCESS remote=NR_REMOTE_PAGE_ACCESS
> +
> +We define 'NUMA locality' as::
> +
> + NR_LOCAL_PAGE_ACCESS * 100 / (NR_LOCAL_PAGE_ACCESS + NR_REMOTE_PAGE_ACCESS)
> +
> +This per-cgroup percentage number helps to represent the NUMA Balancing behavior.
> +
> +Note that the accounting is hierarchical, which means the NUMA locality info for
> +a given group represent not only the workload of this group, but also the
represents
> +workloads of all its descendants.
> +
> +For example the 'cpu.numa_stat' shows::
> +
> + page_access local=129909383 remote=18265810
> +
> +The NUMA locality calculated as::
> +
> + 129909383 * 100 / (129909383 + 18265810) = 87.67
> +
> +Thus we know the workload of this group and its descendants have totally done
> +129909383 times of local page accessing and 18265810 times of remotes, locality
> +is 87.67% which imply most of the memory access are local.
implies
> +
> +NUMA Consumption
> +----------------
> +
> +There are also other cgroup entry help us to estimate NUMA efficiency, which is
entries which help us to estimate NUMA efficiency. They are
> +'cpuacct.usage_percpu' and 'memory.numa_stat'.
> +
> +By reading 'cpuacct.usage_percpu' we will get per-cpu runtime (in nanoseconds)
> +info (in hierarchy) as::
> +
> + CPU_0_RUNTIME CPU_1_RUNTIME CPU_2_RUNTIME ... CPU_X_RUNTIME
> +
> +Combined with the info from::
> +
> + cat /sys/devices/system/node/nodeX/cpulist
> +
> +We would be able to accumulate the runtime of CPUs into NUMA nodes, to get the
> +per-cgroup node runtime info.
> +
> +By reading 'memory.numa_stat' we will get per-cgroup node memory consumption
> +info as::
> +
> + total=TOTAL_MEM N0=MEM_ON_NODE0 N1=MEM_ON_NODE1 ... NX=MEM_ON_NODEX
> +
> +Together we call these the per-cgroup NUMA consumption info, tell us how many
telling us
> +resources a particular workload has consumed, on a particular NUMA node.
> +
> +Monitoring
> +----------
> +
> +By monitoring the increments of locality info, we can easily know whether NUMA
> +Balancing is working well for a particular workload.
> +
> +For example we take a 5 seconds sample period, then on each sampling we have::
> +
> + local_diff = last_nr_local_page_access - nr_local_page_access
> + remote_diff = last_nr_remote_page_access - nr_remote_page_access
> +
> +and we get the locality in this period as::
> +
> + locality = local_diff * 100 / (local_diff + remote_diff)
> +
> +We can plot a line for locality, when the line close to 100% things are good,
locality. When the line is close to 100%, things are good;
> +when getting close to 0% something is wrong, we can pick a proper watermark to
wrong. We can pick
> +trigger warning message.
> +
> +You may want to drop the data if the local/remote_diff is too small, which
> +implies there are not many available pages for NUMA Balancing to scan, ignoring
> +would be fine since most likely the workload is insensitive to NUMA, or the
> +memory topology is already good enough.
> +
> +Monitoring root group helps you control the overall situation, while you may
> +also want to monitor all the leaf groups which contain the workloads, this
> +helps to catch the mouse.
> +
> +Try to put your workload into also the cpuacct & memory cgroup, when NUMA
> +Balancing is disabled or locality becomes too small, we may want to monitor
> +the per-node runtime & memory info to see if the node consumption meet the
> +requirements.
> +
> +For NUMA node X on each sampling we have::
> +
> + runtime_X_diff = runtime_X - last_runtime_X
> + runtime_all_diff = runtime_all - last_runtime_all
> +
> + runtime_percent_X = runtime_X_diff * 100 / runtime_all_diff
> + memory_percent_X = memory_X * 100 / memory_all
> +
> +These two percentages are usually matched on each node, workload should execute
> +mostly on the node that contains most of its memory, but it's not guaranteed.
> +
> +The workload may only access a small part of its memory, in such cases although
> +the majority of memory are remotely, locality could still be good.
are remote,
> +
> +Thus to tell if things are fine or not depends on the understanding of system
> +resource deployment, however, if you find node X got 100% memory percent but 0%
> +runtime percent, definitely something is wrong.
> +
> +Troubleshooting
> +---------------
> +
> +After identifying which workload introduced the bad locality, check:
> +
> +1). Is the workload bound to a particular NUMA node?
> +2). Has any NUMA node run out of resources?
> +
> +There are several ways to bind task's memory with a NUMA node, the strict way
> +like the MPOL_BIND memory policy or 'cpuset.mems' will limit the memory
> +node where to allocate pages. In this situation, admin should make sure the
> +task is allowed to run on the CPUs of that NUMA node, and make sure there are
> +available CPU resource there.
resources
> +
> +There are also ways to bind task's CPU with a NUMA node, like 'cpuset.cpus' or
> +sched_setaffinity() syscall. In this situation, NUMA Balancing help to migrate
helps
> +pages into that node, admin should make sure there are available memory there.
is
> +
> +Admin could try to rebind or unbind the NUMA node to erase the damage, make a
> +change then observe the statistics to see if things get better until the
> +situation is acceptable.
> +
> +Highlights
> +----------
> +
> +For some tasks, NUMA Balancing may be found to be unnecessary to scan pages,
> +and locality could always be 0 or small number, don't pay attention to them
> +since they most likely insensitive to NUMA.
> +
> +There is no accounting until the option is turned on, so enable it in advance
> +if you want to have the whole history.
> +
> +We have per-task migfailed counter to tell how many page migration has been
migrations have {drop: been}
> +failed for a particular task, you will find it in /proc/PID/sched entry.
task; you
HTH.
--
~Randy
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