Re: 答复: [PATCH v3] mm/compaction:let proactive compaction order configurable

[Khalid Aziz]

On 5/11/21 1:48 AM, Chu,Kaiping wrote:
> > -----邮件原件-----
> > 发件人: Khalid Aziz <khalid.aziz@xxxxxxxxxx>
> > 发送时间: 2021年5月7日 5:27
> > 收件人: David Rientjes <rientjes@xxxxxxxxxx>; Chu,Kaiping
> > <chukaiping@xxxxxxxxx>
> > 抄送: mcgrof@xxxxxxxxxx; keescook@xxxxxxxxxxxx; yzaikin@xxxxxxxxxx;
> > akpm@xxxxxxxxxxxxxxxxxxxx; vbabka@xxxxxxx; nigupta@xxxxxxxxxx;
> > bhe@xxxxxxxxxx; iamjoonsoo.kim@xxxxxxx; mateusznosek0@xxxxxxxxx;
> > sh_def@xxxxxxx; linux-kernel@xxxxxxxxxxxxxxx; linux-fsdevel@xxxxxxxxxxxxxxx;
> > linux-mm@xxxxxxxxx
> > 主题: Re: [PATCH v3] mm/compaction:let proactive compaction order
> > configurable
> >
> > On 4/25/21 9:15 PM, David Rientjes wrote:
> > > On Sun, 25 Apr 2021, chukaiping wrote:
> > >
> > > > Currently the proactive compaction order is fixed to
> > > > COMPACTION_HPAGE_ORDER(9), it's OK in most machines with lots of
> > > > normal 4KB memory, but it's too high for the machines with small
> > > > normal memory, for example the machines with most memory configured
> > > > as 1GB hugetlbfs huge pages. In these machines the max order of free
> > > > pages is often below 9, and it's always below 9 even with hard
> > > > compaction. This will lead to proactive compaction be triggered very
> > > > frequently. In these machines we only care about order of 3 or 4.
> > > > This patch export the oder to proc and let it configurable by user,
> > > > and the default value is still COMPACTION_HPAGE_ORDER.
> > >
> > > As asked in the review of the v1 of the patch, why is this not a
> > > userspace policy decision?  If you are interested in order-3 or
> > > order-4 fragmentation, for whatever reason, you could periodically
> > > check /proc/buddyinfo and manually invoke compaction on the system.
> > >
> > > In other words, why does this need to live in the kernel?
> >
> > I have struggled with this question. Fragmentation and allocation stalls are
> > significant issues on large database systems which also happen to use memory
> > in similar ways (90+% of memory is allocated as hugepages) leaving just
> > enough memory to run rest of the userspace processes. I had originally
> > proposed a kernel patch to monitor, do a trend analysis of memory usage and
> > take proactive action -
> > <https://lore.kernel.org/lkml/20190813014012.30232-1-khalid.aziz@oracle.c
> > om/>. Based upon feedback, I moved the implementation to userspace -
> > <https://github.com/oracle/memoptimizer>. Test results across multiple
> > workloads have been very good. Results from one of the workloads are in this
> > blog - <https://blogs.oracle.com/linux/anticipating-your-memory-needs>. It
> > works well from userspace but it has limited ways to influence reclamation and
> > compaction. It uses watermark_scale_factor to boost watermarks and cause
> > reclamation to kick in earlier and run longer. It uses
> > /sys/devices/system/node/node%d/compact to force compaction on the node
> > expected to reach high level of fragmentation soon. Neither of these is very
> > efficient from userspace even though they get the job done. Scaling watermark
> > has longer lasting impact than raising scanning priority in balance_pgdat()
> > temporarily. I plan to experiment with watermark_boost_factor to see if I can
> > use it in place of /sys/devices/system/node/node%d/compact and get the
> > same results. Doing all of this in the kernel can be more efficient and lessen
> > potential negative impact on the system. On the other hand, it is easier to fix
> > and update such policies in userspace although at the cost of having a
> > performance critical component live outside the kernel and thus not be active
> > on the system by default.
> I studied your memoptimizer these days, I also agree to move the implementation into kernel to co-work with current proactive compaction mechanism to get higher efficiency.
> By the way I am interested about the memoptimizer, I want to have a test of it, but how to evaluate its effectiveness?

If you look at this blog I wrote on memoptimizer - <https://blogs.oracle.com/linux/anticipating-your-memory-needs>, 
under the section "Measuring stalls" I describe the workload I used to measure its effectiveness. The metric I use is 
number of allocation/compaction stalls over a multi-hour run of the workload. Number of allocation/compaction stalls 
gives an idea of how effective system is at keeping free order 0 and larger pages available proactively. Any workload 
that runs into significant number of stalls is a good workload to use to measure effectiveness.

--
Khalid