From: "Huang, Ying" <ying.huang@intel.com>
To: Yafang Shao <laoar.shao@gmail.com>
Cc: akpm@linux-foundation.org, mgorman@techsingularity.net,
linux-mm@kvack.org, Matthew Wilcox <willy@infradead.org>,
David Rientjes <rientjes@google.com>
Subject: Re: [PATCH v2 3/3] mm/page_alloc: Introduce a new sysctl knob vm.pcp_batch_scale_max
Date: Mon, 29 Jul 2024 14:14:54 +0800 [thread overview]
Message-ID: <87r0bcwwpt.fsf@yhuang6-desk2.ccr.corp.intel.com> (raw)
In-Reply-To: <CALOAHbCGBVfeiyy5+03u3qqJyXjdNjoQQJbeAhUGKpvtFByb=A@mail.gmail.com> (Yafang Shao's message of "Mon, 29 Jul 2024 14:13:07 +0800")
Yafang Shao <laoar.shao@gmail.com> writes:
> On Mon, Jul 29, 2024 at 2:04 PM Huang, Ying <ying.huang@intel.com> wrote:
>>
>> Yafang Shao <laoar.shao@gmail.com> writes:
>>
>> > On Mon, Jul 29, 2024 at 1:54 PM Huang, Ying <ying.huang@intel.com> wrote:
>> >>
>> >> Yafang Shao <laoar.shao@gmail.com> writes:
>> >>
>> >> > On Mon, Jul 29, 2024 at 1:16 PM Huang, Ying <ying.huang@intel.com> wrote:
>> >> >>
>> >> >> Yafang Shao <laoar.shao@gmail.com> writes:
>> >> >>
>> >> >> > On Mon, Jul 29, 2024 at 11:22 AM Huang, Ying <ying.huang@intel.com> wrote:
>> >> >> >>
>> >> >> >> Hi, Yafang,
>> >> >> >>
>> >> >> >> Yafang Shao <laoar.shao@gmail.com> writes:
>> >> >> >>
>> >> >> >> > During my recent work to resolve latency spikes caused by zone->lock
>> >> >> >> > contention[0], I found that CONFIG_PCP_BATCH_SCALE_MAX is difficult to use
>> >> >> >> > in practice.
>> >> >> >>
>> >> >> >> As we discussed before [1], I still feel confusing about the description
>> >> >> >> about zone->lock contention. How about change the description to
>> >> >> >> something like,
>> >> >> >
>> >> >> > Sure, I will change it.
>> >> >> >
>> >> >> >>
>> >> >> >> Larger page allocation/freeing batch number may cause longer run time of
>> >> >> >> code holding zone->lock. If zone->lock is heavily contended at the same
>> >> >> >> time, latency spikes may occur even for casual page allocation/freeing.
>> >> >> >> Although reducing the batch number cannot make zone->lock contended
>> >> >> >> lighter, it can reduce the latency spikes effectively.
>> >> >> >>
>> >> >> >> [1] https://lore.kernel.org/linux-mm/87ttgv8hlz.fsf@yhuang6-desk2.ccr.corp.intel.com/
>> >> >> >>
>> >> >> >> > To demonstrate this, I wrote a Python script:
>> >> >> >> >
>> >> >> >> > import mmap
>> >> >> >> >
>> >> >> >> > size = 6 * 1024**3
>> >> >> >> >
>> >> >> >> > while True:
>> >> >> >> > mm = mmap.mmap(-1, size)
>> >> >> >> > mm[:] = b'\xff' * size
>> >> >> >> > mm.close()
>> >> >> >> >
>> >> >> >> > Run this script 10 times in parallel and measure the allocation latency by
>> >> >> >> > measuring the duration of rmqueue_bulk() with the BCC tools
>> >> >> >> > funclatency[1]:
>> >> >> >> >
>> >> >> >> > funclatency -T -i 600 rmqueue_bulk
>> >> >> >> >
>> >> >> >> > Here are the results for both AMD and Intel CPUs.
>> >> >> >> >
>> >> >> >> > AMD EPYC 7W83 64-Core Processor, single NUMA node, KVM virtual server
>> >> >> >> > =====================================================================
>> >> >> >> >
>> >> >> >> > - Default value of 5
>> >> >> >> >
>> >> >> >> > nsecs : count distribution
>> >> >> >> > 0 -> 1 : 0 | |
>> >> >> >> > 2 -> 3 : 0 | |
>> >> >> >> > 4 -> 7 : 0 | |
>> >> >> >> > 8 -> 15 : 0 | |
>> >> >> >> > 16 -> 31 : 0 | |
>> >> >> >> > 32 -> 63 : 0 | |
>> >> >> >> > 64 -> 127 : 0 | |
>> >> >> >> > 128 -> 255 : 0 | |
>> >> >> >> > 256 -> 511 : 0 | |
>> >> >> >> > 512 -> 1023 : 12 | |
>> >> >> >> > 1024 -> 2047 : 9116 | |
>> >> >> >> > 2048 -> 4095 : 2004 | |
>> >> >> >> > 4096 -> 8191 : 2497 | |
>> >> >> >> > 8192 -> 16383 : 2127 | |
>> >> >> >> > 16384 -> 32767 : 2483 | |
>> >> >> >> > 32768 -> 65535 : 10102 | |
>> >> >> >> > 65536 -> 131071 : 212730 |******************* |
>> >> >> >> > 131072 -> 262143 : 314692 |***************************** |
>> >> >> >> > 262144 -> 524287 : 430058 |****************************************|
>> >> >> >> > 524288 -> 1048575 : 224032 |******************** |
>> >> >> >> > 1048576 -> 2097151 : 73567 |****** |
>> >> >> >> > 2097152 -> 4194303 : 17079 |* |
>> >> >> >> > 4194304 -> 8388607 : 3900 | |
>> >> >> >> > 8388608 -> 16777215 : 750 | |
>> >> >> >> > 16777216 -> 33554431 : 88 | |
>> >> >> >> > 33554432 -> 67108863 : 2 | |
>> >> >> >> >
>> >> >> >> > avg = 449775 nsecs, total: 587066511229 nsecs, count: 1305242
>> >> >> >> >
>> >> >> >> > The avg alloc latency can be 449us, and the max latency can be higher
>> >> >> >> > than 30ms.
>> >> >> >> >
>> >> >> >> > - Value set to 0
>> >> >> >> >
>> >> >> >> > nsecs : count distribution
>> >> >> >> > 0 -> 1 : 0 | |
>> >> >> >> > 2 -> 3 : 0 | |
>> >> >> >> > 4 -> 7 : 0 | |
>> >> >> >> > 8 -> 15 : 0 | |
>> >> >> >> > 16 -> 31 : 0 | |
>> >> >> >> > 32 -> 63 : 0 | |
>> >> >> >> > 64 -> 127 : 0 | |
>> >> >> >> > 128 -> 255 : 0 | |
>> >> >> >> > 256 -> 511 : 0 | |
>> >> >> >> > 512 -> 1023 : 92 | |
>> >> >> >> > 1024 -> 2047 : 8594 | |
>> >> >> >> > 2048 -> 4095 : 2042818 |****** |
>> >> >> >> > 4096 -> 8191 : 8737624 |************************** |
>> >> >> >> > 8192 -> 16383 : 13147872 |****************************************|
>> >> >> >> > 16384 -> 32767 : 8799951 |************************** |
>> >> >> >> > 32768 -> 65535 : 2879715 |******** |
>> >> >> >> > 65536 -> 131071 : 659600 |** |
>> >> >> >> > 131072 -> 262143 : 204004 | |
>> >> >> >> > 262144 -> 524287 : 78246 | |
>> >> >> >> > 524288 -> 1048575 : 30800 | |
>> >> >> >> > 1048576 -> 2097151 : 12251 | |
>> >> >> >> > 2097152 -> 4194303 : 2950 | |
>> >> >> >> > 4194304 -> 8388607 : 78 | |
>> >> >> >> >
>> >> >> >> > avg = 19359 nsecs, total: 708638369918 nsecs, count: 36604636
>> >> >> >> >
>> >> >> >> > The avg was reduced significantly to 19us, and the max latency is reduced
>> >> >> >> > to less than 8ms.
>> >> >> >> >
>> >> >> >> > - Conclusion
>> >> >> >> >
>> >> >> >> > On this AMD CPU, reducing vm.pcp_batch_scale_max significantly helps reduce
>> >> >> >> > latency. Latency-sensitive applications will benefit from this tuning.
>> >> >> >> >
>> >> >> >> > However, I don't have access to other types of AMD CPUs, so I was unable to
>> >> >> >> > test it on different AMD models.
>> >> >> >> >
>> >> >> >> > Intel(R) Xeon(R) Platinum 8260 CPU @ 2.40GHz, two NUMA nodes
>> >> >> >> > ============================================================
>> >> >> >> >
>> >> >> >> > - Default value of 5
>> >> >> >> >
>> >> >> >> > nsecs : count distribution
>> >> >> >> > 0 -> 1 : 0 | |
>> >> >> >> > 2 -> 3 : 0 | |
>> >> >> >> > 4 -> 7 : 0 | |
>> >> >> >> > 8 -> 15 : 0 | |
>> >> >> >> > 16 -> 31 : 0 | |
>> >> >> >> > 32 -> 63 : 0 | |
>> >> >> >> > 64 -> 127 : 0 | |
>> >> >> >> > 128 -> 255 : 0 | |
>> >> >> >> > 256 -> 511 : 0 | |
>> >> >> >> > 512 -> 1023 : 2419 | |
>> >> >> >> > 1024 -> 2047 : 34499 |* |
>> >> >> >> > 2048 -> 4095 : 4272 | |
>> >> >> >> > 4096 -> 8191 : 9035 | |
>> >> >> >> > 8192 -> 16383 : 4374 | |
>> >> >> >> > 16384 -> 32767 : 2963 | |
>> >> >> >> > 32768 -> 65535 : 6407 | |
>> >> >> >> > 65536 -> 131071 : 884806 |****************************************|
>> >> >> >> > 131072 -> 262143 : 145931 |****** |
>> >> >> >> > 262144 -> 524287 : 13406 | |
>> >> >> >> > 524288 -> 1048575 : 1874 | |
>> >> >> >> > 1048576 -> 2097151 : 249 | |
>> >> >> >> > 2097152 -> 4194303 : 28 | |
>> >> >> >> >
>> >> >> >> > avg = 96173 nsecs, total: 106778157925 nsecs, count: 1110263
>> >> >> >> >
>> >> >> >> > - Conclusion
>> >> >> >> >
>> >> >> >> > This Intel CPU works fine with the default setting.
>> >> >> >> >
>> >> >> >> > Intel(R) Xeon(R) Platinum 8260 CPU @ 2.40GHz, single NUMA node
>> >> >> >> > ==============================================================
>> >> >> >> >
>> >> >> >> > Using the cpuset cgroup, we can restrict the test script to run on NUMA
>> >> >> >> > node 0 only.
>> >> >> >> >
>> >> >> >> > - Default value of 5
>> >> >> >> >
>> >> >> >> > nsecs : count distribution
>> >> >> >> > 0 -> 1 : 0 | |
>> >> >> >> > 2 -> 3 : 0 | |
>> >> >> >> > 4 -> 7 : 0 | |
>> >> >> >> > 8 -> 15 : 0 | |
>> >> >> >> > 16 -> 31 : 0 | |
>> >> >> >> > 32 -> 63 : 0 | |
>> >> >> >> > 64 -> 127 : 0 | |
>> >> >> >> > 128 -> 255 : 0 | |
>> >> >> >> > 256 -> 511 : 46 | |
>> >> >> >> > 512 -> 1023 : 695 | |
>> >> >> >> > 1024 -> 2047 : 19950 |* |
>> >> >> >> > 2048 -> 4095 : 1788 | |
>> >> >> >> > 4096 -> 8191 : 3392 | |
>> >> >> >> > 8192 -> 16383 : 2569 | |
>> >> >> >> > 16384 -> 32767 : 2619 | |
>> >> >> >> > 32768 -> 65535 : 3809 | |
>> >> >> >> > 65536 -> 131071 : 616182 |****************************************|
>> >> >> >> > 131072 -> 262143 : 295587 |******************* |
>> >> >> >> > 262144 -> 524287 : 75357 |**** |
>> >> >> >> > 524288 -> 1048575 : 15471 |* |
>> >> >> >> > 1048576 -> 2097151 : 2939 | |
>> >> >> >> > 2097152 -> 4194303 : 243 | |
>> >> >> >> > 4194304 -> 8388607 : 3 | |
>> >> >> >> >
>> >> >> >> > avg = 144410 nsecs, total: 150281196195 nsecs, count: 1040651
>> >> >> >> >
>> >> >> >> > The zone->lock contention becomes severe when there is only a single NUMA
>> >> >> >> > node. The average latency is approximately 144us, with the maximum
>> >> >> >> > latency exceeding 4ms.
>> >> >> >> >
>> >> >> >> > - Value set to 0
>> >> >> >> >
>> >> >> >> > nsecs : count distribution
>> >> >> >> > 0 -> 1 : 0 | |
>> >> >> >> > 2 -> 3 : 0 | |
>> >> >> >> > 4 -> 7 : 0 | |
>> >> >> >> > 8 -> 15 : 0 | |
>> >> >> >> > 16 -> 31 : 0 | |
>> >> >> >> > 32 -> 63 : 0 | |
>> >> >> >> > 64 -> 127 : 0 | |
>> >> >> >> > 128 -> 255 : 0 | |
>> >> >> >> > 256 -> 511 : 24 | |
>> >> >> >> > 512 -> 1023 : 2686 | |
>> >> >> >> > 1024 -> 2047 : 10246 | |
>> >> >> >> > 2048 -> 4095 : 4061529 |********* |
>> >> >> >> > 4096 -> 8191 : 16894971 |****************************************|
>> >> >> >> > 8192 -> 16383 : 6279310 |************** |
>> >> >> >> > 16384 -> 32767 : 1658240 |*** |
>> >> >> >> > 32768 -> 65535 : 445760 |* |
>> >> >> >> > 65536 -> 131071 : 110817 | |
>> >> >> >> > 131072 -> 262143 : 20279 | |
>> >> >> >> > 262144 -> 524287 : 4176 | |
>> >> >> >> > 524288 -> 1048575 : 436 | |
>> >> >> >> > 1048576 -> 2097151 : 8 | |
>> >> >> >> > 2097152 -> 4194303 : 2 | |
>> >> >> >> >
>> >> >> >> > avg = 8401 nsecs, total: 247739809022 nsecs, count: 29488508
>> >> >> >> >
>> >> >> >> > After setting it to 0, the avg latency is reduced to around 8us, and the
>> >> >> >> > max latency is less than 4ms.
>> >> >> >> >
>> >> >> >> > - Conclusion
>> >> >> >> >
>> >> >> >> > On this Intel CPU, this tuning doesn't help much. Latency-sensitive
>> >> >> >> > applications work well with the default setting.
>> >> >> >> >
>> >> >> >> > It is worth noting that all the above data were tested using the upstream
>> >> >> >> > kernel.
>> >> >> >> >
>> >> >> >> > Why introduce a systl knob?
>> >> >> >> > ===========================
>> >> >> >> >
>> >> >> >> > From the above data, it's clear that different CPU types have varying
>> >> >> >> > allocation latencies concerning zone->lock contention. Typically, people
>> >> >> >> > don't release individual kernel packages for each type of x86_64 CPU.
>> >> >> >> >
>> >> >> >> > Furthermore, for latency-insensitive applications, we can keep the default
>> >> >> >> > setting for better throughput. In our production environment, we set this
>> >> >> >> > value to 0 for applications running on Kubernetes servers while keeping it
>> >> >> >> > at the default value of 5 for other applications like big data. It's not
>> >> >> >> > common to release individual kernel packages for each application.
>> >> >> >>
>> >> >> >> Thanks for detailed performance data!
>> >> >> >>
>> >> >> >> Is there any downside observed to set CONFIG_PCP_BATCH_SCALE_MAX to 0 in
>> >> >> >> your environment? If not, I suggest to use 0 as default for
>> >> >> >> CONFIG_PCP_BATCH_SCALE_MAX. Because we have clear evidence that
>> >> >> >> CONFIG_PCP_BATCH_SCALE_MAX hurts latency for some workloads. After
>> >> >> >> that, if someone found some other workloads need larger
>> >> >> >> CONFIG_PCP_BATCH_SCALE_MAX, we can make it tunable dynamically.
>> >> >> >>
>> >> >> >
>> >> >> > The decision doesn’t rest with us, the kernel team at our company.
>> >> >> > It’s made by the system administrators who manage a large number of
>> >> >> > servers. The latency spikes only occur on the Kubernetes (k8s)
>> >> >> > servers, not in other environments like big data servers. We have
>> >> >> > informed other system administrators, such as those managing the big
>> >> >> > data servers, about the latency spike issues, but they are unwilling
>> >> >> > to make the change.
>> >> >> >
>> >> >> > No one wants to make changes unless there is evidence showing that the
>> >> >> > old settings will negatively impact them. However, as you know,
>> >> >> > latency is not a critical concern for big data; throughput is more
>> >> >> > important. If we keep the current settings, we will have to release
>> >> >> > different kernel packages for different environments, which is a
>> >> >> > significant burden for us.
>> >> >>
>> >> >> Totally understand your requirements. And, I think that this is better
>> >> >> to be resolved in your downstream kernel. If there are clear evidences
>> >> >> to prove small batch number hurts throughput for some workloads, we can
>> >> >> make the change in the upstream kernel.
>> >> >>
>> >> >
>> >> > Please don't make this more complicated. We are at an impasse.
>> >> >
>> >> > The key issue here is that the upstream kernel has a default value of
>> >> > 5, not 0. If you can change it to 0, we can persuade our users to
>> >> > follow the upstream changes. They currently set it to 5, not because
>> >> > you, the author, chose this value, but because it is the default in
>> >> > Linus's tree. Since it's in Linus's tree, kernel developers worldwide
>> >> > support it. It's not just your decision as the author, but the entire
>> >> > community supports this default.
>> >> >
>> >> > If, in the future, we find that the value of 0 is not suitable, you'll
>> >> > tell us, "It is an issue in your downstream kernel, not in the
>> >> > upstream kernel, so we won't accept it." PANIC.
>> >>
>> >> I don't think so. I suggest you to change the default value to 0. If
>> >> someone reported that his workloads need some other value, then we have
>> >> evidence that different workloads need different value. At that time,
>> >> we can suggest to add an user tunable knob.
>> >>
>> >
>> > The problem is that others are unaware we've set it to 0, and I can't
>> > constantly monitor the linux-mm mailing list. Additionally, it's
>> > possible that you can't always keep an eye on it either.
>>
>> IIUC, they will use the default value. Then, if there is any
>> performance regression, they can report it.
>
> Now we report it. What is your replyment? "Keep it in your downstream
> kernel." Wow, PANIC again.
This is not all of my reply. I suggested you to change the default
value too.
>
>>
>> > I believe we should hear Andrew's suggestion. Andrew, what is your opinion?
>>
--
Best Regards,
Huang, Ying
next prev parent reply other threads:[~2024-07-29 6:18 UTC|newest]
Thread overview: 14+ messages / expand[flat|nested] mbox.gz Atom feed top
2024-07-29 2:35 [PATCH v2 0/3] mm: " Yafang Shao
2024-07-29 2:35 ` [PATCH v2 1/3] mm/page_alloc: A minor fix to the calculation of pcp->free_count Yafang Shao
2024-07-29 2:35 ` [PATCH v2 2/3] mm/page_alloc: Avoid changing pcp->high decaying when adjusting CONFIG_PCP_BATCH_SCALE_MAX Yafang Shao
2024-07-29 2:35 ` [PATCH v2 3/3] mm/page_alloc: Introduce a new sysctl knob vm.pcp_batch_scale_max Yafang Shao
2024-07-29 3:18 ` Huang, Ying
2024-07-29 3:40 ` Yafang Shao
2024-07-29 5:12 ` Huang, Ying
2024-07-29 5:45 ` Yafang Shao
2024-07-29 5:50 ` Huang, Ying
2024-07-29 6:00 ` Yafang Shao
2024-07-29 6:00 ` Huang, Ying
2024-07-29 6:13 ` Yafang Shao
2024-07-29 6:14 ` Huang, Ying [this message]
2024-07-29 7:50 ` Yafang Shao
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