On Mon 02-04-18 09:24:22, Buddy Lumpkin wrote:Page replacement is handled in the Linux Kernel in one of two ways:
1) Asynchronously via kswapd
2) Synchronously, via direct reclaim
At page allocation time the allocating task is immediately given a page
from the zone free list allowing it to go right back to work doing
whatever it was doing; Probably directly or indirectly executing business
logic.
Just prior to satisfying the allocation, free pages is checked to see if
it has reached the zone low watermark and if so, kswapd is awakened.
Kswapd will start scanning pages looking for inactive pages to evict to
make room for new page allocations. The work of kswapd allows tasks to
continue allocating memory from their respective zone free list without
incurring any delay.
When the demand for free pages exceeds the rate that kswapd tasks can
supply them, page allocation works differently. Once the allocating task
finds that the number of free pages is at or below the zone min watermark,
the task will no longer pull pages from the free list. Instead, the task
will run the same CPU-bound routines as kswapd to satisfy its own
allocation by scanning and evicting pages. This is called a direct reclaim.
The time spent performing a direct reclaim can be substantial, often
taking tens to hundreds of milliseconds for small order0 allocations to
half a second or more for order9 huge-page allocations. In fact, kswapd is
not actually required on a linux system. It exists for the sole purpose of
optimizing performance by preventing direct reclaims.
When memory shortfall is sufficient to trigger direct reclaims, they can
occur in any task that is running on the system. A single aggressive
memory allocating task can set the stage for collateral damage to occur in
small tasks that rarely allocate additional memory. Consider the impact of
injecting an additional 100ms of latency when nscd allocates memory to
facilitate caching of a DNS query.
The presence of direct reclaims 10 years ago was a fairly reliable
indicator that too much was being asked of a Linux system. Kswapd was
likely wasting time scanning pages that were ineligible for eviction.
Adding RAM or reducing the working set size would usually make the problem
go away. Since then hardware has evolved to bring a new struggle for
kswapd. Storage speeds have increased by orders of magnitude while CPU
clock speeds stayed the same or even slowed down in exchange for more
cores per package. This presents a throughput problem for a single
threaded kswapd that will get worse with each generation of new hardware.
AFAIR we used to scale the number of kswapd workers many years ago. Itjust turned out to be not all that great. We have a kswapd reclaimwindow for quite some time and that can allow to tune how much proactivekswapd should be.
Are you referring to vm.watermark_scale_factor? This helps quite a bit. Previously
I had to increase min_free_kbytes in order to get a larger gap between the low
and min watemarks. I was very excited when saw that this had been added
upstream.
Also please note that the direct reclaim is a way to throttle overly
aggressive memory consumers.
I totally agree, in fact I think this should be the primary role of direct reclaims
because they have a substantial impact on performance. Direct reclaims are
the emergency brakes for page allocation, and the case I am making here is
that they used to only occur when kswapd had to skip over a lot of pages.
This changed over time as the rate a system can allocate pages increased.
Direct reclaims slowly became a normal part of page replacement.
The more we do in the background context
the easier for them it will be to allocate faster. So I am not really
sure that more background threads will solve the underlying problem. It
is just a matter of memory hogs tunning to end in the very same
situtation AFAICS. Moreover the more they are going to allocate the more
less CPU time will _other_ (non-allocating) task get.
The important thing to realize here is that kswapd and direct reclaims run the
same code paths. There is very little that they do differently. If you compare
my test results with one kswapd vs four, your an see that direct reclaims
increase the kernel mode CPU consumption considerably. By dedicating
more threads to proactive page replacement, you eliminate direct reclaims
which reduces the total number of parallel threads that are spinning on the
CPU.
Test Details
I will have to study this more to comment.[...]By increasing the number of kswapd threads, throughput increased by ~50%
while kernel mode CPU utilization decreased or stayed the same, likely due
to a decrease in the number of parallel tasks at any given time doing page
replacement.
Well, isn't that just an effect of more work being done on behalf ofother workload that might run along with your tests (and which doesn'treally need to allocate a lot of memory)? In other words howdoes the patch behaves with a non-artificial mixed workloads?
It works great. I will have results to share very soon.
Please note that I am not saying that we absolutely have to stick with the
current single-thread-per-node implementation but I would really like to
see more background on why we should be allowing heavy memory hogs to
allocate faster or how to prevent that.
My test results demonstrate the problem very well. It shows that a handful of
SSDs can create enough demand for kswapd that it consumes ~100% CPU
long before throughput is able to reach it’s peak. Direct reclaims start occurring
at that point. Aggregate throughput continues to increase, but eventually the
pauses generated by the direct reclaims cause throughput to plateau:
Test #3: 1 kswapd thread per node
dd sy dd_cpu kswapd0 kswapd1 throughput dr pgscan_kswapd pgscan_direct
10 4 26.07 28.56 27.03 7355924.40 0 459316976 0
16 7 34.94 69.33 69.66 10867895.20 0 872661643 0
22 10 36.03 93.99 99.33 13130613.60 489 1037654473 11268334
28 10 30.34 95.90 98.60 14601509.60 671 1182591373 15429142
34 14 34.77 97.50 99.23 16468012.00 10850 1069005644 249839515
40 17 36.32 91.49 97.11 17335987.60 18903 975417728 434467710
46 19 38.40 90.54 91.61 17705394.40 25369 855737040 582427973
52 22 40.88 83.97 83.70 17607680.40 31250 709532935 724282458
58 25 40.89 82.19 80.14 17976905.60 35060 657796473 804117540
64 28 41.77 73.49 75.20 18001910.00 39073 561813658 895289337
70 33 45.51 63.78 64.39 17061897.20 44523 379465571 1020726436
76 36 46.95 57.96 60.32 16964459.60 47717 291299464 1093172384
82 39 47.16 55.43 56.16 16949956.00 49479 247071062 1134163008
88 42 47.41 53.75 47.62 16930911.20 51521 195449924 1180442208
90 43 47.18 51.40 50.59 16864428.00 51618 190758156 1183203901
I would be also very interested
to see how to scale the number of threads based on how CPUs are utilized
by other workloads.
I think we have reached the point where it makes sense for page replacement to have more
than one mode. Enterprise class servers with lots of memory and a large number of CPU
cores would benefit heavily if more threads could be devoted toward proactive page
replacement. The polar opposite case is my Raspberry PI which I want to run as efficiently
as possible. This problem is only going to get worse. I think it makes sense to be able to
choose between efficiency and performance (throughput and latency reduction).
--
Michal Hocko
SUSE Labs
