DragonFly On-Line Manual Pages
SWAPCACHE(8) DragonFly System Manager's Manual SWAPCACHE(8)
swapcache - a mechanism to use fast swap to cache filesystem data and
swapcache is a system capability which allows a solid state disk (SSD) in
a swap space configuration to be used to cache clean filesystem data and
meta-data in addition to its normal function of backing anonymous memory.
Sysctls are used to manage operational parameters and can be adjusted at
any time. Typically a large initial burst is desired after system boot,
controlled by the initial vm.swapcache.curburst parameter. This
parameter is reduced as data is written to swap by the swapcache and
increased at a rate specified by vm.swapcache.accrate. Once this
parameter reaches zero write activity ceases until it has recovered
sufficiently for write activity to resume.
vm.swapcache.meta_enable enables the writing of filesystem meta-data to
the swapcache. Filesystem metadata is any data which the filesystem
accesses via the disk device using buffercache. Meta-data is cached
globally regardless of file or directory flags.
vm.swapcache.data_enable enables the writing of clean filesystem file-
data to the swapcache. Filesystem filedata is any data which the
filesystem accesses via a regular file. In technical terms, when the
buffer cache is used to access a regular file through its vnode. Please
do not blindly turn on this option, see the PERFORMANCE TUNING section
for more information.
vm.swapcache.use_chflags enables the use of the cache and noscache
chflags(1) flags to control which files will be data-cached. If this
sysctl is disabled and data_enable is enabled, the system will ignore
file flags and attempt to swapcache all regular files.
vm.swapcache.read_enable enables reading from the swapcache and should be
set to 1 for normal operation.
vm.swapcache.maxfilesize controls which files are to be cached based on
their size. If set to non-zero only files smaller than the specified
size will be cached. Larger files will not be cached.
vm.swapcache.maxlaunder controls the maximum number of clean VM pages
which will be added to the swap cache and written out to swap on each
poll. Swapcache polls ten times a second.
vm.swapcache.hysteresis controls how many pages swapcache waits to be
added to the inactive page queue before continuing its scan. Once it
decides to scan it continues subject to the above limitations until it
reaches the end of the inactive page queue. This parameter is designed
to make swapcache generate more bulky bursts to swap which helps SSDs
reduce write amplification effects.
Best operation is achieved when the active data set fits within the
This specifies the burst accumulation rate in bytes per second and
ultimately controls the write bandwidth to swap averaged over a
long period of time. This parameter must be carefully chosen to
manage the write endurance of the SSD in order to avoid wearing it
out too quickly. Even though SSDs have limited write endurance,
there is massive cost/performance benefit to using one in a
Let's use the old Intel X25V 40GB MLC SATA SSD as an example. This
device has approximately a 40TB (40 terabyte) write endurance, but
see later notes on this, it is more a minimum value. Limiting the
long term average bandwidth to 100KB/sec leads to no more than
~9GB/day writing which calculates approximately to a 12 year
endurance. Endurance scales linearly with size. The 80GB version
of this SSD will have a write endurance of approximately 80TB.
MLC SSDs have a 1000-10000x write endurance, while the lower
density higher-cost SLC SSDs have a 10000-100000x write endurance,
approximately. MLC SSDs can be used for the swapcache (and swap)
as long as the system manager is cognizant of its limitations.
However, over the years tests have shown the SLC SSDs do not really
live up to their hype and are no more reliable than MLC SSDs.
Instead of worrying about SLC vs MLC, just use MLC (or TLC or
whateve), leave more space unpartitioned which the SSD can utilize
to improve durability, and be cognizant of the SSDs rate of wear.
Turning on just meta_enable causes only filesystem meta-data to be
cached and will result in very fast directory operations even over
millions of inodes and even in the face of other invasive
operations being run by other processes.
For HAMMER filesystems meta-data includes the B-Tree, directory
entries, and data related to tiny files. Approximately 6 GB of
swapcache is needed for every 14 million or so inodes cached,
effectively giving one the ability to cache all the meta-data in a
multi-terabyte filesystem using a fairly small SSD.
Turning on data_enable (with or without other features) allows bulk
file data to be cached. This feature is very useful for web server
operation when the operational data set fits in swap. However,
care must be taken to avoid thrashing the swapcache. In almost all
cases you will want to leave chflags mode enabled and use 'chflags
cache' on governing directories to control which directory subtrees
file data should be cached for.
DragonFly uses generously large kern.maxvnodes values, typically in
excess of 400K vnodes, but large numbers of small files can still
cause problems for swapcache. When operating on a filesystem
containing a large number of small files, vnode recycling by the
kernel will cause related swapcache data to be lost and also cause
the swapcache to potentially thrash. Cache thrashing due to vnode
recyclement can occur whether chflags mode is used or not.
To solve the thrashing problem you can turn on HAMMER's double
buffering feature via vfs.hammer.double_buffer. This causes HAMMER
to cache file data via its block device. HAMMER cannot avoid also
caching file data via individual vnodes but will try to expire the
second copy more quickly (hence why it is called double buffer
mode), but the key point here is that swapcache will only cache the
data blocks via the block device when double_buffer mode is used
and since the block device is associated with the mount, vnode
recycling will not mess with it. This allows the data for any
number (potentially millions) of files to be swapcached. You still
should use chflags mode to control the size of the dataset being
cached to remain under 75% of configured swap space.
Data caching is definitely more wasteful of the SSD's write
durability than meta-data caching. If not carefully managed the
swapcache may exhaust its burst and smack against the long term
average bandwidth limit, causing the SSD to wear out at the maximum
rate you programmed. Data caching is far less wasteful and more
efficient if you provide a sufficiently large SSD.
When caching large data sets you may want to use a medium-sized SSD
with good write performance instead of a small SSD to accommodate
the higher burst write rate data caching incurs and to reduce
interference between reading and writing. Write durability also
tends to scale with larger SSDs, but keep in mind that newer flash
technologies use smaller feature sizes on-chip which reduce the
write durability of the chips, so pay careful attention to the type
of flash employed by the SSD when making durability assumptions.
For example, an Intel X25-V only has 40MB/s in write performance
and burst writing by swapcache will seriously interfere with
concurrent read operation on the SSD. The 80GB X25-M on the
otherhand has double the write performance. Higher-capacity and
larger form-factor SSDs tend to have better write-performance. But
the Intel 310 series SSDs use flash chips with a smaller feature
size so an 80G 310 series SSD will wind up with a durability
relative close to the older 40G X25-V.
When data caching is turned on you can fine-tune what gets
swapcached by also turning on swapcache's chflags mode and using
chflags(1) with the cache flag to enable data caching on a
directory-tree (recursive) basis. This flag is tracked by the
namecache and does not need to be recursively set in the directory
tree. Simply setting the flag in a top level directory or mount
point is usually sufficient. However, the flag does not track
across mount points. A typical setup is something like this:
chflags cache /etc /sbin /bin /usr /home
chflags noscache /usr/obj
It is possible to tell swapcache to ignore the cache flag by
leaving vm.swapcache.use_chflags set to zero. In many situations
it is convenient to simply not use chflags mode, but if you have
numerous mixed SSDs and HDDs you may want to use this flag to
enable swapcache on the HDDs and disable it on the SSDs even if you
do not care about fine-grained control. chflag'ing.
Filesystems such as NFS which do not support flags generally have a
cache mount option which enables swapcache operation on the mount.
This may be used to reduce cache thrashing when a focus on a small
potentially fragmented filespace is desired, leaving the larger
(more linearly accessed) files alone.
This controls hysteresis and prevents nickel-and-dime write
bursting. Once curburst drops to zero, writing to the swapcache
ceases until it has recovered past minburst. The idea here is to
avoid creating a heavily fragmented swapcache where reading data
from a file must alternate between the cache and the primary
filesystem. Doing so does not save disk seeks on the primary
filesystem so we want to avoid doing small bursts. This parameter
allows us to do larger bursts. The larger bursts also tend to
improve SSD performance as the SSD itself can do a better job
write-combining and erasing blocks.
This controls the maximum amount of swapspace swapcache may use, in
percentage terms. The default is 75%, leaving the remaining 25% of
swap available for normal paging operations.
It is important to ensure that your swap partition is nicely aligned.
The standard DragonFly disklabel(8) program guarantees high alignment
(~1MB) automatically. Swap-on HDDs benefit because HDDs tend to use a
larger physical sector size than 512 bytes, and proper alignment for SSDs
will reduce write amplification and write-combining inefficiencies.
Finally, interleaved swap (multiple SSDs) may be used to increase swap
and swapcache performance even further. A single SATA-II SSD is
typically capable of reading 120-220MB/sec. Configuring two SSDs for
your swap will improve aggregate swapcache read performance by 1.5x to
1.8x. In tests with two Intel 40GB SSDs 300MB/sec was easily achieved.
With two SATA-III SSDs it is possible to achieve 600MB/sec or better and
well over 400MB/sec random-read performance (versus the ~3MB/sec random
read performance a hard drive gives you). Faster SATA interfaces or
newer NVMe technologies have significantly more read bandwidth (3GB/sec+
for NVMe), but may still lag on the write bandwidth. With newer
technologies, one swap device is usually plenty.
DragonFly defaults to a maximum of 512G of configured swap. Keep in mind
that each 1GB of actually configured swap requires approximately 1MB of
wired ram to manage.
In addition there will be periods of time where the system is in steady
state and not writing to the swapcache. During these periods curburst
will inch back up but will not exceed maxburst. Thus the maxburst value
controls how large a repeated burst can be. Remember that curburst
dynamically tracks burst and will go up and down depending.
A second bursting parameter called vm.swapcache.minburst controls
bursting when the maximum write bandwidth has been reached. When
minburst reaches zero write activity ceases and curburst is allowed to
recover up to minburst before write activity resumes. The recommended
range for the minburst parameter is 1MB to 50MB. This parameter has a
relationship to how fragmented the swapcache gets when not in a steady
state. Large bursts reduce fragmentation and reduce incidences of
excessive seeking on the hard drive. If set too low the swapcache will
become fragmented within a single regular file and the constant back-and-
forth between the swapcache and the hard drive will result in excessive
seeking on the hard drive.
SWAPCACHE SIZE & MANAGEMENT
The swapcache feature will use up to 75% of configured swap space by
default. The remaining 25% is reserved for normal paging operations.
The system operator should configure at least 4 times the SWAP space
versus main memory and no less than 8GB of swap space. A typical 128GB
SSD might use 64GB for boot + base and 56GB for swap, with 8GB left
unpartitioned. The system might then have a large additional hard drive
for bulk data. Even with many packages installed, 64GB is comfortable
for boot + base.
When configuring a SSD that will be used for swap or swapcache it is a
good idea to leave around 10% unpartitioned to improve the SSDs
You do not need to use swapcache if you have no hard drives in the
system, though in fact swapcache can help if you use NFS heavily as a
The vm_swapcache.maxswappct sysctl may be used to change the default.
You may have to change this default if you also use tmpfs(5), vn(4), or
if you have not allocated enough swap for reasonable normal paging
activity to occur (in which case you probably shouldn't be using
If swapcache reaches the 75% limit it will begin tearing down swap in
linear bursts by iterating through available VM objects, until swap space
use drops to 70%. The tear-down is limited by the rate at which new data
is written and this rate in turn is often limited by
vm.swapcache.accrate, resulting in an orderly replacement of cached data
and meta-data. The limit is typically only reached when doing full
data+meta-data caching with no file size limitations and serving
primarily large files, or bumping kern.maxvnodes up to very high values.
NORMAL SWAP PAGING ACTIVITY WITH SSD SWAP
This is not a function of swapcache per se but instead a normal function
of the system. Most systems have sufficient memory that they do not need
to page memory to swap. These types of systems are the ones best suited
for MLC SSD configured swap running with a swapcache configuration.
Systems which modestly page to swap, in the range of a few hundred
megabytes a day worth of writing, are also well suited for MLC SSD
configured swap. Desktops usually fall into this category even if they
page out a bit more because swap activity is governed by the actions of a
Systems which page anonymous memory heavily when swapcache would
otherwise be turned off are not usually well suited for MLC SSD
configured swap. Heavy paging activity is not governed by swapcache
bandwidth control parameters and can lead to excessive uncontrolled
writing to the SSD, causing premature wearout. This isn't to say that
swapcache would be ineffective, just that the aggregate write bandwidth
required to support the system might be too large to be cost-effective
for a SSD.
With this caveat in mind, SSD based paging on systems with insufficient
RAM can be extremely effective in extending the useful life of the
system. For example, a system with a measly 192MB of RAM and SSD swap
can run a -j 8 parallel build world in a little less than twice the time
it would take if the system had 2GB of RAM, whereas it would take 5x to
10x as long with normal HDD based swap.
USING SWAPCACHE WITH NORMAL HARD DRIVES
Although swapcache is designed to work with SSD-based storage it can also
be used with HD-based storage as an aid for offloading the primary
storage system. Here we need to make a distinction between using RAID
for fanning out storage versus using RAID for redundancy. There are
numerous situations where RAID-based redundancy does not make sense.
A good example would be in an environment where the servers themselves
are redundant and can suffer a total failure without effecting ongoing
operations. When the primary storage requirements easily fit onto a
single large-capacity drive it doesn't make a whole lot of sense to use
RAID if your only desire is to improve performance. If you had a farm
of, say, 20 servers supporting the same facility adding RAID to each one
would not accomplish anything other than to bloat your deployment and
In these sorts of situations it may be desirable and convenient to have
the primary filesystem for each machine on a single large drive and then
use the swapcache facility to offload the drive and make the machine more
effective without actually distributing the filesystem itself across
multiple drives. For the purposes of offloading while a SSD would be the
most effective from a performance standpoint, a second medium sized HD
with its much lower cost and higher capacity might actually be more cost
EXPLANATION OF STATIC VS DYNAMIC WEARING LEVELING, AND WRITE-COMBINING
Modern SSDs keep track of space that has never been written to. This
would also include space freed up via TRIM, but simply not touching a bit
of storage in a factory fresh SSD works just as well. Once you touch
(write to) the storage all bets are off, even if you reformat/repartition
later. It takes sending the SSD a whole-device TRIM command or special
format command to take it back to its factory-fresh condition (sans wear
SSDs have wear leveling algorithms which are responsible for trying to
even out the erase/write cycles across all flash cells in the storage.
The better a job the SSD can do the longer the SSD will remain usable.
The more unused storage there is from the SSDs point of view the easier a
time the SSD has running its wear leveling algorithms. Basically the
wear leveling algorithm in a modern SSD (say Intel or OCZ) uses a
combination of static and dynamic leveling. Static is the best, allowing
the SSD to reuse flash cells that have not been erased very much by
moving static (unchanging) data out of them and into other cells that
have more wear. Dynamic wear leveling involves writing data to available
flash cells and then marking the cells containing the previous copy of
the data as being free/reusable. Dynamic wear leveling is the worst kind
but the easiest to implement. Modern SSDs use a combination of both
algorithms plus also do write-combining.
USB sticks often use only dynamic wear leveling and have short life spans
because of that.
In anycase, any unused space in the SSD effectively makes the dynamic
wear leveling the SSD does more efficient by giving the SSD more 'unused'
space above and beyond the physical space it reserves beyond its stated
storage capacity to cycle data through, so the SSD lasts longer in
Write-combining is a feature whereby the SSD is able to reduced write
amplification effects by combining OS writes of smaller, discrete, non-
contiguous logical sectors into a single contiguous 128KB physical flash
On the flip side write-combining also results in more complex lookup
tables which can become fragmented over time and reduce the SSDs read
performance. Fragmentation can also occur when write-combined blocks are
rewritten piecemeal. Modern SSDs can regain the lost performance by de-
combining previously write-combined areas as part of their static wear
leveling algorithm, but at the cost of extra write/erase cycles which
slightly increase write amplification effects. Operating systems can
also help maintain the SSDs performance by utilizing larger blocks.
Write-combining results in a net-reduction of write-amplification effects
but due to having to de-combine later and other fragmentary effects it
isn't 100%. From testing with Intel devices write-amplification can be
well controlled in the 2x-4x range with the OS doing 16K writes, versus a
worst-case 8x write-amplification with 16K blocks, 32x with 4K blocks,
and a truly horrid worst-case with 512 byte blocks.
The DragonFly swapcache feature utilizes 64K-128K writes and is
specifically designed to minimize write amplification and write-combining
stresses. In terms of placing an actual filesystem on the SSD, the
DragonFly hammer(8) filesystem utilizes 16K blocks and is well behaved as
long as you limit reblocking operations. For UFS you should create the
filesystem with at least a 4K fragment size, versus the default 2K.
Modern Windows filesystems use 4K clusters but it is unclear how SSD-
friendly NTFS is.
EXPLANATION OF FLASH CHIP FEATURE SIZE VS ERASE/REWRITE CYCLE DURABILITY
Manufacturers continue to produce flash chips with smaller feature sizes.
Smaller flash cells means reduced erase/rewrite cycle durability which in
turn reduces the durability of the SSD.
The older 34nm flash typically had a 10,000 cell durability while the
newer 25nm flash is closer to 1000. The newer flash uses larger ECCs and
more sensitive voltage comparators on-chip to increase the durability
closer to 3000 cycles. Generally speaking you should assume a durability
of around 1/3 for the same storage capacity using the new chips versus
the older chips. If you can squeeze out a 400TB durability from an older
40GB X25-V using 34nm technology then you should assume around a 400TB
durability from a newer 120GB 310 series SSD using 25nm technology.
I am going to repeat and expand a bit on SSD wear. Wear on SSDs is a
function of the write durability of the cells, whether the SSD implements
static or dynamic wear leveling (or both), write amplification effects
when the OS does not issue write-aligned 128KB ops or when the SSD is
unable to write-combine adjacent logical sectors, or if the SSD has a
poor write-combining algorithm for non-adjacent sectors. In addition
some additional erase/rewrite activity occurs from cleanup operations the
SSD performs as part of its static wear leveling algorithms and its
write-decombining algorithms (necessary to maintain performance over
time). MLC flash uses 128KB physical write/erase blocks while SLC flash
typically uses 64KB physical write/erase blocks.
The algorithms the SSD implements in its firmware are probably the most
important part of the device and a major differentiator between e.g. SATA
and USB-based SSDs. SATA form factor drives will universally be far
superior to USB storage sticks. SSDs can also have wildly different
wearout rates and wildly different performance curves over time. For
example the performance of a SSD which does not implement write-
decombining can seriously degrade over time as its lookup tables become
severely fragmented. For the purposes of this manual page we are
primarily using Intel and OCZ drives when describing performance and wear
swapcache parameters should be carefully chosen to avoid early wearout.
For example, the Intel X25V 40GB SSD has a minimum write durability of
40TB and an actual durability that can be quite a bit higher. Generally
speaking, you want to select parameters that will give you at least 10
years of service life. The most important parameter to control this is
vm.swapcache.accrate. swapcache uses a very conservative 100KB/sec
default but even a small X25V can probably handle 300KB/sec of continuous
writing and still last 10 years.
Depending on the wear leveling algorithm the drive uses, durability and
performance can sometimes be improved by configuring less space (in a
manufacturer-fresh drive) than the drive's probed capacity. For example,
by only using 32GB of a 40GB SSD. SSDs typically implement 10% more
storage than advertised and use this storage to improve wear leveling.
As cells begin to fail this overallotment slowly becomes part of the
primary storage until it has been exhausted. After that the SSD has
basically failed. Keep in mind that if you use a larger portion of the
SSD's advertised storage the SSD will not know if/when you decide to use
less unless appropriate TRIM commands are sent (if supported), or a low
level factory erase is issued.
smartctl (from dports(7)'s sysutils/smartmontools) may be used to
retrieve the wear indicator from the drive. One usually runs something
like `smartctl -d sat -a /dev/daXX' (for AHCI/SILI/SCSI), or `smartctl -a
/dev/adXX' for NATA. Some SSDs (particularly the Intels) will brick the
SATA port when smart operations are done while the drive is busy with
normal activity, so the tool should only be run when the SSD is idle.
ID 232 (0xe8) in the SMART data dump indicates available reserved space
and ID 233 (0xe9) is the wear-out meter. Reserved space typically starts
at 100 and decrements to 10, after which the SSD is considered to operate
in a degraded mode. The wear-out meter typically starts at 99 and
decrements to 0, after which the SSD has failed.
swapcache tends to use large 64KB writes and tends to cluster multiple
writes linearly. The SSD is able to take significant advantage of this
and write amplification effects are greatly reduced. If we take a 40GB
Intel X25V as an example the vendor specifies a write durability of
approximately 40TB, but swapcache should be able to squeeze out upwards
of 200TB due the fairly optimal write clustering it does. The
theoretical limit for the Intel X25V is 400TB (10,000 erase cycles per
MLC cell, 40GB drive, with 34nm technology), but the firmware doesn't do
perfect static wear leveling so the actual durability is less. In tests
over several hundred days we have validated a write endurance greater
than 200TB on the 40G Intel X25V using swapcache.
In contrast, filesystems directly stored on a SSD could have fairly
severe write amplification effects and will have durabilities ranging
closer to the vendor-specified limit.
Tests have shown that power cycling (with proper shutdown) and read
operations do not adversely effect a SSD. Writing within the wearout
constraints provided by the vendor also does not make a powered SSD any
less reliable over time. Time itself seems to be a factor as the SSD
encounters defects and weak cells in the flash chips. Writes to a SSD
will effect cold durability (a typical flash chip has 10 years of cold
data retention when fresh and less than 1 year of cold data retention
near the end of its wear life). Keeping a SSD cool improves its data
Beware the standard comparison between SLC, MLC, and TLC-based flash in
terms of wearout and durability. Over the years, tests have shown that
SLC is not actually any more reliable than MLC, despite having a
significantly larger theoretical durability. Cell and chip failures seem
to trump theoretical wear limitations in terms of device reliability.
With that in mind, we do not recommend using SLC for anything anymore.
Instead we recommend that the flash simply be over-provisioned to provide
the needed durability. This is already done in numerous NVMe solutions
for the vendor to be able to provide certain minimum wear guarantees.
Durability scales with the amount of flash storage (but the fab process
typically scales the opposite... smaller feature sizes for flash cells
greatly reduce their durability). When wear calculations are in years,
these differences become huge, but often the quantity of storage needed
trumps the wear life so we expect most people will be using MLC.
Beware the huge difference between larger (e.g. 2.5") form-factor SSDs
and smaller SSDs such as USB sticks are very small M.2 storage. Smaller
form-factor devices have fewer flash chips and, much lower write
bandwidths, less ram for caching and write-combining, and usb sticks in
particular will usually have unsophisticated wear-leveling algorithms
compared to a 2.5" SSD. It is generally not a good idea to make a USB
stick your primary storage. Long-form-factor NGFF/M.2 devices will be
better, and 2.5" form factor devices even better. The read-bandwidth for
a SATA SSD caps out more quickly than the read-bandwidth for a NVMe SSD,
but the larger form factor of a 2.5" SATA SSD will often have superior
write performance to a NGFF NVMe device. There are 2.5" NVMe devices as
well, requiring a special connector or PCIe adapter, which give you the
best of both worlds.
chflags(1), fstab(5), disklabel64(8), hammer(8), swapon(8)
swapcache first appeared in DragonFly 2.5.
DragonFly 6.3-DEVELOPMENT February 7, 2010 DragonFly 6.3-DEVELOPMENT