File: README.benchmarks

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The first comparison is that of a linux kernel tarball (2.6.37). In all cases
the default options were used. 4 other common compression apps were used for
comparison, 7z which is an excellent all-round lzma based compression app,
gzip which is the benchmark fast standard that has good compression, and bzip2
which is the most common linux used compression. xz was included for
completeness.

In the following tables, lrzip means lrzip default options, lrzip -l means
lrzip using the lzo backend, lrzip -g means using the gzip backend,
lrzip -b means using the bzip2 backend and lrzip -z means using the zpaq
backend.


linux-2.6.37.tar

These are benchmarks performed on a 3GHz quad core Intel Core2 with 8GB ram
using lrzip v0.612 on an SSD drive.

Compression	Size		Percentage	Compress	Decompress
None		430612480	100
7z		63636839	14.8		2m28s		0m6.6s
xz		63291156	14.7		4m02s		0m8.7
lrzip		64561485	14.9		1m12s		0m4.3s
lrzip -z	51588423	12.0		2m02s		2m08s
lrzip -l	137515997	31.9		0m14s		0m2.7s
lrzip -g	86142459	20.0		0m17s		0m3.0s
lrzip -b	72103197	16.7		0m21s		0m6.5s
bzip2		74060625	17.2		0m48s		0m12.8s
gzip		94512561	21.9		0m17s		0m4.0s


These results are interesting to note the compression of lrzip by default is
about the same as 7z, but it's significantly faster thanks to its heavily
multithreaded nature. Zpaq offers by far the best compression but at the cost
of extra time. However with the heavily threaded nature of lrzip, it's not a lot
longer given how much better its compression is. It's actually faster than xz
on compression on a quad core machine.


Let's take six kernel trees one version apart as a tarball, linux-2.6.31 to
linux-2.6.36. These will show lots of redundant information, but hundreds
of megabytes apart, which lrzip will be very good at compressing. For
simplicity, only 7z will be compared since that's by far the best general
purpose compressor at the moment:

These are benchmarks performed on a 2.53Ghz dual core Intel Core2 with 4GB ram
using lrzip v0.5.1. Note that it was running with a 32 bit userspace so only
2GB addressing was posible. However the benchmark was run with the -U option
allowing the whole file to be treated as one large compression window.

Tarball of 6 consecutive kernel trees.

Compression	Size		Percentage	Compress	Decompress
None		2373713920	100
7z		344088002	14.5		17m26s		1m22s
lrzip		104874109	4.4		11m37s		56s
lrzip -l	223130711	9.4		05m21s		1m01s
lrzip -U	73356070	3.1		08m53s		43s
lrzip -Ul	158851141	6.7		04m31s		35s
lrzip -Uz	62614573	2.6		24m42s		25m30s

Things start getting very interesting now when lrzip is really starting to
shine. Note how it's not that much larger for 6 kernel trees than it was for
one. That's because all the similar data in both kernel trees is being
compressed as one copy and only the differences really make up the extra size.
All compression software does this, but not over such large distances. If you
copy the same data over multiple times, the resulting lrzip archive doesn't
get much larger at all. You might find this example interesting because the
-U option is actually faster as well as providing better compression. The
reason is that the window is not much larger than the amount of ram addressable
(2GB), and it compresses so much more in the rzip stage that it makes up the
time by not needing to compress anywhere near as much data with the backend
compressor.


Using the first example (linux-2.6.31.tar) and simply copying the data multiple
times over gives these results with lrzip(lzo):

Copies		Size		Compressed	Compress	Decompress
1		365711360	112151676	0m14.9s		0m5.1s
2		731422720	112151829	0m16.2s		0m6.5s
3		1097134080	112151832	0m17.5s		0m8.1s


I had the amusing thought that this compression software could be used as a
bullshit detector if you were to compress people's speeches because if their
talks were full of catchphrases and not much actual content, it would all be
compressed down. So the larger the final archive, the less bullshit =)

Now let's move on to the other special feature of lrzip, the ability to
compress massive amounts of data on huge ram machines by using massive
compression windows. This is a 10GB virtual image of an installed operating
system and some basic working software on it. The default options on the
8GB machine meant that it was using a 5 GB window.


10GB Virtual image:

These benchmarks were done on the quad core with version 0.612

Compression	Size		Percentage	Compress Time	Decompress Time
None		10737418240	100.0
gzip		2772899756	 25.8		05m47s		2m46s
bzip2		2704781700	 25.2		16m15s		6m19s
xz		2272322208	 21.2		50m58s		3m52s
7z		2242897134	 20.9		26m36s		5m41s
lrzip		1372218189	 12.8		10m23s		2m53s
lrzip -U	1095735108	 10.2		08m44s		2m45s
lrzip -l	1831894161	 17.1		04m53s		2m37s
lrzip -lU	1414959433	 13.2		04m48s		2m38s
lrzip -zU	1067169419	  9.9		39m32s		39m46s


At this end of the spectrum things really start to heat up. The compression
advantage is massive, with the lzo backend even giving much better results than
7z, and over a ridiculously short time. The improvements in version 0.530 in
scalability with multiple CPUs has a huge impact on compression time here,
with zpaq almost being faster on quad core than xz is, yet producing a file
less than half the size.

What appears to be a big disappointment is actually zpaq here which takes more
than 4 times longer than r/lzma for a measly .3% improvement. The reason is that
most of the advantage here is achieved by the rzip first stage since there's a
lot of redundant space over huge distances on a virtual image. The -U option
which works the memory subsystem rather hard making noticeable impact on the
rest of the machine also does further wonders for the compression (virtually
always) and even the times in this particular case.


Finally testing the same 10GB image on a i7-3930K at 3.2GHz (12 thread CPU!)
with 32GB of ram so the whole image fits in ram with a fast SSD:

Compression	Size		Percentage	Compress Time	Decompress Time
None		10737418240	100.0
gzip		2772899756	 25.8		3m56s		2m15s
pbzip2		2705814394	 25.2		1m41s		1m46s
lrzip		1095337763	 10.2		2m54s		2m21s


Note that with enough ram and CPU, lrzip is actually faster than gzip (which
does compression in place) and comparable on decompression, despite a huge
increase in compression. pbzip2 is faster than both but its compression is
almost no better than gzip.


This should help govern what compression you choose. Small files are nicely
compressed with zpaq. Intermediate files are nicely compressed with lzma.
Large files get excellent results even with lzo provided you have enough ram.
(Small being < 100MB, intermediate <1GB, large >1GB).
Or, to make things easier, just use the default settings all the time and be
happy as lzma gives good results. :D

Con Kolivas
Saturday, 7th July 2012