Brotli Compression Algorithm Combines High Compression Ratio, and Fast Decompression

After Zopfli, Google has now announced and released Brotli, a new compression algorithm to make the web faster, with a ratio compression similar to LZMA, but a much faster decompression, making it ideal for low power mobile devices.

Compression Ratio vs Decompression Speed for LZMA, Bzip2, Brotli, Zopfli…

Contrary to Zopfli that is deflate compatible, Brotli is a complete new format, and combines “2nd order context modeling, re-use of entropy codes, larger memory window of past data and joint distribution codes” to achieve higher compression ratios.

Google published some benchmark results comparing Brotli to other common algorithms. Since the company aims to make the web faster, the target is to decrease both downloading time (high compression ratio), and rendering time (fast decompression speed), and Brotli with a quality set to 11 is much better than competitor once both parameters are taken into account.

As you’d expect the source code can also be pulled from Github. So I gave it a quick try myself in an Ubuntu PC, and installed it as follows:

The application usage info is not really detailed, but good enough to get started:

I was a little too optimistic at first, and started by compressing a 2.4GB firmware file using quality 11 with bro, but I quickly found out it would take a very long time, as the compression speed is rather slow… Google white paper shows Brotli compresses 0.5 MB of data per second when quality is set to 11, and they performed the test on a server powered by an Intel Xeon E5-1650 v2 running at 3.5 GHz…

So instead I switched to Linux 4.2 Changelog text file I created a few days ago that’s only 14MB in size.

My machine is based on an AMD FX8350 processor (8 cores @ 4.0 GHz), and it took about 46.6 second to compress the file.
Then I switched to xz which implements LZMA compression, and compression preset 9.

Compression speed is much faster with xz, about 7.5 times faster , but it’s not really a concern for Google, because in their use cases, the file is compressed once, but downloaded and decompressed millions of times. It’s also interesting to note that both tools only used one core to compress the file.

Let’s check the file sizes.

In my case, LZMA compression ratio was also slightly higher than Brotli compression ratio, but that’s only for one file, and Google’s much larger test sample (1,000+ files) shows a slight advantage to Brotli (11) over LZMA (9).

Decompression is much faster than compression in both cases:

Brotli is indeed considerably faster at decompressing than LZMA, about 3 times faster, just as reported in Google’s study.

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20 Replies to “Brotli Compression Algorithm Combines High Compression Ratio, and Fast Decompression”

  1. It’s worth noting that, unlike other compression algorithms, brotli uses a static dictionary based on common English, Spanish, HTML etc. That’s not a bad idea but it is sort-of cheating when you’re doing a comparison against other algorithms.

  2. @opk

    Why do you see it like cheating?
    If using a certain dictionary in certain applications proves to be useful, then this is a legitimate approach.

  3. Using the term quality to compress a video file with brotli, kind of thru me off… should be called compression strength or something like that, no?

  4. Groan, all i can see is someone rushing to use it for everything all of a sudden and “turning it up to 11”, although that compression speed needs a lot of work.

    I also wonder what the decompression memory requirements are (incl fixed overheads) and can it stream the process? And which of those tools isn’t honouring the umask properly – the generated file should have the same permissions.

    FWIW try adding overflow:auto to your pre style.

    Also a bummer threading isn’t utilised.

  5. @LinAdmin

    LZMA/deflate support custom preset dictionaries. It would’ve probably been fairer if a comparison was made with those algorithms using a similar preset dictionary.

    Another thing to note is that Brotli’s max dictionary size is 16MB, which is another facet which makes this algorithm very web focused (as opposed to a more general purpose algorithm like LZMA).

  6. Hi,
    a good review and good for us all if Brotli manages to boost the browsing.

    Please run your test with ‘dickens’ (from Silesia Corpus) too, it is one of the most used testdatafiles in compression community for a reason, it represents English texts in its fat book form (2 Bibles). Just use ‘-v’ option in order we all to see what is the Brotli’s decompression speed on your Vishera, on my old Core 2 laptop I reached 145 MB/s, for more info:

    Also, I shared my opinion with Brotli’s team about their current defaults and in short it still needs some tweaking and debugging. My superfast textual decompressor is 3x faster than Brotli on ‘dickens’ but yields:
    10,192,446 dickens
    03,740,418 dickens.Nakamichi
    02,962,118 dickens.brotli

    (3,740,418-2,962,118)/2,962,118*100= 26% less compression ratio.

    It would be interesting to see how AMD Vishera executes Brotli&Shifune on ‘dickens’, the C source code is here:

    You can compile it like that:
    gcc -O3 -fomit-frame-pointer Nakamichi_Shifune.c -o Nakamichi_Shifune.exe -D_N_XMM -D_N_prefetch_4096 -D_N_Branchfull

  7. @cnxsoft

    >I can test it, but could you provide the download link for dickens?
    Bravo, I very much want to see how “low caliber” CPUs execute them, ‘dickens’ is inhere:

    >A single script that I can run to provide the results you want would be even nicer.
    Sure, but I am lame in *nix prompt, so an “estimate” for *nix:

    Step #1: Download the whole package all-in-one:!c0hBkCYQ!U2irEQPbiig6xcUD0mXIVn7P-suzTcku6COKtkvKHmo
    Step #2: Download the C source:
    Step #3: Compile the C source: ./gcc -O3 -fomit-frame-pointer Nakamichi_Shifune.c -o Nakamichi_Shifune.elf -D_N_XMM -D_N_prefetch_4096 -D_N_Branchfull
    Step #4: ./Nakamichi_Shifune.elf dickens.Nakamichi /report

    Sorry for the burdensomeness, but my environment is Windows.

    By the way, one American overclocker was good enough and tested it on all modern (4960x, 5960x, 6600K) Intel CPUs:

    Also, the results in one picture:

  8. @Georgi Marinov (@Sanmayce)
    The showdown package is only for Windows.
    Nakamichi_Shifune won’t build:

    gcc -O3 -fomit-frame-pointer Nakamichi_Shifune.c -o Nakamichi_Shifune.elf -D_N_XMM -D_N_prefetch_4096 -D_N_Branchfull
    In file included from Nakamichi_Shifune.c:940:0:
    /usr/lib/gcc/x86_64-linux-gnu/4.8/include/smmintrin.h:31:3: error: #error “SSE4.1 instruction set not enabled”
    # error “SSE4.1 instruction set not enabled”

    Here are the results for brotli:

    time bro –quality 11 –input dickens –output dicken.bro –verbose
    Brotli compression speed: 0.284661 MB/s

    real 0m34.219s
    user 0m33.767s
    sys 0m0.383s
    jaufranc@FX8350:~/edev/sandbox/brotli$ time bro –decompress –input dicken.bro –output dicken.out –verbose
    Brotli decompression speed: 195.78 MB/s

    real 0m0.056s
    user 0m0.032s
    sys 0m0.020s

  9. @cnxsoft
    Oh, there is difference between GCC Windows and GCC Linux, maybe GCC is not fully installed.
    Just comment the line #940, SSE4.1 is actually not used just SSE2:

    938 #ifdef _N_XMM
    939 #include // SSE2 intrinsics
    //940 #include // SSE4.1 intrinsics
    941 #endif

    It should work this way.
    I was lazy to make time reporting portable enough:

    k = (((float)1000*TargetSize/(clocks2 – clocks1 + 1))); k=k>>20; k=k*Trials;
    printf(“RAM-to-RAM performance: %d MB/s.\n”, k);

    If clocks_per_sec is not 1000 as in Windows, the MB/s would be unusable.

    Anyway, thanks for your FX8350 result, 195MB/s is still far from my ~512MB/s obtained on Core 2 Q9550s @2.8GHz.

  10. @Georgi Marinov (@Sanmayce)
    The reporting does not seem to work that well on Linux…
    This is what I got:

  11. @cnxsoft

    Thank you for wrestling with my code 😉
    If you still care, just replace the ‘1000’ with ‘CLOCKS_PER_SEC’ in next three lines and voila:

    //k = (((float)1000*TargetSize/(clocks2 - clocks1 + 1))); k=k>>20; k=k*Trials;
    k = (((float)CLOCKS_PER_SEC*TargetSize/(clocks2 - clocks1 + 1))); k=k>>20; k=k*Trials;
    //k = (((float)1000*SourceSize/(clocks2 - clocks1 + 1))); //k=k>>10;
    k = (((float)CLOCKS_PER_SEC*SourceSize/(clocks2 - clocks1 + 1))); //k=k>>10;
    //j = (float)1000*1024*( 512 )/ ((int) durationGENERIC);
    j = (float)CLOCKS_PER_SEC*1024*( 512 )/ ((int) durationGENERIC);

    This is the dump from my MinGW console:

    D:\Internetdownloads\Nakamichi_Shifune>gcc --version
    gcc (x86_64-posix-seh-rev0, Built by MinGW-W64 project) 5.1.0
    Copyright (C) 2015 Free Software Foundation, Inc.
    This is free software; see the source for copying conditions. There is NO


    09/28/2015 02:53 PM 184,455 Nakamichi_Shifune.c

    D:\Internetdownloads\Nakamichi_Shifune>gcc -O3 -fomit-frame-pointer Nakamichi_Shifune.c -o Nakamichi_Shifune.exe -D_N_XMM -D_N_prefetch_4096 -D_N_Branchfull


    09/26/2015 11:41 PM 3,740,418 dickens.Nakamichi
    09/28/2015 02:53 PM 184,455 Nakamichi_Shifune.c
    09/28/2015 02:54 PM 63,597 Nakamichi_Shifune.exe

    D:\Internetdownloads\Nakamichi_Shifune>Nakamichi_Shifune.exe dickens.Nakamichi /report
    Nakamichi 'Shifune-Totenschiff', written by Kaze, based on Nobuo Ito's LZSS source, babealicious suggestion by m^2 enforced, muffinesque suggestion by Jim Dempsey enforced.
    Decompressing 3740418 bytes ...
    RAM-to-RAM performance: 512 MB/s.
    Memory pool starting address: 0000000000980080 ... 64 byte aligned, OK
    Copying a 512MB block 1024 times i.e. 512GB READ + 512GB WRITTEN ...
    memcpy(): (512MB block); 524288MB copied in 210495 clocks or 2.491MB per clock
    RAM-to-RAM performance vs memcpy() ratio (bigger-the-better): 20%


    By the way, have you asked yourself why the Brotli team used XEON worth $560 when one WHOLE mobile system, say AMD Carrizo, can be bought. I mean, most people (poor like me) would benefit Brotli and alike from ‘low caliber’ CPUs.
    I very much want to see how mobile CPUs likee Atom Silvermont and AMD perform such decompression.

    I asked a similar question on ‘Hacker News’ and one guy listed many top performers with their decompression time:

  12. @Georgi Marinov (@Sanmayce)

  13. @Georgi Marinov (@Sanmayce)
    If you want mobile device top of performance, I’ve just tested both tools on the Orange Pi 2 mini board (ARM Cortex A7 @ 1.5GHz) I have on my desk.

    I stopped your test after 20 minutes as it still had not completed the first part (stuck at Decompressing 3740418 bytes …), and I’ll go to bed now… 🙂

    I can see the x86 code uses SSE instructions, so unless there’s also some NEON implementation in your code, it would mean everything is done with the CPU on ARM…

  14. Oh man, these lilliput machines are so exciting!
    I know next to nothing about ARM, yet I see that v7 has 32bit registers whereas v8 has already 64bit, this will hurt Shifune’s decoding speed.

    The price is lovable, just for me.

    To avoid waiting the ‘memcpy()’ mumbo-jumbo segment, it can be skipped by adding ‘BandwidthFlag=0;’ that way:

    if (BandwidthFlag) {
    // Benchmark memcpy() [

    Please run it again, these little scamps are so sweet&cheap.

    By the way, by chance I have become the author of fastest hash function (for table lookups), called FNV1a-YoshimitsuTRIAD, with supremacy especially on ARM:

    CortexA8 1 thread@720 Mhz L1 cache

    Codec version speed (MB/s)
    FNV1a-YoshimitsuTRIAD 2013-05-12 1021.79
    fletcher2 2010 834.93
    FNV1a-Jesteress 2013-05-12 682.55
    xxhash r29 520.19
    murmur3_x86_128 2012-02-29 303.36
    SpookyHash V2 2012-08-05 229.25

    Just to swag a bit, 2x faster than the superb xxhash, heh-heh.

  15. @cnxsoft
    Ugh, stupid of me, you said that it stuck still decompressing, don’t know what is the cause, maybe the XMM macro is the culprit, you could comment it and put below it standard memcpy() as below:

    #ifdef _N_XMM
    //SlowCopy128bit( (const char *)( (uint64_t)(srcLOCAL+1) ), retLOCAL );
    memcpy(retLOCAL, (const char *)( (uint64_t)(srcLOCAL+1) ), 16);

    Being little endian (as x86) it should work.

  16. @cnxsoft
    >I had only compiled the code with:
    >gcc -O3 -fomit-frame-pointer Nakamichi_Shifune.c -o Nakamichi_Shifune.elf
    >maybe that’s why it looped.

    If this was the full compile line no wonder, you cannot omit ‘-D_N_XMM’, it should be like this:

    gcc -O3 -fomit-frame-pointer Nakamichi_Shifune.c -o Nakamichi_Shifune.elf -D_N_XMM -march=armv7v

    >Anyway, I’ve done the modifications with memcpy, and built it as on x86, but it will just segfault as I run the program.

    Never compiled for ARM, but shouldn’t you specify ARM target in GCC command options?!
    It says that “not all architectures are recognized” automatically:

    This specifies the name of the target ARM architecture. GCC uses this name to determine what kind of instructions it can emit when generating assembly code. This option can be used in conjunction with or instead of the -mcpu= option. Permissible names are: ‘armv2’, ‘armv2a’, ‘armv3’, ‘armv3m’, ‘armv4’, ‘armv4t’, ‘armv5’, ‘armv5t’, ‘armv5e’, ‘armv5te’, ‘armv6’, ‘armv6j’, ‘armv6t2’, ‘armv6z’, ‘armv6kz’, ‘armv6-m’, ‘armv7’, ‘armv7-a’, ‘armv7-r’, ‘armv7-m’, ‘armv7e-m’, ‘armv7ve’, ‘armv8-a’, ‘armv8-a+crc’, ‘iwmmxt’, ‘iwmmxt2’, ‘ep9312’.

    -march=armv7ve is the armv7-a architecture with virtualization extensions.

    -march=armv8-a+crc enables code generation for the ARMv8-A architecture together with the optional CRC32 extensions.

    -march=native causes the compiler to auto-detect the architecture of the build computer. At present, this feature is only supported on GNU/Linux, and not all architectures are recognized. If the auto-detect is unsuccessful the option has no effect.

  17. @Georgi Marinov (@Sanmayce)
    I should not matter on ARMv7 platforms, but for earlier versions it might become an issue. Normally, you’ll get the message “illegal instruction” if you try to run the program build for ARMv7 on an earlier version.

    If you don’t have ARM hardware right now and are interested in making your program work on ARM, I’d recommend getting one like the Raspberry Pi 2.

    You could also run QEMU with ARM Linux. I’ve explained how to do so on an older post, which may not be 100% up-to-date:

    Alternatively, you could also rent an ARM server for 0.006 Euro per hour ->

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