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xxHash - Extremely fast hash algorithm

xxHash is an Extremely fast Hash algorithm, processing at RAM speed limits. Code is highly portable, and produces hashes identical across all platforms (little / big endian). The library includes the following algorithms :

  • XXH32 : generates 32-bit hashes, using 32-bit arithmetic
  • XXH64 : generates 64-bit hashes, using 64-bit arithmetic
  • XXH3 (since v0.8.0): generates 64 or 128-bit hashes, using vectorized arithmetic. The 128-bit variant is called XXH128.

All variants successfully complete the SMHasher test suite which evaluates the quality of hash functions (collision, dispersion and randomness). Additional tests, which evaluate more thoroughly speed and collision properties of 64-bit hashes, are also provided.

Branch Status
release Build Status
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Benchmarks

The benchmarked reference system uses an Intel i7-9700K cpu, and runs Ubuntu x64 20.04. The open source benchmark program is compiled with clang v10.0 using -O3 flag.

Hash Name Width Bandwidth (GB/s) Small Data Velocity Quality Comment
XXH3 (SSE2) 64 31.5 GB/s 133.1 10
XXH128 (SSE2) 128 29.6 GB/s 118.1 10
RAM sequential read N/A 28.0 GB/s N/A N/A for reference
City64 64 22.0 GB/s 76.6 10
T1ha2 64 22.0 GB/s 99.0 9 Slightly worse collisions
City128 128 21.7 GB/s 57.7 10
XXH64 64 19.4 GB/s 71.0 10
SpookyHash 64 19.3 GB/s 53.2 10
Mum 64 18.0 GB/s 67.0 9 Slightly worse collisions
XXH32 32 9.7 GB/s 71.9 10
City32 32 9.1 GB/s 66.0 10
Murmur3 32 3.9 GB/s 56.1 10
SipHash 64 3.0 GB/s 43.2 10
FNV64 64 1.2 GB/s 62.7 5 Poor avalanche properties
Blake2 256 1.1 GB/s 5.1 10 Cryptographic
SHA1 160 0.8 GB/s 5.6 10 Cryptographic but broken
MD5 128 0.6 GB/s 7.8 10 Cryptographic but broken

note 1: Small data velocity is a rough evaluation of algorithm's efficiency on small data. For more detailed analysis, please refer to next paragraph.

note 2: some algorithms feature faster than RAM speed. In which case, they can only reach their full speed potential when input is already in CPU cache (L3 or better). Otherwise, they max out on RAM speed limit.

Small data

Performance on large data is only one part of the picture. Hashing is also very useful in constructions like hash tables and bloom filters. In these use cases, it's frequent to hash a lot of small data (starting at a few bytes). Algorithm's performance can be very different for such scenarios, since parts of the algorithm, such as initialization or finalization, become fixed cost. The impact of branch mis-prediction also becomes much more present.

XXH3 has been designed for excellent performance on both long and small inputs, which can be observed in the following graph:

XXH3, latency, random size

For a more detailed analysis, please visit the wiki : https://github.com/Cyan4973/xxHash/wiki/Performance-comparison#benchmarks-concentrating-on-small-data-

Quality

Speed is not the only property that matters. Produced hash values must respect excellent dispersion and randomness properties, so that any sub-section of it can be used to maximally spread out a table or index, as well as reduce the amount of collisions to the minimal theoretical level, following the birthday paradox.

xxHash has been tested with Austin Appleby's excellent SMHasher test suite, and passes all tests, ensuring reasonable quality levels. It also passes extended tests from newer forks of SMHasher, featuring additional scenarios and conditions.

Finally, xxHash provides its own massive collision tester, able to generate and compare billions of hashes to test the limits of 64-bit hash algorithms. On this front too, xxHash features good results, in line with the birthday paradox. A more detailed analysis is documented in the wiki.

Build modifiers

The following macros can be set at compilation time to modify libxxhash's behavior. They are generally disabled by default.

  • XXH_INLINE_ALL: Make all functions inline, with implementations being directly included within xxhash.h. Inlining functions is beneficial for speed on small keys. It's extremely effective when key length is expressed as a compile time constant, with performance improvements observed in the +200% range . See this article for details.
  • XXH_PRIVATE_API: same outcome as XXH_INLINE_ALL. Still available for legacy support. The name underlines that XXH_* symbol names will not be exported.
  • XXH_NAMESPACE: Prefixes all symbols with the value of XXH_NAMESPACE. This macro can only use compilable character set. Useful to evade symbol naming collisions, in case of multiple inclusions of xxHash's source code. Client applications still use the regular function names, as symbols are automatically translated through xxhash.h.
  • XXH_FORCE_ALIGN_CHECK: Use a faster direct read path when input is aligned. This option can result in dramatic performance improvement when input to hash is aligned on 32 or 64-bit boundaries, when running on architectures unable to load memory from unaligned addresses, or suffering a performance penalty from it. It is (slightly) detrimental on platform with good unaligned memory access performance (same instruction for both aligned and unaligned accesses). This option is automatically disabled on x86, x64 and aarch64, and enabled on all other platforms.
  • XXH_FORCE_MEMORY_ACCESS: The default method 0 uses a portable memcpy() notation. Method 1 uses a gcc-specific packed attribute, which can provide better performance for some targets. Method 2 forces unaligned reads, which is not standard compliant, but might sometimes be the only way to extract better read performance. Method 3 uses a byteshift operation, which is best for old compilers which don't inline memcpy() or big-endian systems without a byteswap instruction.
  • XXH_VECTOR : manually select a vector instruction set (default: auto-selected at compilation time). Available instruction sets are XXH_SCALAR, XXH_SSE2, XXH_AVX2, XXH_AVX512, XXH_NEON and XXH_VSX. Compiler may require additional flags to ensure proper support (for example, gcc on linux will require -mavx2 for AVX2, and -mavx512f for AVX512).
  • XXH_NO_PREFETCH : disable prefetching. Some platforms or situations may perform better without prefetching. XXH3 only.
  • XXH_PREFETCH_DIST : select prefetching distance. For close-to-metal adaptation to specific hardware platforms. XXH3 only.
  • XXH_NO_STREAM: Disables the streaming API, limiting it to single shot variants only.
  • XXH_SIZE_OPT: 0: default, optimize for speed 1: default for -Os and -Oz: disables some speed hacks for size optimization 2: makes code as small as possible, performance may cry
  • XXH_NO_INLINE_HINTS: By default, xxHash uses __attribute__((always_inline)) and __forceinline to improve performance at the cost of code size. Defining this macro to 1 will mark all internal functions as static, allowing the compiler to decide whether to inline a function or not. This is very useful when optimizing for smallest binary size, and is automatically defined when compiling with -O0, -Os, -Oz, or -fno-inline on GCC and Clang. This may also increase performance depending on compiler and architecture.
  • XXH32_ENDJMP: Switch multi-branch finalization stage of XXH32 by a single jump. This is generally undesirable for performance, especially when hashing inputs of random sizes. But depending on exact architecture and compiler, a jump might provide slightly better performance on small inputs. Disabled by default.
  • XXH_NO_STDLIB: Disable invocation of <stdlib.h> functions, notably malloc() and free(). libxxhash's XXH*_createState() will always fail and return NULL. But one-shot hashing (like XXH32()) or streaming using statically allocated states still work as expected. This build flag is useful for embedded environments without dynamic allocation.
  • XXH_STATIC_LINKING_ONLY: gives access to internal state declaration, required for static allocation. Incompatible with dynamic linking, due to risks of ABI changes.
  • XXH_NO_XXH3 : removes symbols related to XXH3 (both 64 & 128 bits) from generated binary. Useful to reduce binary size, notably for applications which do not employ XXH3.
  • XXH_NO_LONG_LONG: removes compilation of algorithms relying on 64-bit types (XXH3 and XXH64). Only XXH32 will be compiled. Useful for targets (architectures and compilers) without 64-bit support.
  • XXH_IMPORT: MSVC specific: should only be defined for dynamic linking, as it prevents linkage errors.
  • XXH_CPU_LITTLE_ENDIAN: By default, endianness is determined by a runtime test resolved at compile time. If, for some reason, the compiler cannot simplify the runtime test, it can cost performance. It's possible to skip auto-detection and simply state that the architecture is little-endian by setting this macro to 1. Setting it to 0 states big-endian.
  • XXH_DEBUGLEVEL : When set to any value >= 1, enables assert() statements. This (slightly) slows down execution, but may help finding bugs during debugging sessions.

When compiling the Command Line Interface xxhsum using make, the following environment variables can also be set :

  • DISPATCH=1 : use xxh_x86dispatch.c, to automatically select between scalar, sse2, avx2 or avx512 instruction set at runtime, depending on local host. This option is only valid for x86/x64 systems.

Building xxHash - Using vcpkg

You can download and install xxHash using the vcpkg dependency manager:

git clone https://github.com/Microsoft/vcpkg.git
cd vcpkg
./bootstrap-vcpkg.sh
./vcpkg integrate install
./vcpkg install xxhash

The xxHash port in vcpkg is kept up to date by Microsoft team members and community contributors. If the version is out of date, please create an issue or pull request on the vcpkg repository.

Building and Using xxHash - tipi.build

You can work on xxHash and depend on it in your tipi.build projects by adding the following entry to your .tipi/deps:

{
    "Cyan4973/xxHash": { "@": "v0.8.1" }
}

An example of such usage can be found in the /cli folder of this project which, if built as root project will depend on the release v0.8.1 of xxHash

To contribute to xxHash itself use tipi.build on this repository (change the target name appropriately to linux or macos or windows):

tipi . -t <target> --test all

Example

The simplest example calls xxhash 64-bit variant as a one-shot function generating a hash value from a single buffer, and invoked from a C/C++ program:

#include "xxhash.h"

    (...)
    XXH64_hash_t hash = XXH64(buffer, size, seed);
}

Streaming variant is more involved, but makes it possible to provide data incrementally:

#include "stdlib.h"   /* abort() */
#include "xxhash.h"


XXH64_hash_t calcul_hash_streaming(FileHandler fh)
{
    /* create a hash state */
    XXH64_state_t* const state = XXH64_createState();
    if (state==NULL) abort();

    size_t const bufferSize = SOME_SIZE;
    void* const buffer = malloc(bufferSize);
    if (buffer==NULL) abort();

    /* Initialize state with selected seed */
    XXH64_hash_t const seed = 0;   /* or any other value */
    if (XXH64_reset(state, seed) == XXH_ERROR) abort();

    /* Feed the state with input data, any size, any number of times */
    (...)
    while ( /* some data left */ ) {
        size_t const length = get_more_data(buffer, bufferSize, fh);
        if (XXH64_update(state, buffer, length) == XXH_ERROR) abort();
        (...)
    }
    (...)

    /* Produce the final hash value */
    XXH64_hash_t const hash = XXH64_digest(state);

    /* State could be re-used; but in this example, it is simply freed  */
    free(buffer);
    XXH64_freeState(state);

    return hash;
}

License

The library files xxhash.c and xxhash.h are BSD licensed. The utility xxhsum is GPL licensed.

Other programming languages

Beyond the C reference version, xxHash is also available from many different programming languages, thanks to great contributors. They are listed here.

Packaging status

Many distributions bundle a package manager which allows easy xxhash installation as both a libxxhash library and xxhsum command line interface.

Packaging status

Special Thanks

  • Takayuki Matsuoka, aka @t-mat, for creating xxhsum -c and great support during early xxh releases
  • Mathias Westerdahl, aka @JCash, for introducing the first version of XXH64
  • Devin Hussey, aka @easyaspi314, for incredible low-level optimizations on XXH3 and XXH128

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