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MRX - A suite of high speed hashing functions

This software includes a suite of high speed non-cryptographic hashing algorithms utilising various different CPU instruction sets available on Intel CPUs.

All of the hashing algorithms have been optimised for bulk hashing of large files but can be used for hashing messages of any length.

All of the algorithms use the same fundamental block based design and use a Merkle-Damgard style construction by adding an extra bit after the message and including the message length in the last block for added strength.

All algorithms offer a single call interface as well as a streaming interface such that data can be fed to the algorithm in multiple chunks of arbitrary length.

All of these algorithms successfully pass all of the tests from the SMHasher test suites available at https://github.com/aappleby/smhasher and https://github.com/demerphq/smhasher.

MRXHash32 (32-bit)

  • A 32-bit algorithm using multiple/rotate/xor (hence MRX) operations.

MRXHash64 (64-bit)

  • A 64-bit algorithm using multiple/rotate/xor (hence MRX) operations.

MLXHash (64-bit)

  • Uses the 64x64 -> 128 bit mul instruction. This is significantly slower than ordinary 64 bit multiplication but it doesn't need to rotate the bits and multiply again to get mixing in both directions. Overall its faster than the MRX variants.

MLXHash2 (256-bit)

  • Similar to MLXHash but mixes across the state to provide a 256-bit hash.

SPBHash (64-bit)

  • Uses only lookup tables and xor to simulate a substitution/permutation box. Very slow but good distribution. This was originally an experiment to use the pext/pdep instructions but it turned out a single lookup table was slightly faster.

SSEHash (128-bit)

  • Uses SSE instructions by combining the results of the low and high products of 16 bit multiplication and shifting bytes with the alignr instruction. Using 16 bit multiplication was significantly faster than 32 bit multiplication but the mixing effect is poor so it needs to do more work in the final mix to ensure all bits are mixed properly.

SSEHash2 (128-bit)

  • Uses 32x32->64 bit multiplication which is slower than 16x16->16 and 32x32->32 multiplication but it only needs half as many instructions since both the low and high orders of the product are provided in the one result.

CLMHash (128-bit)

  • Uses the pclmul instruction to perform 64x64->128 bit carry-less multiplication. Very similar to MLXHash but this instruction is a lot faster.

CLMHash2 (1024-bit)

  • Similar to CLMHash but mixes across the full state to provide a 1024-bit hash.

AVXHash (128-bit)

  • Similar to SSEHash but doubles the register width for greater parallelism.

AVXHash2 (128-bit)

  • Similar to SSEHash2 but doubles the register width for greater parallelism.

AVXHash3 (256-bit)

  • Similar to AVXHash2 but faster and uses the permute instruction to mix across lanes and provide a 256-bit hash.

AESHash (128-bit)

  • Uses the AES-NI encrypt instruction to mix bits. Each aesenc call has relatively poor mixing but the mixing effect propagates with subsequent calls as more input is processed. The final mix needs to do a few more cycles to ensure mixing is complete.

AESHash2 (1024-bit)

  • Similar to AESHash but also uses the aesenc instruction to mix across the full state to provide a 1024-bit hash.

Included in this software suite is a command line tool 'mrx' that can use any of the above algorithms to generate hashes for a collection of files and also verify hashes to check integrity. The command also includes a benchmarking feature.

Using a reference system of an Intel(R) Core(TM) i7-8650U CPU @ 1.90GHz the following performance was achieved:

Name Speed GB/s Bytes/cycle
MRXHash32 8.1 3.8
MRXHash64 16.3 7.7
MLXHash 29.2 13.8
MLXHash2 22.4 10.6
SPBHash 0.6 0.3
SSEHash 22.7 10.8
SSEHash2 25.5 12.1
CLMHash 49.9 23.6
CLMHash2 45.3 21.5
AVXHash 57.8 27.4
AVXHash2 68.9 32.6
AVXHash3 73.3 34.7
AESHash 66.4 31.4
AESHash2 33.1 15.7

The software in the suite has only been tested on Intel CPUs that provide the necessary CPU instruction sets. Some or all of these algorithms may be ported to other architectures that support equivalent instructions. No specific support has been included for endian conversion so if any of these algorithms are run on big endian CPUs the hashes produced will be different. Adding support for endian conversion should be trivial though.

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