MURMUR3F Hash Tool

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MD2 MD4 MD5 SHA1 SHA224 SHA256 SHA384 SHA512/224 SHA512/256 SHA512 SHA3-224 SHA3-256 SHA3-384 SHA3-512 RIPEMD128 RIPEMD160 RIPEMD256 RIPEMD320 WHIRLPOOL TIGER128,3 TIGER160,3 TIGER192,3 TIGER128,4 TIGER160,4 TIGER192,4 SNEFRU SNEFRU256 GOST GOST-CRYPTO ADLER32 CRC32 CRC32B CRC32C FNV132 FNV1A32 FNV164 FNV1A64 JOAAT MURMUR3A MURMUR3C MURMUR3F XXH32 XXH64 XXH3 XXH128 HAVAL128,3 HAVAL160,3 HAVAL192,3 HAVAL224,3 HAVAL256,3 HAVAL128,4 HAVAL160,4 HAVAL192,4 HAVAL224,4 HAVAL256,4 HAVAL128,5 HAVAL160,5 HAVAL192,5 HAVAL224,5 HAVAL256,5

The Murmur3f algorithm is a non-cryptographic hash function designed for high performance in software systems requiring fast hash computations. It is part of the MurmurHash family, specifically optimized for 32-bit floating-point keys. Unlike cryptographic hashes, Murmur3f emphasizes speed, uniform distribution, and minimal collision rates for general-purpose data indexing and retrieval.

Core Components

The algorithm operates on a sequence of input bytes, processing them in fixed-size blocks. The primary components include:

Initialization: Murmur3f begins by initializing a hash state variable with a seed value provided by the user or set to a default. This ensures deterministic outputs for identical inputs while allowing variance with different seeds.
Block Processing: Input data is partitioned into 32-bit blocks. Each block undergoes a series of arithmetic and bitwise operations, including multiplication with predefined constants, rotations, and XOR operations. These steps ensure that even small changes in input produce significantly different hash values.
Finalization: After processing all full-size blocks, any remaining bytes are processed individually. The algorithm then applies a final mixing stage that combines all intermediate states into a single 32-bit hash output. This finalization guarantees a uniform distribution of hash values.

Mathematical Operations

Murmur3f relies heavily on multiplication and rotation operations, leveraging prime constants to reduce clustering in hash space. Each block undergoes the following transformations:

k = k * c1k = ROTL32(k, r1)k = k * c2hash ^= khash = ROTL32(hash, r2)hash = hash * m + n

Here, ROTL32 represents a left rotation of 32-bit integers, and constants c1, c2, r1, r2, m, n are fixed values chosen to maximize avalanche behavior and reduce collisions.

Performance Characteristics

High throughput due to simple arithmetic and bitwise operations suitable for software and hardware implementations.
Low collision probability for uniform and non-uniform input distributions.
Deterministic output, allowing consistent hashing across multiple runs with the same seed.
Optimized for in-memory hash tables, bloom filters, and other data structures requiring fast key hashing.

Usage Considerations

Murmur3f is appropriate for applications that prioritize speed over cryptographic security. It should not be used for password storage or digital signatures. The algorithm's deterministic nature and uniform distribution make it effective for load balancing, data partitioning, and indexing where hash collisions must be minimized.

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