WyHash 1.0.0

There is a newer version of this package available.
See the version list below for details.
dotnet add package WyHash --version 1.0.0                
NuGet\Install-Package WyHash -Version 1.0.0                
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="WyHash" Version="1.0.0" />                
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add WyHash --version 1.0.0                
#r "nuget: WyHash, 1.0.0"                
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
// Install WyHash as a Cake Addin
#addin nuget:?package=WyHash&version=1.0.0

// Install WyHash as a Cake Tool
#tool nuget:?package=WyHash&version=1.0.0                

wyhash-dotnet

Zero-allocation C# implementation of Wang Yi's 64-bit wyhash hash algorithm and wyrand PRNG.

wyhash is an extremely fast, portable hashing algorithm, and passes all of the SMHasher tests (which evaluates collision, dispersion and randomness qualities of hash functions).

Getting Started

Install the WyHash package from NuGet:

Install-Package WyHash

WyHash implements HashAlgorithm, so can be integrated into existing projects easily:

var seed = 42;
var hasher = WyHash64.Create(seed);

var result = hasher.ComputeHash(myData);

A common use case is getting the resulting hash as a 64-bit unsigned integer (ulong), so a static convenience method is also provided:

// Note that if no seed is specified, it default to 0
var seed = 42;
var result = WyHash64.ComputeHash64(myData, seed);

The wyrand PRNG is also implemented:

var rng = new WyRng(42);

// Generate pseudorandom values
ulong a64BitVal = rng.NextLong();
uint a32BitVal = rng.Next();

// Fill a buffer with pseudorandom bytes
var buffer = new byte[256];
rng.NextBytes(buffer);

// Span is also supported
Span<byte> spanBuffer = stackalloc byte[128];
rng.NextBytes(spanBuffer);

Performance & Future Work

At present (April 2019), wyhash is the fastest algorithm in the SMHasher benchmark.

On a dev laptop with 64GB RAM and an Intel Xeon CPU E3-1545M v5 2.90GHz CPU, this implementation can process data at a rate of around 3GB/s, which is very fast.

Note that PInvokeing into a native DLL built using the reference C code (see the WyHash.Native project) achieves around 10.8GB/s, so there is still work to do to bridge the performance gap.

The bottleneck is 64-bit integer multiplication, as .NET doesn't yet support intrinsics, which would allow performing 64x64 multiplication in a single instruction on supported platforms. Work on this is ongoing by the .NET team, and is expected to land in .NET Core 3.0 - support is unlikely to make it into the .NET Framework though. I expected that using instructions such as BMI2 MULX or SSE4.1 PMULLD will get this implementation running at roughly the same speeds as the C reference code (that is, more or less RAM SPEED)

Latest benchmarks (DataSize is the size of data hashed, in bytes):


BenchmarkDotNet=v0.11.5, OS=Windows 7 SP1 (6.1.7601.0)
Intel Xeon CPU E3-1545M v5 2.90GHz, 1 CPU, 8 logical and 4 physical cores
Frequency=2836132 Hz, Resolution=352.5929 ns, Timer=TSC
.NET Core SDK=2.2.105
  [Host] : .NET Core 2.2.3 (CoreCLR 4.6.27414.05, CoreFX 4.6.27414.05), 64bit RyuJIT
  Core   : .NET Core 2.2.3 (CoreCLR 4.6.27414.05, CoreFX 4.6.27414.05), 64bit RyuJIT

Job=Core  Runtime=Core  

Method DataSize Mean Error StdDev Median Min Max Ratio RatioSD Rank Gen 0 Gen 1 Gen 2 Allocated
TestXxHash 100 20.40 ns 0.4396 ns 0.3671 ns 20.48 ns 19.71 ns 20.92 ns 0.48 0.02 2 - - - -
TestXxHashNative 100 24.53 ns 0.5409 ns 0.5313 ns 24.43 ns 23.95 ns 25.71 ns 0.58 0.02 3 - - - -
TestWyHashNative 100 18.96 ns 0.0906 ns 0.0757 ns 18.95 ns 18.85 ns 19.12 ns 0.44 0.01 1 - - - -
TestWyHash 100 40.53 ns 0.8427 ns 1.6829 ns 39.59 ns 39.13 ns 44.56 ns 1.00 0.00 4 - - - -
TestXxHash 1024 99.90 ns 0.7521 ns 0.6667 ns 99.74 ns 99.06 ns 101.42 ns 0.32 0.01 3 - - - -
TestXxHashNative 1024 98.04 ns 2.2641 ns 3.2471 ns 96.98 ns 93.90 ns 105.07 ns 0.31 0.01 2 - - - -
TestWyHashNative 1024 78.13 ns 0.6726 ns 0.5963 ns 78.04 ns 77.34 ns 79.58 ns 0.25 0.01 1 - - - -
TestWyHash 1024 313.00 ns 6.1691 ns 8.6482 ns 310.51 ns 302.29 ns 328.01 ns 1.00 0.00 4 - - - -
Product Compatible and additional computed target framework versions.
.NET net5.0 was computed.  net5.0-windows was computed.  net6.0 was computed.  net6.0-android was computed.  net6.0-ios was computed.  net6.0-maccatalyst was computed.  net6.0-macos was computed.  net6.0-tvos was computed.  net6.0-windows was computed.  net7.0 was computed.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 was computed.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed. 
.NET Core netcoreapp2.0 was computed.  netcoreapp2.1 was computed.  netcoreapp2.2 was computed.  netcoreapp3.0 was computed.  netcoreapp3.1 was computed. 
.NET Standard netstandard2.0 is compatible.  netstandard2.1 was computed. 
.NET Framework net461 was computed.  net462 is compatible.  net463 was computed.  net47 was computed.  net471 was computed.  net472 was computed.  net48 was computed.  net481 was computed. 
MonoAndroid monoandroid was computed. 
MonoMac monomac was computed. 
MonoTouch monotouch was computed. 
Tizen tizen40 was computed.  tizen60 was computed. 
Xamarin.iOS xamarinios was computed. 
Xamarin.Mac xamarinmac was computed. 
Xamarin.TVOS xamarintvos was computed. 
Xamarin.WatchOS xamarinwatchos was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

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Version Downloads Last updated
1.0.5 4,648 6/16/2023
1.0.4 163,352 8/12/2019
1.0.3 51,788 7/23/2019
1.0.2 91,420 5/7/2019
1.0.1 1,016 4/23/2019
1.0.0 596 4/18/2019