Xoshiro128Plus Class

public sealed class Xoshiro128Plus : RandomSource<ScalarGenerator32<Xoshiro128PlusEngine>>, 
	IRandomSourceFactory<Xoshiro128Plus>, IAdvanceable, IJumpable

Public NotInheritable Class Xoshiro128Plus
	Inherits RandomSource(Of ScalarGenerator32(Of Xoshiro128PlusEngine))
	Implements IRandomSourceFactory(Of Xoshiro128Plus), IAdvanceable, 
	IJumpable

public ref class Xoshiro128Plus sealed : public RandomSource<ScalarGenerator32<Xoshiro128PlusEngine>>, 
	IRandomSourceFactory<Xoshiro128Plus^>, IAdvanceable, IJumpable

[<SealedAttribute>]
type Xoshiro128Plus = 
    class
        inherit RandomSource<ScalarGenerator32<Xoshiro128PlusEngine>>
        interface IRandomSourceFactory<Xoshiro128Plus>
        interface IAdvanceable
        interface IJumpable
    end

Inheritance

Object  →  RandomSource<ScalarGenerator32<Xoshiro128PlusEngine>>  →  Xoshiro128Plus

Implements

IAdvanceable, IJumpable, IRandomSourceFactory<Xoshiro128Plus>

Use the Xoshiro128Plus class to represent a pseudo-random number generator that uses the Xoshiro128+ algorithm by David Blackman and Sebastiano Vigna.

This generator has a period of 2¹²⁸ - 1 and is optimized for high-performance floating-point generation. The "+" scrambler is fast but has low linear complexity in the low bits.

⚠ Warning: The low bits of this generator have low linear complexity and should NOT be used for integer generation or bit-masking scenarios. Use Xoshiro128StarStar for general-purpose integer generation instead.

Performance: This generator is one of the fastest 32-bit RNGs available and is particularly well-suited for generating floating-point numbers where only high bits are used.

Use cases:

• High-performance floating-point generation
• Applications where only high bits are used (e.g., NextDouble())
• Parallel computing with jump-ahead capability

Avoid using for:

• Integer generation (use Xoshiro128StarStar instead)
• Bit-level operations requiring uniformity in low bits
• Cryptographic purposes (like all PRNGs in this library)

Reference: David Blackman and Sebastiano Vigna. "Scrambled Linear Pseudorandom Number Generators." ACM Trans. Math. Softw. 2021.

Reference