Which RNG sources are compatible with this skill?

The skill supports specific sources including splitmix_ternary, xoroshiro_3color, and gay_mcp for validating deterministic outputs.

What is Strong Parallelism Invariance (SPI)?

SPI is a property ensuring that a computational system's output remains identical regardless of whether tasks are processed sequentially, in parallel, or in a shuffled order.

Does this skill handle floating-point errors?

Yes, it specifically avoids float truncation by using arbitrary precision, which is critical for maintaining the integrity of RNG states during verification.

Why is GF(3) conservation important in this context?

In 3-way color streams, GF(3) conservation ensures that the mathematical properties of ternary logic or color triplets are preserved throughout the computational process.

SPI Parallel Verify

Name: SPI Parallel Verify
Author: plurigrid

byplurigrid

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Security & Testing

Verifies Strong Parallelism Invariance and GF(3) conservation for 3-way color streams to ensure deterministic results across parallel executions.

The SPI Parallel Verify skill is designed for developers working with topological computing and complex parallel systems that require absolute mathematical consistency. It validates Strong Parallelism Invariance (SPI), ensuring that results remain identical whether execution is ordered, reversed, shuffled, or split across parallel threads. By checking GF(3) conservation and utilizing arbitrary precision to prevent floating-point truncation, this skill provides a rigorous framework for testing 3-way color streams and specialized RNGs like SplitMixTernary and Xoroshiro.

Key Features

01Generates detailed deterministic reports for seed, indices, and validation status

02Ensures GF(3) conservation laws are strictly maintained per triplet

03Compares ordered, reversed, and parallel results for bit-perfect equality

047 GitHub stars

05Supports arbitrary precision to prevent float truncation in RNG states

06Validates Strong Parallelism Invariance (SPI) across shuffled or split streams

Use Cases

01Testing RNG state consistency across distributed or parallel workloads

02Validating mathematical invariants in topological chemputer simulations

03Ensuring deterministic outcomes in high-concurrency ternary stream processing

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add plurigrid/asi spi-parallel-verify

For use in Claude.ai and ChatGPT

Download Skill