simulation-dev

Name: simulation-dev
Availability: InStock
Author: spiriMirror

Provides best practices for simulation code correctness, stability, and debuggability across CPU/GPU paths.

307|59|Updated Jun 2, 2024

Search Tags:#testing #debugging #validation #simulation #diagnostics #robustness #gpu

Ready to run

npx skills add https://github.com/spiriMirror/libuipc --skill simulation-dev

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: simulation-dev
Source: https://github.com/spiriMirror/libuipc/tree/main/.cursor/skills/simulation-dev
Command: npx skills add https://github.com/spiriMirror/libuipc --skill simulation-dev

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This guidance helps engineering teams enforce correctness, stability, and debuggability in simulation code, reducing crashes, nondeterminism, and silent numerical errors by standardizing validation, diagnostics, and deterministic paths.

Core Features & Use Cases

Validation at subsystem boundaries to catch invalid inputs early.
Deterministic debugging practices and structured diagnostics for GPU paths.
Clear guidelines for building robust CUDA and MUDA paths, solver components, and kernel development across CPU/GPU contexts.

Quick Start

Follow these practices when implementing or modifying simulation systems to improve correctness and debuggability.

Frequently Asked Questions about simulation-dev

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I handle NaN and Inf errors in GPU simulation code?▼

To handle NaN and Inf errors in simulation code, apply structured best practices for numerical robustness and diagnostic instrumentation. This enforces input validation, index safety checks, and deterministic debugging across CPU and GPU solver paths.

What is the best way to debug nondeterministic behavior in CUDA kernels?▼

Debug nondeterministic behavior in CUDA kernels by following deterministic debugging practices with structured diagnostics. This standardizes validation at subsystem boundaries to catch invalid inputs early and reduce silent numerical errors.

How do I validate inputs at subsystem boundaries in a physics solver?▼

Validate inputs at solver subsystem boundaries by enforcing clear input validation and index safety checks. This catches invalid inputs early, improving correctness and stability while reducing crashes in simulation systems.

Does this simulation development guidance apply to both CPU and GPU paths?▼

Yes, this simulation development guidance applies to both CPU and GPU paths. It provides clear guidelines for building robust CUDA and MUDA paths, solver components, and kernel development across mixed CPU/GPU contexts.

Why does my simulation crash silently without throwing a numerical error?▼

Your simulation crashes silently because it lacks proper diagnostic instrumentation and numerical robustness checks. Implementing structured validation for NaN and Inf handling alongside deterministic debugging practices surfaces these silent numerical errors.