Jukka Aho
a8495bdc4a
Explains why JuliaFEM uses nodal assembly instead of element assembly: Five major advantages: 1. No atomic operations on GPU (each node writes to own DOFs) 2. Contact mechanics is natural (forces at nodes, not elements) 3. Clean domain decomposition (explicit node ownership for MPI) 4. Better cache locality (sequential node processing) 5. Adaptive refinement easier (local node operations) Key data structure: - NodeSet contains nodes + elements + node_to_elements connectivity - Inverse connectivity enables gathering from connected elements - Fields accessed via node_set.fields (type-stable) Algorithm: - Loop over nodes (not elements) - Each node gathers contributions from connected elements - Direct write to owned DOFs (no race conditions) - Perfect for matrix-free Krylov methods Validated with demo: - CPU/GPU results match exactly (0.0 relative error) - Average 3.24 elements per node (efficient gathering) - Natural integration with contact mechanics Compares to traditional element assembly: - Element: scatter to nodes (atomic ops, cache misses) - Nodal: gather from elements (no atomics, better cache)
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| JuliaFEM Documentation | Three-tier documentation structure for users, contributors, and researchers | 2025-11-09 | Jukka Aho |
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Welcome! JuliaFEM documentation is organized into three manuals for three different audiences:
📘 User Manual - "Just Get It Done"
For: End users, engineers, students who want to run simulations.
Style: Simple, practical, step-by-step.
Contents:
- Quick start and installation
- Tutorials and examples
- API reference
- Troubleshooting
Philosophy: Show me how to solve my problem, skip the lectures.
👉 Start Here if you want to run simulations.
🔧 Contributor Manual - "Show Me the Code"
For: Developers, contributors, advanced users who want to extend JuliaFEM.
Style: Technical, detailed, design rationale.
Contents:
- Testing philosophy
- Code style and architecture
- Performance guidelines
- How to add elements
- CI/CD and git workflow
Philosophy: Explain HOW the code works and WHY we made these choices.
👉 Start Here if you want to contribute code.
📖 The JuliaFEM Book - "Let Me Show You How I Think"
For: Advanced researchers, theory nerds, those who want to understand deeply. And Jukka.
Style: Comprehensive, educational, opinionated, personal.
Contents:
- Mathematical foundations (Lagrange basis, contact mechanics, etc.)
- Design philosophy and technical vision
- Strategic mistakes and lessons learned (2015-2019)
- Research directions (nodal assembly, matrix-free, etc.)
- Personal reflections on the journey
Philosophy: Mix theory, software design, and personal experience. Teach FEM through implementation.
👉 Start Here if you love deep dives and want to understand the "why" behind everything.
Quick Navigation
I want to...
- Solve a heat transfer problem → User Manual
- Add a new element type → Contributor Manual
- Understand Lagrange basis functions → Book: Lagrange Basis
- Learn about testing → Contributor: Testing Philosophy
- See benchmark results → Book: Benchmarks
- Understand the design philosophy → Book: Philosophy
- Report a bug → GitHub Issues
- Ask a question → GitHub Discussions
Documentation Philosophy
Why Three Manuals?
Different readers have different needs:
- Users don't care about implementation details - they just want working code.
- Contributors need technical depth but not necessarily all the theory.
- Researchers (and Jukka) want to understand everything from first principles.
Mixing these audiences in one manual makes it too complex for users and too shallow for researchers.
Design Principles
- User Manual: Optimize for time-to-first-result
- Contributor Manual: Optimize for correctness and maintainability
- Book: Optimize for understanding and education
Cross-References
Manuals link to each other when appropriate:
- User manual links to theory when deeper understanding helps
- Contributor manual links to book for design rationale
- Book links to code examples and practical guides
Contributing to Documentation
Documentation improvements are always welcome!
- User docs: Fix errors, add examples, improve clarity
- Contributor docs: Update for new features, clarify architecture
- Book: Add theory, share insights, document research
See Contributor Manual for guidelines.
License: MIT (same as code)
Questions? Open an issue or discussion on GitHub