Official Resources
- Source Repository: https://github.com/MagneticSimulation/MicroMagnetic.jl
- Documentation: https://magneticimulation.github.io/MicroMagnetic.jl/
- License: Open source
Overview
MicroMagnetic.jl is a Julia package for classical spin dynamics and micromagnetic simulations with multi-platform GPU support (NVIDIA, AMD, Intel, Apple). It supports atomistic and continuum spin simulations, Monte Carlo, NEB energy barriers, and spin-transfer torque effects.
Scientific domain: Micromagnetic and atomistic spin simulation, GPU computing
Target user community: Researchers needing fast GPU-accelerated magnetic simulations across different GPU platforms
Theoretical Methods
- Landau-Lifshitz-Gilbert (LLG) equation
- Finite-difference method
- Atomistic and continuum spin models
- Monte Carlo simulation
- Nudged elastic band (NEB)
- Spin-transfer torque (Zhang-Li, Slonczewski)
- Exchange, anisotropy, Zeeman, demagnetization
- Dzyaloshinskii-Moriya interaction
- Constructive solid geometry (CSG)
Capabilities (CRITICAL)
- Micromagnetic simulation (continuum)
- Atomistic spin simulation
- Monte Carlo simulation
- NEB energy barrier calculation
- Multi-GPU support (CUDA, AMDGPU, oneAPI, Metal)
- Spin-transfer torque
- Periodic boundary conditions
- Constructive solid geometry
- Thermal fluctuations
- Julia scripting interface
Sources: GitHub repository
Key Strengths
Multi-Platform GPU:
- NVIDIA (CUDA)
- AMD (AMDGPU.jl)
- Intel (oneAPI.jl)
- Apple (Metal.jl)
- CPU fallback
Julia Performance:
- Near-C performance
- JIT compilation
- Automatic differentiation
- Composable with Julia ecosystem
Comprehensive Physics:
- Atomistic + continuum
- Monte Carlo + dynamics
- NEB energy barriers
- Spin-torque effects
- CSG geometry definition
Inputs & Outputs
-
Input formats:
- Julia scripts
- Material parameters
- Mesh specifications (CSG)
-
Output data types:
- Magnetization fields
- Energy vs time
- NEB paths and barriers
- VTK output
Interfaces & Ecosystem
- Julia: Primary language
- CUDA.jl/AMDGPU.jl: GPU backends
- Makie.jl: Visualization
- JLD2.jl: Data storage
Performance Characteristics
- Speed: Fast (GPU-accelerated)
- Accuracy: Good (validated)
- System size: Millions of cells (GPU)
- Multi-GPU: Supported
Computational Cost
- Small systems: Seconds (GPU)
- Large systems: Minutes to hours
- Typical: Very efficient with GPU
Limitations & Known Constraints
- Julia language: Less common than Python/C++
- Newer code: Less established than OOMMF
- Documentation: Growing but limited
- Community: Small but active
Comparison with Other Codes
- vs Mumax3: MicroMagnetic.jl supports more GPU platforms, Mumax3 is NVIDIA-only
- vs OOMMF: MicroMagnetic.jl is GPU, OOMMF is CPU
- vs Spirit: MicroMagnetic.jl is Julia/GPU, Spirit is C++
- Unique strength: Multi-platform GPU support (NVIDIA/AMD/Intel/Apple), Julia performance, atomistic+continuum
Application Areas
GPU-Accelerated Micromagnetics:
- Large-scale domain dynamics
- Fast hysteresis loops
- Parameter sweeps
- Real-time simulation
Skyrmion Dynamics:
- Skyrmion creation and motion
- Skyrmion lattice dynamics
- Current-driven skyrmions
- Temperature effects
Energy Barriers:
- Switching field determination
- Thermal stability analysis
- NEB transition paths
- Coercivity estimation
Novel Architectures:
- Apple Silicon GPU
- AMD GPU clusters
- Intel GPU nodes
- Cross-platform portability
Best Practices
GPU Selection:
- Use available GPU backend
- Test CPU vs GPU for small systems
- Monitor GPU memory usage
- Use appropriate precision
Julia Setup:
- Install Julia with GPU support
- Pre-compile for first-run speed
- Use Makie for visualization
- Leverage Julia ecosystem
Community and Support
- Open source on GitHub
- Developed by MicroMagnetic.jl team
- Active development
- Documentation growing
Verification & Sources
Primary sources:
- GitHub: https://github.com/MagneticSimulation/MicroMagnetic.jl
- Documentation: https://magneticimulation.github.io/MicroMagnetic.jl/
Confidence: VERIFIED
Verification status: ✅ VERIFIED
- Source code: ACCESSIBLE (GitHub)
- Documentation: ACCESSIBLE
- Active development: Ongoing
- Specialized strength: Multi-platform GPU micromagnetic simulation (NVIDIA/AMD/Intel/Apple), Julia performance