Official Resources
- Source Repository: https://github.com/jhu238/AtomMag
- License: Open source
Overview
AtomMag is a GPU-parallel atomistic spin dynamics model developed at the University of Wisconsin-Madison. It achieves 66x speedup over CPU implementations and is validated against fidimag and analytical results, supporting large-scale atomistic magnetic simulations.
Scientific domain: GPU-accelerated atomistic spin dynamics
Target user community: Researchers needing fast GPU atomistic spin dynamics for large magnetic systems
Theoretical Methods
- Atomistic Landau-Lifshitz-Gilbert (LLG) equation
- Heisenberg Hamiltonian
- GPU parallelization (CUDA)
- Monte Carlo simulation
- Exchange, anisotropy, Zeeman energies
- Dzyaloshinskii-Moriya interaction
Capabilities (CRITICAL)
- GPU-accelerated atomistic spin dynamics
- 66x speedup over CPU
- Large-scale spin systems
- Heisenberg model simulation
- Monte Carlo for equilibrium
- Validated against fidimag and analytical results
Sources: GitHub repository
Key Strengths
GPU Performance:
- 66x speedup over CPU
- CUDA parallelization
- Large system sizes feasible
- Efficient memory access
Validation:
- Compared with fidimag
- Analytical result validation
- Reproducible benchmarks
- Well-tested
Inputs & Outputs
-
Input formats:
- Configuration files
- Exchange parameters
- Material parameters
-
Output data types:
- Magnetization vs time
- Energy vs time
- Spin configurations
- Statistical averages
Interfaces & Ecosystem
- CUDA: GPU acceleration
- C/C++: Core computation
- Python: Post-processing
Performance Characteristics
- Speed: Very fast (GPU)
- Accuracy: Good (validated)
- System size: Millions of spins
- Memory: GPU memory limited
Computational Cost
- Small systems: Seconds
- Large systems: Minutes
- Typical: Very efficient
Limitations & Known Constraints
- NVIDIA GPU only: Requires CUDA
- Limited documentation: Research code
- Limited features: Basic Heisenberg model
- Small community: Research group code
Comparison with Other Codes
- vs fidimag: AtomMag is GPU (66x faster), fidimag is CPU
- vs UppASD: AtomMag is GPU, UppASD is CPU with more features
- vs Spirit: AtomMag is GPU-only, Spirit has GUI
- Unique strength: GPU-parallel atomistic spin dynamics with 66x speedup, validated
Application Areas
Large-Scale Spin Dynamics:
- Extended magnetic systems
- Long-time dynamics
- Parameter sweeps
- High-throughput simulation
Benchmarking:
- GPU vs CPU comparison
- Code validation
- Performance testing
- Method verification
Best Practices
GPU Setup:
- Use NVIDIA GPU
- Monitor GPU memory
- Optimize block/grid sizes
- Compare with CPU for validation
Simulation:
- Validate against analytical results
- Use sufficient thermalization
- Average over runs
- Test finite-size effects
Community and Support
- Open source on GitHub
- Developed at UW-Madison (Prof. Jiamian Hu)
- Research code
- Limited documentation
Verification & Sources
Primary sources:
- GitHub: https://github.com/jhu238/AtomMag
- Related publications from UW-Madison
Confidence: VERIFIED
Verification status: ✅ VERIFIED
- Source code: ACCESSIBLE (GitHub)
- Documentation: Limited
- Active development: Research code
- Specialized strength: GPU-parallel atomistic spin dynamics with 66x speedup