Pseudo-Transient solvers
Official@ptsolvers
Concise multi-physics solvers for GPUs and CPUs
Agent Skills by Pseudo-Transient solvers
Showing 6 vetted skills indexed across 1 GitHub repositories.
PTsolversrunning-tests
Execute and debug JustRelax.jl tests on CPU, CUDA, AMDGPU, and MPI backends.
PTsolverskernel-style
Standardize ParallelStencil kernels and check GPU compatibility with JustRelax.jl guidelines.
PTsolversminiapps-and-benchmarks
Validate JustRelax.jl solver changes by executing predefined miniapps and benchmarks.
PTsolversrelease
Automate version bumps, compatibility updates, and Julia package releases.
PTsolversdocs
Build and edit JustRelax.jl documentation with Documenter.jl and DocumenterVitepress.
PTsolversbackend-conventions
Document JustRelax.jl backend module structures and ParallelStencil initialization rules.
Frequently Asked Questions About Pseudo-Transient solvers
FAQPage SchemaWhat specific computational tasks are enabled by Pseudo-Transient solvers?▼
These solvers enable high-performance multi-physics simulations by providing standardized kernel structures and execution environments. Users can perform complex numerical modeling on CPU, CUDA, and AMDGPU backends while ensuring compatibility with ParallelStencil guidelines for distributed memory systems.
Which engineering personas benefit from these solvers?▼
Computational scientists, research engineers, and high-performance computing developers working on multi-physics simulations benefit from these solvers. The framework is specifically designed for those requiring rigorous testing, benchmarking, and documentation standards within the Julia ecosystem for large-scale parallel numerical analysis.
What are the primary prerequisites for running these solvers?▼
The primary prerequisites include a functional Julia environment and the JustRelax.jl package. Users must configure their hardware backends for CUDA or AMDGPU support and ensure ParallelStencil initialization rules are met to maintain compatibility across distributed MPI clusters.