Hendrik Ranocha's Projects
Metal programming in Julia
General purpose algebraic metaprogramming and symbolic computation library for the Julia programming language: E-Graphs & equality saturation, term rewriting and more.
Utilities to analyze Julia's method tables
Automatic Finite Difference PDE solving with Julia SciML
Immutable empty and singleton collections
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Finds relationships between the parameters of a mathematical model
A small Julia wrapper of the Qhull library
Intel MKL linear algebra backend for Julia
An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
A standard library of components to model the world and beyond
High-level model-order reduction to automate the acceleration of large-scale simulations
Julia package for lazily viewing a 3D or 4D array as an expanded 2D array in the form of a mosaic of matrix slices
MPI wrappers for Julia
Julia parallel constructs over MPI
Julia MsgPack implementation with type-driven, overloadable packing/unpacking functionality
This package contains a macro for converting expressions to use muladd calls and fused-multiply-add (FMA) operations for high-performance in the SciML scientific machine learning ecosystem
Create a higher-dimensional array from lazily-loaded slices in separate files
A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations
Julia math built-ins which return NaN and accumulator functions which ignore NaN
Debugging native applications
Natural sort order
A differentiable simulator for scientific machine learning (SciML) with N-body problems, including astrophysical and molecular dynamics
A Julia wrapper for the NVIDIA Collective Communications Library.
Load and save Netpbm images in Julia
DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia
Physics-Informed Neural Networks (PINN) and Deep BSDE Solvers of Differential Equations for Scientific Machine Learning (SciML) accelerated simulation