LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.
-
Updated
May 11, 2024 - Julia
Julia is a high-level dynamic programming language designed to address the needs of high-performance numerical analysis and computational science. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.
LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.
Dpdl (Dynamic Packet Definition Language) is a rapid development programming language and constrained device framework with built-in database technology. Dpdl enables access to Java platform API's and external native libraries and allows the embedding and execution of C/C++ code, Python, Julia, js, Lua and Ruby code directly within Dpdl code
Thesis for the Computational Science Master's program at Central Washington University. 3D extension of an analog of cosmological particle creation in a Friedmann-Robertson-Walker universe by numerically simulating a Bose-Einstein condensate with a time-dependent scattering length.
Julia bindings for the Enzyme automatic differentiator
C# style generators a.k.a. semi-coroutines for Julia.
Library for the numerical simulation of closed as well as open quantum systems.
The Julia Programming Language
Combine multiple types in a single one
Heterogeneous programming in Julia
analyzer of the proof structure of a clause set by resolution and HOW TO WRITE THE WORLDS BY FOL.
Collecting and maintaining crucial Julia package data, including Names, UUIDs, and download statistics, for enhanced accessibility, insight, and discoverability.
Global documentation for the Julia SciML Scientific Machine Learning Organization
Generic Mapping Tools Library Wrapper 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
The SciML Scientific Machine Learning Software Organization Website
Efficient and type-stable physical quantities in Julia
Efficient Handling of Trajectories with User Defined Named Components
A Julia package for exponential family principal component analysis (E-PCA).
Created by Jeff Bezanson, Stefan Karpinski, Viral B. Shah, Alan Edelman
Released February 14, 2012