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LoopVectorization.jl is a Julia package for accelerating numerical loops by automatically applying SIMD (Single Instruction, Multiple Data) vectorization and other low-level optimizations. It analyzes loops and generates highly efficient code that leverages CPU vector instructions, making it ideal for performance-critical computing in fields such as scientific computing, signal processing, and machine learning.
GLM.jl is a Julia package for fitting linear and generalized linear models (GLMs) with a syntax and functionality familiar to users of R or other statistical environments. It is part of the JuliaStats ecosystem and is tightly integrated with StatsModels.jl for formula handling, and Distributions.jl for specifying error families. The package supports modeling through both formula-based (e.g. @formula) and matrix-based interfaces, allowing both high-level convenience and low-level control....
...A large variety of surface types are supported, and these can be composed into complex 3D objects through the use of constructive solid geometry (CSG). A complete catalog of optical materials is provided through the complementary GlassCat submodule. This software provides extensive control over the modelling, simulation, visualization and optimization of optical systems. It is especially suited for designs that have a procedural architecture.