===== Benchmarks for 3×3 Float64 matrices ===== Matrix multiplication -> 5.9x speedup Matrix multiplication (mutating) -> 1.8x speedup Matrix addition -> 33.1x ...

Matrix-vector multiplications form the core of a plethora of scientific computing and machine learning applications that include solving partial differential equations, forward and back propagation in ...

Large-scale Machine Learning (ML) algorithms are often iterative, using repeated read-only data access and I/O-bound matrix-vector multiplications. Hence, it is crucial for performance to fit the data ...

Because the list based, functional toolbox of Raku is not enough to calculate matrices comfortably, there is a need for a dedicated data type. The aim is to provide a full featured set of structural ...

Many computationally demanding statistical procedures, such as Bootstrapping and Markov Chain Monte Carlo, can be speeded up significantly by using several connected computers in parallel. The package ...