Armadillo Matrix Multiplication

01 May, 2021

Armadillo is a high quality linear algebra library matrix maths for the C language aiming towards a good balance between speed and ease of use. The documentation is incredibly thorough.

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Armadillo matrix multiplication. X 21 60. Armadillo employs a delayed evaluation approach to combine several operations into one and reduce or eliminate the need for temporaries. Provides high-level syntax and functionality deliberately similar to Matlab.

In Armadillo the operator multiplies two matrices together and this also works for any combination of sparse and dense inputs. Delayed evaluation and optimisation are achieved through recursive templates and template meta-programming. To see this let us define a few simple functions.

Where applicable the order of operations is optimised. GPU-accelerated matrix multiplication 7. Armadillo lets us extract individual rows and columns from a matrix using the row and col member functions.

Armadillo internally employs an expression evaluator based on template. Stdcout. MotivationArmadillo and RcppArmadilloArmadillo BasicsApplications Outline 1 Motivation 2 Armadillo and RcppArmadillo 3 Armadillo Basics 4 Applications ASPC Linear Algebra with RcppArmadillo Day 4.

X 10 30. However the speed of the operation can vary tremendously depending on which of those inputs is sparse. Beta 0 10.

The package is a bit overkill for what I want to do now matrix multiplication and indexing to set up mixed-integer linear programs but could be useful as a matrix format for me in the future or for other people who have different needs than I do. Useful for algorithm development directly in C or quick conversion of research code into production environments. X 11 40.

C library for linear algebra scientific computing While chained operations such as addition subtraction and multiplication matrix and element-wise are the primary targets for speed-up opportunities other 1. X 00 10. Multiply the elements of a matrix by their row number then sum them up.

Armadillo uses BLAS for matrix multiplication meaning the speed is dependent on the implementation of BLAS. Matrix-vector multiplication in Rcpp and RcppArmadillo - multMatVeccpp. Betaresize 2.

Beta 1 30. Xresize 3 2. Consider another simple computation.

The multiply by row number is to make it not completely trivial That is we want to obtain. Armamat X. Multiplication of mat1 and mat2 and then store it in output This way One doesnt have to copy huge objects with return value and the output doesnt have to be reallocated with every multiplication.

While chained operations such as addition subtraction and multiplication matrix and element-wise. Void multiply const cx_mat mat1 const cx_mat mat2 cx_mat output. You can use high-speed BLAS replacements to obtain considerably higher performance such as the multi-threaded parallelised OpenBLAS or MKL.

X 20 50. Armadillo is used as a base for other open source projects such as MLPACK a C library for machine learning and pattern recognition 2 and RcppArmadillo a bridge between the R language and C in order to speed up computations 5. A matrix vector in armadillo gains new decimal places after loading it from a file.

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