Currently, support for linear algebra operations in stdlib is limited. The goal of this idea would be to implement algorithms for linear algebra operations such as matrix multiplication, calculating the matrix inverse, eigenvalue calculation, singular value decomposition, Cholesky & LU Decomposition, and the like. This overlaps with the goal of increasing the amount of BLAS and LAPACK that is available in stdlib.
Expected Outcomes
stdlib will have extended support for linear algebra operations which can be used to solve problems involving matrices and vectors.
Involved Software
No other software should be necessary. However, we will need to do a needs analysis to determine which prerequisite packages/functionality is necessary in order to allow these operations to be implemented (e.g., BLAS, ndarray slicing, etc).
Prerequisite Knowledge
JavaScript, Node.js. C, Fortran. Familiarity with linear algebra would be very useful, as will need to consult and understand reference implementations.
Difficulty
Hard. Depends on the reference implementation requirements and algorithmic difficulty.
Idea
Currently, support for linear algebra operations in stdlib is limited. The goal of this idea would be to implement algorithms for linear algebra operations such as matrix multiplication, calculating the matrix inverse, eigenvalue calculation, singular value decomposition, Cholesky & LU Decomposition, and the like. This overlaps with the goal of increasing the amount of BLAS and LAPACK that is available in stdlib.
Expected Outcomes
stdlib will have extended support for linear algebra operations which can be used to solve problems involving matrices and vectors.
Involved Software
No other software should be necessary. However, we will need to do a needs analysis to determine which prerequisite packages/functionality is necessary in order to allow these operations to be implemented (e.g., BLAS, ndarray slicing, etc).
Prerequisite Knowledge
JavaScript, Node.js. C, Fortran. Familiarity with linear algebra would be very useful, as will need to consult and understand reference implementations.
Difficulty
Hard. Depends on the reference implementation requirements and algorithmic difficulty.
Project Length
350 hours.
Potential Mentors
@kgryte @Planeshifter @Pranavchiku @czgdp1807 @rreusser