[Idea]: add LAPACK bindings and implementations for linear algebra #95
Labels
difficulty: 4
Likely to be challenging with ambitious goals.
idea
Potential GSoC project idea.
priority: high
High priority.
tech: c
Involves programming in C.
tech: fortran
Involves programming in Fortran.
tech: javascript
Involves programming in JavaScript.
tech: native addons
Involves developing Node.js native add-ons.
tech: nodejs
Requires developing with Node.js.
Idea
LAPACK routines are standard building blocks for performing basic vector and matrix operations. These building blocks are leveraged by most modern numerical programming languages and libraries, including NumPy, SciPy, Julia, MATLAB, R, and others.
The goal of this idea is to
Expected outcomes
Users will be able to call LAPACK routines from JavaScript. In web browsers, LAPACK routines will be in JavaScript. In Node.js, provided native bindings have been compiled, LAPACK routines will either be ported reference implementations or hardware optimized system libraries.
Status
Some work has begun toward this effort. See https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/lapack/base.
Involved software
No other software is necessary apart from standard compilers (GCC, gfortran).
Technology
C, JavaScript, Fortran, nodejs, native addons
Other technology
None.
Difficulty
4
Difficulty justification
Familiarity with C and Fortran will be beneficial. This idea mainly involves porting existing implementations and doing so in a manner which conforms with stdlib conventions. Some of the reference implementations are likely to be quite involved and testing the correct output can be tricky, especially for lower-level helper routines.
Prerequisite knowledge
C, Fortran, JavaScript, Node.js.
Project length
350
Checklist
[Idea]:
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