Package Exports
- vectorious
This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (vectorious) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.
Readme
Vectorious
Vectorious is a high performance linear algebra library. It is written in JavaScript using nBLAS for single- and double-precision C++ bindings to CBLAS. In the future the goal is to also include C++ bindings to LAPACK. With native fallbacks, it can be used without the bindings in supported browsers.
$ npm install vectorious
$ npm test
$ npm run benchmarkTo enjoy the full performance of vectorious, you will need to have BLAS installed
on your system. It is by default included in the OSX Accelerate framework. On Ubuntu/Debian you can e.g. use libblas (apt-get libblas-dev). If you use Windows, you can install LAPACK.
Browser
Download a release and use it like this:
<script src="vectorious-4.0.0.js"></script>
<script>
// e.g. var vector = new vectorious.Vector()
</script>Documentation
Examples
Benchmarks
The following plot compares Vectorious (4.0.4) benchmarks for basic vector operations with three popular matrix/vector libraries: numeric.js, sylvester and math.js.
These benchmarks were performed on a MacBook Pro (i5 2.7GHz, OSX 10.11, 8GB RAM) with benchmark.js on random vectors of 1 048 576 elements.
The following plot compares Vectorious (4.0.4) benchmarks for basic matrix operations with three popular matrix/vector libraries: numeric.js, sylvester and math.js.
These benchmarks were performed on a MacBook Pro (i5 2.7GHz, OSX 10.11, 8GB RAM) with benchmark.js on random matrices of 256x256 elements.
