Making cross platform, compute intense vector problems less... vexing.
Aims to provide convienent and intuitive syntax for vector computations, whilst guaranteeing best-in-class performance on all platforms.
| JVM | JS | Native | |
|---|---|---|---|
| Data structure | Array[Double] |
Float64Array |
Array[Double] |
| Shims to | https://github.com/luhenry/netlib | https://github.com/stdlib-js/blas | CBLAS |
https://github.com/dragonfly-ai/narr
Surprise! Add that dependancy, express your computation in NArray and get best-in-class, native performance (no runtime overhead) on all platforms.
Note: Narr is not distributed "out the box", but it is recommended for anything cross platform.
Supported operationsa re currently very basic, but we share a single test suite across all platforms, e.g.
val v1 = NArray[Double](1.0, 2.0, 3.0)
val v2 = NArray[Double](3.0, 2.0, 1.0)
val v3 = v1 + v2
assertEqualsDouble(v3(0), 4, 0.00001)
assertEqualsDouble(v3(1), 4, 0.00001)
assertEqualsDouble(v3(2), 4, 0.00001)
Not?