Performance
The core aim of this library, is to provide platform native, friction free performance. I'm confident that I can't do better than this - at least outside of an absurd about of effort.
In general cross platform performance is a hard problem. We sidestep it by simply providing compiletime @inline shims to platform native BLAS implementations.
| JVM | JS | Native | Cross | |
|---|---|---|---|---|
| Data structure | Array[Double] |
Float64Array |
Array[Double] |
NArray[Double] |
| Shims to | https://github.com/luhenry/netlib | https://github.com/stdlib-js/blas | CBLAS | Best available |
Consider browsing the vecxt api, and particulaly the extensions object. You'll see that most definitions are @inline anotated - i.e. there is zero runtime overhead calling this library.
JS
On Node, this shim ships with it's own C BLAS implementation.
In browser / elsewhere, it's done in loop-unrolled native arrays.
TODO: Investigate webassembly?
In this article