Jacobot

This library is for fast scientific computing, you can use it for games (its 100k minified and the matrix algos are extreemly fast),

Context is important, also the context is mentioned explicitly! All other BLAS javascript implementations are just fortran recompiles with "emscripten" to webassembly.

This is a (non emscripted) Javascript re-write (Typescript is a superset of Javascript)

Yes it is javascript the bundle is an UMD web/node file you can use in your browser!

BLAS is BLAS there is no "naive" or "expert" or "regular" variant.

* the distributed bundle is always javascript, * it is manual re-write from BLAS reference. * Typescript is a superset of Javascript,. * the repo is selfcontained, "npm install" will install webpack and all tools you need to build the bundle.

I Want to put this here as a first level comment, some people (well actually only one) are making up stuff that JavaScript "fudges" floating point numbers.

Some ppl are going to make up drame to "sound interesting" but i dont see how that is FACTUAL.

The README contains over 8900 lines of 200+ well documented standalone code examples samples comparing JS and R code ,side by side for every function call.

THE RESULTS ARE EXACTLY THE SAME!!

Name dropping like web

Javascript fudges numbers??? I don't see how making stuff up is helpfull.

The README contains over 8900 lines of 200+ well documented standalone examples with many many code samples comparing JS and R side by side for every function call.

THE RESULTS ARE EXACTLY THE SAME!!

You took the effort to throw dirt at JS, but could you not have glossed over the "proof" first?

You seem to not know that IEEE floating is a standard, I suggest you read up on that first

The README in the github JS port has 9000 lines of documentation and code samples (R and JS side by side) to prove the output is the same for all functions.

R is fudging numbers? I dont think so, neither does JS or excel btw.

R shows limited precision to a human, you can control this with options('digits'=22) Example

> options(digits=22)

> 1/1.2

[1] 0.83333333333333337

> options(digits=4)

> 1/1.2

[1] 0.8333

...apples and oranges.... R doesn't support non IEEE standard floats, what you are basically doing is using an external library (GMP), and special functions for addition, multiplication from that package.

Nor can any of the functions in R "base" use GMP.

Again, nobody is fudging numbers, neither R, Java, C, or JS because floating point is implemented on hardware so this argumument is a moot one.

Thanks, Note, JS is breaking benchmarks if compared to Python!

Floating point IEEE 754 is implemented in the hardware (Intel, AMD). It is a feature of the hardware not any language. We need facts not sophism.

Hi, I am owner of libRmath.js and porting BLAS at the moment,

Python and R cant use SIMD either (out of the box), infact no compiler can use SIMD efficiently, therefore gotoBlAS is directly written in assembler for this reason.

Secondly WebGL2 as a vast array of new texture types and Mozilla is implementing the ARB shader. But this has nothing to do with JS perse, because shader langauge is not JS, (its more C like).