About JEP 338: Vector API

[Paul Sandoz]

Hi Bruno,

You make a fair point about the complexity. The API is designed to be low-level and literal, making use of current language features, requiring a vector expression be built as an explicit tree (as if input to a compiler).

It would be interesting to express:

  DoubleVector va = ...
  DoubleVector vb = ...
  DoubleVector vc = va.lanewise(vb, (double a, double b) -> -(a*b + b*b));

Whereby the Vector API can reflect over the scalar code of the lambda expression. Then potentially use the same expression to operate over two arrays, the implementation of which may utilize the same expression for fixed length vectors over the variable length arrays.

It is a non-trivial exercise (an understatement!) to modify the Java language and runtime in such a manner, but something like the above is what we have mused about before, and I think is a promising approach.

Paul.


> On Feb 5, 2021, at 6:19 AM, b.lacombe at lug.com wrote:
> 
> About JEP 338: Vector API
> 
> A)  you write :
> -----
> static final VectorSpecies<Float> SPECIES = FloatVector.SPECIES_256;
> 
> void vectorComputation(float[] a, float[] b, float[] c) {
> 
> 
>    for (int i = 0; i < a.length; i += SPECIES.length()) {
>        var m = SPECIES.indexInRange(i, a.length);
>    // FloatVector va, vb, vc;
>        var va = FloatVector.fromArray(SPECIES, a, i, m);
>        var vb = FloatVector.fromArray(SPECIES, b, i, m);
>        var vc = va.mul(va).
>                    add(vb.mul(vb)).
>                    neg();
>        vc.intoArray(c, i, m);
>    }
> }
> -----
> It is very complexe source code to write a simple (a*a+b )*-1
> 
> It 'll more easy, if we can write :
>        FloatVector.forAll(a).mul(a).add(b).neg().toArray(c)
> Where each operator (mul,add,neg) can make the convertion :
>        var va=>FloatVector.fromArray(SPECIES, a, i, m) ...
> Of course optimisation can be done  with a code like :
> ----
>        void mul(a, ... buf){
>                var va = cache.get(a);
>                if( va==nul ){
>                        va =  FloatVector.fromArray(SPECIES, a, i, m);
>                        cache.put(a,va);
>                }
>                //here va
>                .....
>        }
> ----
> 
> 2) A another optimisation can be make by preparing data  whith a "width" 
> operator like :
>        FloatVector
>                .width(a,b,c)
>                .forAll(a)
>                .mul(a).add(b).neg()
>                .toArray(c);
> then source is more easy to read, and less complex 
> what did you think ?
> 
> 
> 3) And if we can upgrade java grammar, a code like this for matrix :
>                c = FloatVector[[ a*a+b*-1 ]] 
> would be ecxellent (where a,b,c must be final array) and so easy ....
> 
> 
> 
> 
> 
> 
> 
> Cordialement
> 
> Bruno LACOMBE
> Multimédia SOLUTIONS
> Site Technologique de Marticot
> 33610 Cestas
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