JEP proposed to target JDK 19: 424: Foreign Function & Memory API (Preview)

• rapaio

  2 66 8.7 Java

  statistics, data mining and machine learning toolbox

Thank you a lot for your thoughts. I have implemented some vectorization into my pet project which I do not want to advertise but I will put some links to some relevant sources. In short I wanted to introduce Vector API into the linear algebra part. I chose the following design: implement a base class to offer default standard implementations. From there I derived three vector classes, one dense, one with stride and another one with indexes. To avoid implementing in each class I made them to implement loadVector and storeVector at some given position. Those are simple methods which basically translated to code like DoubleVector.fromArray(species, array, offset_pos) etc. I tested those implementations against vanilla vector API and I see no issue and there is no memory increase at all. See some vector code here: dense vector, stride vector and some generic code in a base class. I tested with jmh in multiple ways and I see no performance difference. The only hint which I have is that the overloaded methods are inlined by jit since they are small and hot. Perhaps this could be an explanation. What do you think?

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