Github user hqzizania commented on the issue:
https://github.com/apache/spark/pull/13891
This is a prototype. Actually, it is critical if it will be faster = =!
I have done a simple test, the effect is up to "number of user for each
product". The "number of user for each product" is equal to the range of
[i](https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala#L1299)
in each loop. If a considerable number of vectors can be stack, its nativeBLAS
will speeup > 3x than original nativeBLAS, but it is still slower than original
F2JBLAS. In my test for the original ALS, nativeBLAS is much slower than
F2JBLAS.
Anyway I don't know if "number of user for each product" can be very large
in a real case.
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