srowen closed pull request #18936: [SPARK-21688][ML][MLLIB] make native BLAS
the first choice for BLAS level 1 operations for dense data
URL: https://github.com/apache/spark/pull/18936
This is a PR merged from a forked repository.
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diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/BLAS.scala
b/mllib/src/main/scala/org/apache/spark/mllib/linalg/BLAS.scala
index cb97742245689..97fc1773e04b3 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/BLAS.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/BLAS.scala
@@ -65,7 +65,7 @@ private[spark] object BLAS extends Serializable with Logging {
*/
private def axpy(a: Double, x: DenseVector, y: DenseVector): Unit = {
val n = x.size
- f2jBLAS.daxpy(n, a, x.values, 1, y.values, 1)
+ nativeBLAS.daxpy(n, a, x.values, 1, y.values, 1)
}
/**
@@ -125,7 +125,7 @@ private[spark] object BLAS extends Serializable with
Logging {
*/
private def dot(x: DenseVector, y: DenseVector): Double = {
val n = x.size
- f2jBLAS.ddot(n, x.values, 1, y.values, 1)
+ nativeBLAS.ddot(n, x.values, 1, y.values, 1)
}
/**
@@ -222,7 +222,7 @@ private[spark] object BLAS extends Serializable with
Logging {
case sx: SparseVector =>
f2jBLAS.dscal(sx.values.length, a, sx.values, 1)
case dx: DenseVector =>
- f2jBLAS.dscal(dx.values.length, a, dx.values, 1)
+ nativeBLAS.dscal(dx.values.length, a, dx.values, 1)
case _ =>
throw new IllegalArgumentException(s"scal doesn't support vector type
${x.getClass}.")
}
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