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[SPARK-10491] [MLlib] move RowMatrix.dspr to BLAS #8663

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[SPARK-10491] [MLlib] move RowMatrix.dspr to BLAS #8663

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f27dbf3
move dspr to BLAS
hhbyyh Sep 9, 2015
53c9b7b
merge conflict
hhbyyh Sep 15, 2015
f8f2633
change WLS
hhbyyh Sep 15, 2015
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35 changes: 35 additions & 0 deletions mllib/src/main/scala/org/apache/spark/mllib/linalg/BLAS.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -168,6 +168,41 @@ private[spark] object BLAS extends Serializable with Logging {
sum
}

/**
* Adds alpha * x * x.t to a matrix in-place. This is the same as BLAS's DSPR.
*
* @param U the upper triangular part of the matrix packed in an array (column major)
*/
def dspr(alpha: Double, v: Vector, U: Array[Double]): Unit = {
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@mengxr mengxr Sep 9, 2015

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  • Should be spr instead of dspr. We only use double precision.
  • It might be useful to make U a DenseVector (or add a convenient method) for API consistency.
  • Do you mind adding tests for both dense and sparse input?

val n = v.size
v match {
case DenseVector(values) =>
NativeBLAS.dspr("U", n, alpha, values, 1, U)
case SparseVector(size, indices, values) =>
val nnz = indices.length
var colStartIdx = 0
var prevCol = 0
var col = 0
var j = 0
var i = 0
var av = 0.0
while (j < nnz) {
col = indices(j)
// Skip empty columns.
colStartIdx += (col - prevCol) * (col + prevCol + 1) / 2
col = indices(j)
av = alpha * values(j)
i = 0
while (i <= j) {
U(colStartIdx + indices(i)) += av * values(i)
i += 1
}
j += 1
prevCol = col
}
}
}

/**
* y = x
*/
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39 changes: 1 addition & 38 deletions mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
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Expand Up @@ -24,7 +24,6 @@ import scala.collection.mutable.ListBuffer
import breeze.linalg.{DenseMatrix => BDM, DenseVector => BDV, SparseVector => BSV, axpy => brzAxpy,
svd => brzSvd, MatrixSingularException, inv}
import breeze.numerics.{sqrt => brzSqrt}
import com.github.fommil.netlib.BLAS.{getInstance => blas}

import org.apache.spark.Logging
import org.apache.spark.SparkContext._
Expand Down Expand Up @@ -123,7 +122,7 @@ class RowMatrix @Since("1.0.0") (
// Compute the upper triangular part of the gram matrix.
val GU = rows.treeAggregate(new BDV[Double](new Array[Double](nt)))(
seqOp = (U, v) => {
RowMatrix.dspr(1.0, v, U.data)
BLAS.dspr(1.0, v, U.data)
U
}, combOp = (U1, U2) => U1 += U2)

Expand Down Expand Up @@ -673,42 +672,6 @@ class RowMatrix @Since("1.0.0") (
@Experimental
object RowMatrix {

/**
* Adds alpha * x * x.t to a matrix in-place. This is the same as BLAS's DSPR.
*
* @param U the upper triangular part of the matrix packed in an array (column major)
*/
private def dspr(alpha: Double, v: Vector, U: Array[Double]): Unit = {
// TODO: Find a better home (breeze?) for this method.
val n = v.size
v match {
case DenseVector(values) =>
blas.dspr("U", n, alpha, values, 1, U)
case SparseVector(size, indices, values) =>
val nnz = indices.length
var colStartIdx = 0
var prevCol = 0
var col = 0
var j = 0
var i = 0
var av = 0.0
while (j < nnz) {
col = indices(j)
// Skip empty columns.
colStartIdx += (col - prevCol) * (col + prevCol + 1) / 2
col = indices(j)
av = alpha * values(j)
i = 0
while (i <= j) {
U(colStartIdx + indices(i)) += av * values(i)
i += 1
}
j += 1
prevCol = col
}
}
}

/**
* Fills a full square matrix from its upper triangular part.
*/
Expand Down