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[SPARK-4717][MLlib] Optimize BLAS library to avoid de-reference multiple times in loop #3577

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[SPARK-4717][MLlib] Optimize BLAS library to avoid de-reference multiple times in loop #3577

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0316cef
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Dec 3, 2014
62d38c4
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Dec 3, 2014
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DB Tsai committed Dec 3, 2014
commit 62d38c48a0b554ed8c1eb13eef3384e7b0f19c82
26 changes: 13 additions & 13 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 @@ -376,7 +376,7 @@ private[spark] object BLAS extends Serializable with Logging {
}
} else {
// Scale matrix first if `beta` is not equal to 0.0
if (beta != 0.0){
if (beta != 0.0) {
f2jBLAS.dscal(C.values.length, beta, C.values, 1)
}
// Perform matrix multiplication and add to C. The rows of A are multiplied by the columns of
Expand All @@ -391,7 +391,7 @@ private[spark] object BLAS extends Serializable with Logging {
var i = Acols(colCounterForA)
val indEnd = Acols(colCounterForA + 1)
val Bval = Bvals(Bstart + colCounterForA) * alpha
while (i < indEnd){
while (i < indEnd) {
Cvals(Cstart + Arows(i)) += Avals(i) * Bval
i += 1
}
Expand All @@ -403,11 +403,11 @@ private[spark] object BLAS extends Serializable with Logging {
while (colCounterForB < nB) {
var colCounterForA = 0 // The column of A to multiply with the row of B
val Cstart = colCounterForB * mA
while (colCounterForA < kA){
while (colCounterForA < kA) {
var i = Acols(colCounterForA)
val indEnd = Acols(colCounterForA + 1)
val Bval = B(colCounterForB, colCounterForA) * alpha
while (i < indEnd){
while (i < indEnd) {
Cvals(Cstart + Arows(i)) += Avals(i) * Bval
i += 1
}
Expand Down Expand Up @@ -506,38 +506,38 @@ private[spark] object BLAS extends Serializable with Logging {
val xValues = x.values
val yValues = y.values

val mA: Int = if(!trans) A.numRows else A.numCols
val nA: Int = if(!trans) A.numCols else A.numRows
val mA: Int = if (!trans) A.numRows else A.numCols
val nA: Int = if (!trans) A.numCols else A.numRows

val Avals = A.values
val Arows = if (!trans) A.rowIndices else A.colPtrs
val Acols = if (!trans) A.colPtrs else A.rowIndices
// Slicing is easy in this case. This is the optimal multiplication setting for sparse matrices
if (trans){
if (trans) {
var rowCounter = 0
while (rowCounter < mA){
while (rowCounter < mA) {
var i = Arows(rowCounter)
val indEnd = Arows(rowCounter + 1)
var sum = 0.0
while(i < indEnd){
while (i < indEnd) {
sum += Avals(i) * xValues(Acols(i))
i += 1
}
yValues(rowCounter) = beta * yValues(rowCounter) + sum * alpha
yValues(rowCounter) = beta * yValues(rowCounter) + sum * alpha
rowCounter += 1
}
} else {
// Scale vector first if `beta` is not equal to 0.0
if (beta != 0.0){
if (beta != 0.0) {
scal(beta, y)
}
// Perform matrix-vector multiplication and add to y
var colCounterForA = 0
while (colCounterForA < nA){
while (colCounterForA < nA) {
var i = Acols(colCounterForA)
val indEnd = Acols(colCounterForA + 1)
val xVal = xValues(colCounterForA) * alpha
while (i < indEnd){
while (i < indEnd) {
val rowIndex = Arows(i)
yValues(rowIndex) += Avals(i) * xVal
i += 1
Expand Down