xuyang1706 commented on a change in pull request #9732: [FLINK-14153][ml] Add
to BLAS a method that performs DenseMatrix and SparseVector multiplication.
URL: https://github.com/apache/flink/pull/9732#discussion_r336441369
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File path:
flink-ml-parent/flink-ml-lib/src/main/java/org/apache/flink/ml/common/linalg/BLAS.java
##########
@@ -146,4 +148,38 @@ public static void gemv(double alpha, DenseMatrix matA,
boolean transA,
final String ta = transA ? "T" : "N";
NATIVE_BLAS.dgemv(ta, m, n, alpha, matA.getData(), lda,
x.getData(), 1, beta, y.getData(), 1);
}
+
+ /**
+ * y := alpha * A * x + beta * y .
+ */
+ public static void gemv(double alpha, DenseMatrix matA, boolean transA,
+ SparseVector x, double
beta, DenseVector y) {
+ if (transA) {
+ Preconditions.checkArgument(matA.numCols() == y.size()
&& matA.numRows() == x.size(),
+ "Matrix and vector size mismatched.");
+ } else {
+ Preconditions.checkArgument(matA.numRows() == y.size()
&& matA.numCols() == x.size(),
+ "Matrix and vector size mismatched.");
+ }
+ final int m = matA.numRows();
+ final int n = matA.numCols();
+ if (transA) {
+ int start = 0;
+ for (int i = 0; i < n; i++) {
+ double s = 0.;
+ for (int j = 0; j < x.indices.length; j++) {
+ s += x.values[j] * matA.data[start +
x.indices[j]];
+ }
+ y.data[i] = beta * y.data[i] + alpha * s;
+ start += m;
+ }
+ } else {
+ scal(beta, y);
+ for (int i = 0; i < x.indices.length; i++) {
+ int index = x.indices[i];
+ double value = alpha * x.values[i];
+ F2J_BLAS.daxpy(m, value, matA.data, index * m,
1, y.data, 0, 1);
Review comment:
There are two reasons I use BLAS here.
1. BLAS is a mature linear algebra libarary, which pays a lot of attension
to data locality, thus it is more cache friendly than naive implementation.
Usually we gain a lot of permformace improvement on level-2/level-3 BLAS
routine through calling native (JNI) BLAS, while F2J BLAS is better in level-1
BLAS routines.
2. In the case here, y is first scaled by b, then each columns of Ax is
added to y. It is inevitable that y would be visited more than once.
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