Baunsgaard commented on a change in pull request #1480:
URL: https://github.com/apache/systemds/pull/1480#discussion_r768109239
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File path: src/main/java/org/apache/sysds/runtime/matrix/data/MatrixBlock.java
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@@ -5096,34 +5081,52 @@ public final MatrixBlock
aggregateBinaryOperations(MatrixBlock m1, MatrixBlock m
return aggregateBinaryOperations(m1, m2, null, op);
}
- public MatrixBlock aggregateBinaryOperations(MatrixBlock m1,
MatrixBlock m2, MatrixBlock ret, AggregateBinaryOperator op) {
+ public final MatrixBlock aggregateBinaryOperations(MatrixBlock m1,
MatrixBlock m2, MatrixBlock ret, AggregateBinaryOperator op) {
//check input types, dimensions, configuration
- if( m1.clen != m2.rlen ) {
+ if( m1.clen != m2.rlen )
throw new RuntimeException("Dimensions do not match for
matrix multiplication ("+m1.clen+"!="+m2.rlen+").");
- }
- if( !(op.binaryFn instanceof Multiply && op.aggOp.increOp.fn
instanceof Plus) ) {
+ if( !(op.binaryFn instanceof Multiply && op.aggOp.increOp.fn
instanceof Plus) )
throw new DMLRuntimeException("Unsupported binary
aggregate operation: ("+op.binaryFn+", "+op.aggOp+").");
+ if(!(m1 == this || m2 == this))
+ throw new DMLRuntimeException("Invalid
aggregateBinaryOperatio: one of either input should be this");
+ return matrixMult(m1, m2, ret, op.getNumThreads());
+ }
+
+ public MatrixBlock matrixMult(MatrixBlock m1, MatrixBlock m2,
MatrixBlock ret, int k){
+
+ final int rl = m1.rlen;
+ final int cl = m2.clen;
+
+ if(m1.isEmptyBlock(false) || m2.isEmptyBlock(false)) {
+ if(ret == null)
+ return new MatrixBlock(rl, cl, true);
+ else {
+ ret.reset(rl, cl, true);
+ ret.setNonZeros(0);
+ ret.cleanupBlock(true, true);
+ return ret;
+ }
}
-
- //setup meta data (dimensions, sparsity)
- int rl = m1.rlen;
- int cl = m2.clen;
- SparsityEstimate sp = estimateSparsityOnAggBinary(m1, m2, op);
-
- //create output matrix block
- if( ret==null )
- ret = new MatrixBlock(rl, cl, sp.sparse,
sp.estimatedNonZeros);
+
+ final boolean m1Perm = m1.isSparsePermutationMatrix();
+ final boolean ultraSparse =
LibMatrixMult.isUltraSparseMatrixMult(m1, m2, m1Perm);
+ final boolean sparse = !m1Perm && !ultraSparse &&
LibMatrixMult.isSparseOutputMatrixMult(m1, m2);
+ final boolean sparseRet = ultraSparse | sparse;
Review comment:
copied sparsity check from matrix mult lib
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