use of org.apache.sysml.lops.UAggOuterChain in project incubator-systemml by apache.
the class AggUnaryOp method constructLops.
@Override
public Lop constructLops() throws HopsException, LopsException {
//return already created lops
if (getLops() != null)
return getLops();
try {
ExecType et = optFindExecType();
Hop input = getInput().get(0);
if (et == ExecType.CP) {
Lop agg1 = null;
if (isTernaryAggregateRewriteApplicable(et)) {
agg1 = constructLopsTernaryAggregateRewrite(et);
} else if (isUnaryAggregateOuterCPRewriteApplicable()) {
OperationTypes op = HopsAgg2Lops.get(_op);
DirectionTypes dir = HopsDirection2Lops.get(_direction);
BinaryOp binput = (BinaryOp) getInput().get(0);
agg1 = new UAggOuterChain(binput.getInput().get(0).constructLops(), binput.getInput().get(1).constructLops(), op, dir, HopsOpOp2LopsB.get(binput.getOp()), DataType.MATRIX, getValueType(), ExecType.CP);
PartialAggregate.setDimensionsBasedOnDirection(agg1, getDim1(), getDim2(), input.getRowsInBlock(), input.getColsInBlock(), dir);
if (getDataType() == DataType.SCALAR) {
UnaryCP unary1 = new UnaryCP(agg1, HopsOpOp1LopsUS.get(OpOp1.CAST_AS_SCALAR), getDataType(), getValueType());
unary1.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
setLineNumbers(unary1);
setLops(unary1);
}
} else {
//general case
int k = OptimizerUtils.getConstrainedNumThreads(_maxNumThreads);
if (DMLScript.USE_ACCELERATOR && (DMLScript.FORCE_ACCELERATOR || getMemEstimate() < OptimizerUtils.GPU_MEMORY_BUDGET)) {
// Only implemented methods for GPU
if ((_op == AggOp.SUM && (_direction == Direction.RowCol || _direction == Direction.Row || _direction == Direction.Col)) || (_op == AggOp.SUM_SQ && (_direction == Direction.RowCol || _direction == Direction.Row || _direction == Direction.Col)) || (_op == AggOp.MAX && (_direction == Direction.RowCol || _direction == Direction.Row || _direction == Direction.Col)) || (_op == AggOp.MIN && (_direction == Direction.RowCol || _direction == Direction.Row || _direction == Direction.Col)) || (_op == AggOp.MEAN && (_direction == Direction.RowCol || _direction == Direction.Row || _direction == Direction.Col)) || (_op == AggOp.VAR && (_direction == Direction.RowCol || _direction == Direction.Row || _direction == Direction.Col)) || (_op == AggOp.PROD && (_direction == Direction.RowCol))) {
et = ExecType.GPU;
k = 1;
}
}
agg1 = new PartialAggregate(input.constructLops(), HopsAgg2Lops.get(_op), HopsDirection2Lops.get(_direction), getDataType(), getValueType(), et, k);
}
setOutputDimensions(agg1);
setLineNumbers(agg1);
setLops(agg1);
if (getDataType() == DataType.SCALAR) {
agg1.getOutputParameters().setDimensions(1, 1, getRowsInBlock(), getColsInBlock(), getNnz());
}
} else if (et == ExecType.MR) {
OperationTypes op = HopsAgg2Lops.get(_op);
DirectionTypes dir = HopsDirection2Lops.get(_direction);
//unary aggregate operation
Lop transform1 = null;
if (isUnaryAggregateOuterRewriteApplicable()) {
BinaryOp binput = (BinaryOp) getInput().get(0);
transform1 = new UAggOuterChain(binput.getInput().get(0).constructLops(), binput.getInput().get(1).constructLops(), op, dir, HopsOpOp2LopsB.get(binput.getOp()), DataType.MATRIX, getValueType(), ExecType.MR);
PartialAggregate.setDimensionsBasedOnDirection(transform1, getDim1(), getDim2(), input.getRowsInBlock(), input.getColsInBlock(), dir);
} else //default
{
transform1 = new PartialAggregate(input.constructLops(), op, dir, DataType.MATRIX, getValueType());
((PartialAggregate) transform1).setDimensionsBasedOnDirection(getDim1(), getDim2(), input.getRowsInBlock(), input.getColsInBlock());
}
setLineNumbers(transform1);
//aggregation if required
Lop aggregate = null;
Group group1 = null;
Aggregate agg1 = null;
if (requiresAggregation(input, _direction) || transform1 instanceof UAggOuterChain) {
group1 = new Group(transform1, Group.OperationTypes.Sort, DataType.MATRIX, getValueType());
group1.getOutputParameters().setDimensions(getDim1(), getDim2(), input.getRowsInBlock(), input.getColsInBlock(), getNnz());
setLineNumbers(group1);
agg1 = new Aggregate(group1, HopsAgg2Lops.get(_op), DataType.MATRIX, getValueType(), et);
agg1.getOutputParameters().setDimensions(getDim1(), getDim2(), input.getRowsInBlock(), input.getColsInBlock(), getNnz());
agg1.setupCorrectionLocation(PartialAggregate.getCorrectionLocation(op, dir));
setLineNumbers(agg1);
aggregate = agg1;
} else {
((PartialAggregate) transform1).setDropCorrection();
aggregate = transform1;
}
setLops(aggregate);
//cast if required
if (getDataType() == DataType.SCALAR) {
// Set the dimensions of PartialAggregate LOP based on the
// direction in which aggregation is performed
PartialAggregate.setDimensionsBasedOnDirection(transform1, input.getDim1(), input.getDim2(), input.getRowsInBlock(), input.getColsInBlock(), dir);
if (group1 != null && agg1 != null) {
//if aggregation required
group1.getOutputParameters().setDimensions(input.getDim1(), input.getDim2(), input.getRowsInBlock(), input.getColsInBlock(), getNnz());
agg1.getOutputParameters().setDimensions(1, 1, input.getRowsInBlock(), input.getColsInBlock(), getNnz());
}
UnaryCP unary1 = new UnaryCP(aggregate, HopsOpOp1LopsUS.get(OpOp1.CAST_AS_SCALAR), getDataType(), getValueType());
unary1.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
setLineNumbers(unary1);
setLops(unary1);
}
} else if (et == ExecType.SPARK) {
OperationTypes op = HopsAgg2Lops.get(_op);
DirectionTypes dir = HopsDirection2Lops.get(_direction);
//unary aggregate
if (isTernaryAggregateRewriteApplicable(et)) {
Lop aggregate = constructLopsTernaryAggregateRewrite(et);
//0x0 (scalar)
setOutputDimensions(aggregate);
setLineNumbers(aggregate);
setLops(aggregate);
} else if (isUnaryAggregateOuterSPRewriteApplicable()) {
BinaryOp binput = (BinaryOp) getInput().get(0);
Lop transform1 = new UAggOuterChain(binput.getInput().get(0).constructLops(), binput.getInput().get(1).constructLops(), op, dir, HopsOpOp2LopsB.get(binput.getOp()), DataType.MATRIX, getValueType(), ExecType.SPARK);
PartialAggregate.setDimensionsBasedOnDirection(transform1, getDim1(), getDim2(), input.getRowsInBlock(), input.getColsInBlock(), dir);
setLineNumbers(transform1);
setLops(transform1);
if (getDataType() == DataType.SCALAR) {
UnaryCP unary1 = new UnaryCP(transform1, HopsOpOp1LopsUS.get(OpOp1.CAST_AS_SCALAR), getDataType(), getValueType());
unary1.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
setLineNumbers(unary1);
setLops(unary1);
}
} else //default
{
boolean needAgg = requiresAggregation(input, _direction);
SparkAggType aggtype = getSparkUnaryAggregationType(needAgg);
PartialAggregate aggregate = new PartialAggregate(input.constructLops(), HopsAgg2Lops.get(_op), HopsDirection2Lops.get(_direction), DataType.MATRIX, getValueType(), aggtype, et);
aggregate.setDimensionsBasedOnDirection(getDim1(), getDim2(), input.getRowsInBlock(), input.getColsInBlock());
setLineNumbers(aggregate);
setLops(aggregate);
if (getDataType() == DataType.SCALAR) {
UnaryCP unary1 = new UnaryCP(aggregate, HopsOpOp1LopsUS.get(OpOp1.CAST_AS_SCALAR), getDataType(), getValueType());
unary1.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
setLineNumbers(unary1);
setLops(unary1);
}
}
}
} catch (Exception e) {
throw new HopsException(this.printErrorLocation() + "In AggUnary Hop, error constructing Lops ", e);
}
//add reblock/checkpoint lops if necessary
constructAndSetLopsDataFlowProperties();
//return created lops
return getLops();
}
Aggregations