Examples with DirectionTypes org.apache.sysml.lops.PartialAggregate.DirectionTypes used on opensource projects

Example 1 with DirectionTypes

use of org.apache.sysml.lops.PartialAggregate.DirectionTypes 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();
}

Example 2 with DirectionTypes

use of org.apache.sysml.lops.PartialAggregate.DirectionTypes in project incubator-systemml by apache.

the class AggUnaryOp method constructLopsTernaryAggregateRewrite.

private Lop constructLopsTernaryAggregateRewrite(ExecType et) throws HopsException, LopsException {
    Hop input1 = getInput().get(0);
    Hop input11 = input1.getInput().get(0);
    Hop input12 = input1.getInput().get(1);
    Lop in1 = null;
    Lop in2 = null;
    Lop in3 = null;
    if (input11 instanceof BinaryOp && ((BinaryOp) input11).getOp() == OpOp2.MULT) {
        in1 = input11.getInput().get(0).constructLops();
        in2 = input11.getInput().get(1).constructLops();
        in3 = input12.constructLops();
    } else if (input12 instanceof BinaryOp && ((BinaryOp) input12).getOp() == OpOp2.MULT) {
        in1 = input11.constructLops();
        in2 = input12.getInput().get(0).constructLops();
        in3 = input12.getInput().get(1).constructLops();
    } else {
        in1 = input11.constructLops();
        in2 = input12.constructLops();
        in3 = new LiteralOp(1).constructLops();
    }
    //create new ternary aggregate operator 
    int k = OptimizerUtils.getConstrainedNumThreads(_maxNumThreads);
    // The execution type of a unary aggregate instruction should depend on the execution type of inputs to avoid OOM
    // Since we only support matrix-vector and not vector-matrix, checking the execution type of input1 should suffice.
    ExecType et_input = input1.optFindExecType();
    DirectionTypes dir = HopsDirection2Lops.get(_direction);
    return new TernaryAggregate(in1, in2, in3, Aggregate.OperationTypes.KahanSum, Binary.OperationTypes.MULTIPLY, dir, getDataType(), ValueType.DOUBLE, et_input, k);
}