Examples with Group org.apache.sysml.lops.Group used on opensource projects

Example 46 with Group

use of org.apache.sysml.lops.Group in project systemml by apache.

the class QuaternaryOp method constructMRLopsWeightedDivMM.

private void constructMRLopsWeightedDivMM(WDivMMType wtype) {
    // NOTE: the common case for wdivmm are factors U/V with a rank of 10s to 100s; the current runtime only
    // supports single block outer products (U/V rank <= blocksize, i.e., 1000 by default); we enforce this
    // by applying the hop rewrite for Weighted DivMM only if this constraint holds.
    Hop W = getInput().get(0);
    Hop U = getInput().get(1);
    Hop V = getInput().get(2);
    Hop X = getInput().get(3);
    // MR operator selection, part1
    // size U
    double m1Size = OptimizerUtils.estimateSize(U.getDim1(), U.getDim2());
    // size V
    double m2Size = OptimizerUtils.estimateSize(V.getDim1(), V.getDim2());
    boolean isMapWdivmm = ((!wtype.hasFourInputs() || wtype.hasScalar()) && m1Size + m2Size < OptimizerUtils.getRemoteMemBudgetMap(true));
    if (// broadcast
    !FORCE_REPLICATION && isMapWdivmm) {
        // partitioning of U
        boolean needPartU = !U.dimsKnown() || U.getDim1() * U.getDim2() > DistributedCacheInput.PARTITION_SIZE;
        Lop lU = U.constructLops();
        if (needPartU) {
            // requires partitioning
            lU = new DataPartition(lU, DataType.MATRIX, ValueType.DOUBLE, (m1Size > OptimizerUtils.getLocalMemBudget()) ? ExecType.MR : ExecType.CP, PDataPartitionFormat.ROW_BLOCK_WISE_N);
            lU.getOutputParameters().setDimensions(U.getDim1(), U.getDim2(), getRowsInBlock(), getColsInBlock(), U.getNnz());
            setLineNumbers(lU);
        }
        // partitioning of V
        boolean needPartV = !V.dimsKnown() || V.getDim1() * V.getDim2() > DistributedCacheInput.PARTITION_SIZE;
        Lop lV = V.constructLops();
        if (needPartV) {
            // requires partitioning
            lV = new DataPartition(lV, DataType.MATRIX, ValueType.DOUBLE, (m2Size > OptimizerUtils.getLocalMemBudget()) ? ExecType.MR : ExecType.CP, PDataPartitionFormat.ROW_BLOCK_WISE_N);
            lV.getOutputParameters().setDimensions(V.getDim1(), V.getDim2(), getRowsInBlock(), getColsInBlock(), V.getNnz());
            setLineNumbers(lV);
        }
        // map-side wdivmm always with broadcast
        Lop wdivmm = new WeightedDivMM(W.constructLops(), lU, lV, X.constructLops(), DataType.MATRIX, ValueType.DOUBLE, wtype, ExecType.MR);
        setOutputDimensions(wdivmm);
        setLineNumbers(wdivmm);
        setLops(wdivmm);
    } else // general case
    {
        // MR operator selection part 2 (both cannot happen for wdivmm, otherwise mapwdivmm)
        boolean cacheU = !FORCE_REPLICATION && (m1Size < OptimizerUtils.getRemoteMemBudgetReduce());
        boolean cacheV = !FORCE_REPLICATION && ((!cacheU && m2Size < OptimizerUtils.getRemoteMemBudgetReduce()) || (cacheU && m1Size + m2Size < OptimizerUtils.getRemoteMemBudgetReduce()));
        Group grpW = new Group(W.constructLops(), Group.OperationTypes.Sort, DataType.MATRIX, ValueType.DOUBLE);
        grpW.getOutputParameters().setDimensions(W.getDim1(), W.getDim2(), W.getRowsInBlock(), W.getColsInBlock(), W.getNnz());
        setLineNumbers(grpW);
        Lop grpX = X.constructLops();
        if (wtype.hasFourInputs() && (X.getDataType() != DataType.SCALAR))
            grpX = new Group(grpX, Group.OperationTypes.Sort, DataType.MATRIX, ValueType.DOUBLE);
        grpX.getOutputParameters().setDimensions(X.getDim1(), X.getDim2(), X.getRowsInBlock(), X.getColsInBlock(), X.getNnz());
        setLineNumbers(grpX);
        Lop lU = constructLeftFactorMRLop(U, V, cacheU, m1Size);
        Lop lV = constructRightFactorMRLop(U, V, cacheV, m2Size);
        // reduce-side wdivmm w/ or without broadcast
        Lop wdivmm = new WeightedDivMMR(grpW, lU, lV, grpX, DataType.MATRIX, ValueType.DOUBLE, wtype, cacheU, cacheV, ExecType.MR);
        setOutputDimensions(wdivmm);
        setLineNumbers(wdivmm);
        setLops(wdivmm);
    }
    // in contrast to to wsloss/wsigmoid, wdivmm requires partial aggregation (for the final mm)
    Group grp = new Group(getLops(), Group.OperationTypes.Sort, getDataType(), getValueType());
    setOutputDimensions(grp);
    setLineNumbers(grp);
    Aggregate agg1 = new Aggregate(grp, HopsAgg2Lops.get(AggOp.SUM), getDataType(), getValueType(), ExecType.MR);
    // aggregation uses kahanSum but the inputs do not have correction values
    agg1.setupCorrectionLocation(CorrectionLocationType.NONE);
    setOutputDimensions(agg1);
    setLineNumbers(agg1);
    setLops(agg1);
}

Example 47 with Group

use of org.apache.sysml.lops.Group in project systemml by apache.

the class QuaternaryOp method constructMRLopsWeightedCeMM.

private void constructMRLopsWeightedCeMM(WCeMMType wtype) {
    // NOTE: the common case for wcemm are factors U/V with a rank of 10s to 100s; the current runtime only
    // supports single block outer products (U/V rank <= blocksize, i.e., 1000 by default); we enforce this
    // by applying the hop rewrite for Weighted Cross Entropy only if this constraint holds.
    Hop X = getInput().get(0);
    Hop U = getInput().get(1);
    Hop V = getInput().get(2);
    Hop eps = getInput().get(3);
    // MR operator selection, part1
    // size U
    double m1Size = OptimizerUtils.estimateSize(U.getDim1(), U.getDim2());
    // size V
    double m2Size = OptimizerUtils.estimateSize(V.getDim1(), V.getDim2());
    boolean isMapWcemm = (m1Size + m2Size < OptimizerUtils.getRemoteMemBudgetMap(true));
    if (// broadcast
    !FORCE_REPLICATION && isMapWcemm) {
        // partitioning of U
        boolean needPartU = !U.dimsKnown() || U.getDim1() * U.getDim2() > DistributedCacheInput.PARTITION_SIZE;
        Lop lU = U.constructLops();
        if (needPartU) {
            // requires partitioning
            lU = new DataPartition(lU, DataType.MATRIX, ValueType.DOUBLE, (m1Size > OptimizerUtils.getLocalMemBudget()) ? ExecType.MR : ExecType.CP, PDataPartitionFormat.ROW_BLOCK_WISE_N);
            lU.getOutputParameters().setDimensions(U.getDim1(), U.getDim2(), getRowsInBlock(), getColsInBlock(), U.getNnz());
            setLineNumbers(lU);
        }
        // partitioning of V
        boolean needPartV = !V.dimsKnown() || V.getDim1() * V.getDim2() > DistributedCacheInput.PARTITION_SIZE;
        Lop lV = V.constructLops();
        if (needPartV) {
            // requires partitioning
            lV = new DataPartition(lV, DataType.MATRIX, ValueType.DOUBLE, (m2Size > OptimizerUtils.getLocalMemBudget()) ? ExecType.MR : ExecType.CP, PDataPartitionFormat.ROW_BLOCK_WISE_N);
            lV.getOutputParameters().setDimensions(V.getDim1(), V.getDim2(), getRowsInBlock(), getColsInBlock(), V.getNnz());
            setLineNumbers(lV);
        }
        // map-side wcemm always with broadcast
        Lop wcemm = new WeightedCrossEntropy(X.constructLops(), lU, lV, eps.constructLops(), DataType.MATRIX, ValueType.DOUBLE, wtype, ExecType.MR);
        wcemm.getOutputParameters().setDimensions(1, 1, X.getRowsInBlock(), X.getColsInBlock(), -1);
        setLineNumbers(wcemm);
        Group grp = new Group(wcemm, Group.OperationTypes.Sort, DataType.MATRIX, ValueType.DOUBLE);
        grp.getOutputParameters().setDimensions(1, 1, X.getRowsInBlock(), X.getColsInBlock(), -1);
        setLineNumbers(grp);
        Aggregate agg1 = new Aggregate(grp, HopsAgg2Lops.get(AggOp.SUM), DataType.MATRIX, ValueType.DOUBLE, ExecType.MR);
        // aggregation uses kahanSum
        agg1.setupCorrectionLocation(CorrectionLocationType.NONE);
        agg1.getOutputParameters().setDimensions(1, 1, X.getRowsInBlock(), X.getColsInBlock(), -1);
        setLineNumbers(agg1);
        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
    {
        // MR operator selection part 2
        boolean cacheU = !FORCE_REPLICATION && (m1Size < OptimizerUtils.getRemoteMemBudgetReduce());
        boolean cacheV = !FORCE_REPLICATION && ((!cacheU && m2Size < OptimizerUtils.getRemoteMemBudgetReduce()) || (cacheU && m1Size + m2Size < OptimizerUtils.getRemoteMemBudgetReduce()));
        Group grpX = new Group(X.constructLops(), Group.OperationTypes.Sort, DataType.MATRIX, ValueType.DOUBLE);
        grpX.getOutputParameters().setDimensions(X.getDim1(), X.getDim2(), X.getRowsInBlock(), X.getColsInBlock(), -1);
        setLineNumbers(grpX);
        Lop lU = constructLeftFactorMRLop(U, V, cacheU, m1Size);
        Lop lV = constructRightFactorMRLop(U, V, cacheV, m2Size);
        // reduce-side wcemm w/ or without broadcast
        Lop wcemm = new WeightedCrossEntropyR(grpX, lU, lV, eps.constructLops(), DataType.MATRIX, ValueType.DOUBLE, wtype, cacheU, cacheV, ExecType.MR);
        wcemm.getOutputParameters().setDimensions(1, 1, X.getRowsInBlock(), X.getColsInBlock(), -1);
        setLineNumbers(wcemm);
        Group grp = new Group(wcemm, Group.OperationTypes.Sort, DataType.MATRIX, ValueType.DOUBLE);
        grp.getOutputParameters().setDimensions(1, 1, X.getRowsInBlock(), X.getColsInBlock(), -1);
        setLineNumbers(grp);
        Aggregate agg1 = new Aggregate(grp, HopsAgg2Lops.get(AggOp.SUM), DataType.MATRIX, ValueType.DOUBLE, ExecType.MR);
        // aggregation uses kahanSum
        agg1.setupCorrectionLocation(CorrectionLocationType.NONE);
        agg1.getOutputParameters().setDimensions(1, 1, X.getRowsInBlock(), X.getColsInBlock(), -1);
        setLineNumbers(agg1);
        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);
    }
}

Example 48 with Group

use of org.apache.sysml.lops.Group in project systemml by apache.

the class QuaternaryOp method constructMRLopsWeightedUMM.

private void constructMRLopsWeightedUMM(WUMMType wtype) {
    // NOTE: the common case for wumm are factors U/V with a rank of 10s to 100s; the current runtime only
    // supports single block outer products (U/V rank <= blocksize, i.e., 1000 by default); we enforce this
    // by applying the hop rewrite for Weighted UnaryMM  only if this constraint holds.
    Unary.OperationTypes uop = _uop != null ? HopsOpOp1LopsU.get(_uop) : _sop == OpOp2.POW ? Unary.OperationTypes.POW2 : Unary.OperationTypes.MULTIPLY2;
    Hop X = getInput().get(0);
    Hop U = getInput().get(1);
    Hop V = getInput().get(2);
    // MR operator selection, part1
    // size U
    double m1Size = OptimizerUtils.estimateSize(U.getDim1(), U.getDim2());
    // size V
    double m2Size = OptimizerUtils.estimateSize(V.getDim1(), V.getDim2());
    boolean isMapWumm = (m1Size + m2Size < OptimizerUtils.getRemoteMemBudgetMap(true));
    if (// broadcast
    !FORCE_REPLICATION && isMapWumm) {
        // partitioning of U
        boolean needPartU = !U.dimsKnown() || U.getDim1() * U.getDim2() > DistributedCacheInput.PARTITION_SIZE;
        Lop lU = U.constructLops();
        if (needPartU) {
            // requires partitioning
            lU = new DataPartition(lU, DataType.MATRIX, ValueType.DOUBLE, (m1Size > OptimizerUtils.getLocalMemBudget()) ? ExecType.MR : ExecType.CP, PDataPartitionFormat.ROW_BLOCK_WISE_N);
            lU.getOutputParameters().setDimensions(U.getDim1(), U.getDim2(), getRowsInBlock(), getColsInBlock(), U.getNnz());
            setLineNumbers(lU);
        }
        // partitioning of V
        boolean needPartV = !V.dimsKnown() || V.getDim1() * V.getDim2() > DistributedCacheInput.PARTITION_SIZE;
        Lop lV = V.constructLops();
        if (needPartV) {
            // requires partitioning
            lV = new DataPartition(lV, DataType.MATRIX, ValueType.DOUBLE, (m2Size > OptimizerUtils.getLocalMemBudget()) ? ExecType.MR : ExecType.CP, PDataPartitionFormat.ROW_BLOCK_WISE_N);
            lV.getOutputParameters().setDimensions(V.getDim1(), V.getDim2(), getRowsInBlock(), getColsInBlock(), V.getNnz());
            setLineNumbers(lV);
        }
        // map-side wumm always with broadcast
        Lop wumm = new WeightedUnaryMM(X.constructLops(), lU, lV, DataType.MATRIX, ValueType.DOUBLE, wtype, uop, ExecType.MR);
        setOutputDimensions(wumm);
        setLineNumbers(wumm);
        setLops(wumm);
    // in contrast to wsloss no aggregation required
    } else // general case
    {
        // MR operator selection part 2
        boolean cacheU = !FORCE_REPLICATION && (m1Size < OptimizerUtils.getRemoteMemBudgetReduce());
        boolean cacheV = !FORCE_REPLICATION && ((!cacheU && m2Size < OptimizerUtils.getRemoteMemBudgetReduce()) || (cacheU && m1Size + m2Size < OptimizerUtils.getRemoteMemBudgetReduce()));
        Group grpX = new Group(X.constructLops(), Group.OperationTypes.Sort, DataType.MATRIX, ValueType.DOUBLE);
        grpX.getOutputParameters().setDimensions(X.getDim1(), X.getDim2(), X.getRowsInBlock(), X.getColsInBlock(), X.getNnz());
        setLineNumbers(grpX);
        Lop lU = constructLeftFactorMRLop(U, V, cacheU, m1Size);
        Lop lV = constructRightFactorMRLop(U, V, cacheV, m2Size);
        // reduce-side wumm w/ or without broadcast
        Lop wumm = new WeightedUnaryMMR(grpX, lU, lV, DataType.MATRIX, ValueType.DOUBLE, wtype, uop, cacheU, cacheV, ExecType.MR);
        setOutputDimensions(wumm);
        setLineNumbers(wumm);
        setLops(wumm);
    // in contrast to wsloss no aggregation required
    }
}

Example 49 with Group

use of org.apache.sysml.lops.Group in project systemml by apache.

the class QuaternaryOp method constructRightFactorMRLop.

private Lop constructRightFactorMRLop(Hop U, Hop V, boolean cacheV, double m2Size) {
    Lop lV = null;
    if (cacheV) {
        // partitioning of V for read through distributed cache
        boolean needPartV = !V.dimsKnown() || V.getDim1() * V.getDim2() > DistributedCacheInput.PARTITION_SIZE;
        lV = V.constructLops();
        if (needPartV) {
            // requires partitioning
            lV = new DataPartition(lV, DataType.MATRIX, ValueType.DOUBLE, (m2Size > OptimizerUtils.getLocalMemBudget()) ? ExecType.MR : ExecType.CP, PDataPartitionFormat.ROW_BLOCK_WISE_N);
            lV.getOutputParameters().setDimensions(V.getDim1(), V.getDim2(), getRowsInBlock(), getColsInBlock(), V.getNnz());
            setLineNumbers(lV);
        }
    } else {
        // replication of t(V) for shuffle to target block
        Transform ltV = new Transform(V.constructLops(), HopsTransf2Lops.get(ReOrgOp.TRANSPOSE), getDataType(), getValueType(), ExecType.MR);
        ltV.getOutputParameters().setDimensions(V.getDim2(), V.getDim1(), V.getColsInBlock(), V.getRowsInBlock(), V.getNnz());
        setLineNumbers(ltV);
        // nrow of U determines num replicates
        Lop offset = createOffsetLop(U, false);
        lV = new RepMat(ltV, offset, false, V.getDataType(), V.getValueType());
        lV.getOutputParameters().setDimensions(V.getDim2(), V.getDim1(), V.getColsInBlock(), V.getRowsInBlock(), V.getNnz());
        setLineNumbers(lV);
        Group grpV = new Group(lV, Group.OperationTypes.Sort, DataType.MATRIX, ValueType.DOUBLE);
        grpV.getOutputParameters().setDimensions(V.getDim2(), V.getDim1(), V.getColsInBlock(), V.getRowsInBlock(), -1);
        setLineNumbers(grpV);
        lV = grpV;
    }
    return lV;
}

Example 50 with Group

use of org.apache.sysml.lops.Group in project systemml by apache.

the class TernaryOp method constructLopsTernaryDefault.

private void constructLopsTernaryDefault() {
    ExecType et = optFindExecType();
    if (getInput().stream().allMatch(h -> h.getDataType().isScalar()))
        // always CP for pure scalar operations
        et = ExecType.CP;
    Ternary plusmult = null;
    if (et == ExecType.CP || et == ExecType.SPARK || et == ExecType.GPU) {
        plusmult = new Ternary(HopsOpOp3Lops.get(_op), getInput().get(0).constructLops(), getInput().get(1).constructLops(), getInput().get(2).constructLops(), getDataType(), getValueType(), et);
    } else {
        // MR
        Hop first = getInput().get(0);
        Hop second = getInput().get(1);
        Hop third = getInput().get(2);
        Lop firstLop = first.constructLops();
        if (first.getDataType().isMatrix()) {
            firstLop = new Group(firstLop, Group.OperationTypes.Sort, getDataType(), getValueType());
            setLineNumbers(firstLop);
            setOutputDimensions(firstLop);
        }
        Lop secondLop = second.constructLops();
        if (second.getDataType().isMatrix()) {
            secondLop = new Group(secondLop, Group.OperationTypes.Sort, getDataType(), getValueType());
            setLineNumbers(secondLop);
            setOutputDimensions(secondLop);
        }
        Lop thirdLop = third.constructLops();
        if (third.getDataType().isMatrix()) {
            thirdLop = new Group(thirdLop, Group.OperationTypes.Sort, getDataType(), getValueType());
            setLineNumbers(thirdLop);
            setOutputDimensions(thirdLop);
        }
        plusmult = new Ternary(HopsOpOp3Lops.get(_op), firstLop, secondLop, thirdLop, getDataType(), getValueType(), et);
    }
    setOutputDimensions(plusmult);
    setLineNumbers(plusmult);
    setLops(plusmult);
}