Examples with MatrixBlock org.apache.sysml.runtime.matrix.data.MatrixBlock used on opensource projects

Example 81 with MatrixBlock

use of org.apache.sysml.runtime.matrix.data.MatrixBlock in project incubator-systemml by apache.

the class TernaryInstruction method processInstruction.

@Override
public void processInstruction(Class<? extends MatrixValue> valueClass, CachedValueMap cachedValues, IndexedMatrixValue tempValue, IndexedMatrixValue zeroInput, int blockRowFactor, int blockColFactor) {
    MatrixBlock lm1 = input1.isMatrix() ? (MatrixBlock) cachedValues.getFirst(ixinput1).getValue() : m1;
    MatrixBlock lm2 = input2.isMatrix() ? (MatrixBlock) cachedValues.getFirst(ixinput2).getValue() : m2;
    MatrixBlock lm3 = input3.isMatrix() ? (MatrixBlock) cachedValues.getFirst(ixinput3).getValue() : m3;
    MatrixIndexes ixin = input1.isMatrix() ? cachedValues.getFirst(ixinput1).getIndexes() : input2.isMatrix() ? cachedValues.getFirst(ixinput2).getIndexes() : cachedValues.getFirst(ixinput3).getIndexes();
    // prepare output
    IndexedMatrixValue out = new IndexedMatrixValue(new MatrixIndexes(), new MatrixBlock());
    out.getIndexes().setIndexes(ixin);
    // process instruction
    TernaryOperator op = (TernaryOperator) optr;
    lm1.ternaryOperations(op, lm2, lm3, (MatrixBlock) out.getValue());
    // put the output value in the cache
    cachedValues.add(ixoutput, out);
}

Example 82 with MatrixBlock

use of org.apache.sysml.runtime.matrix.data.MatrixBlock in project incubator-systemml by apache.

the class AggregateTernarySPInstruction method processInstruction.

@Override
public void processInstruction(ExecutionContext ec) {
    SparkExecutionContext sec = (SparkExecutionContext) ec;
    // get inputs
    MatrixCharacteristics mcIn = sec.getMatrixCharacteristics(input1.getName());
    JavaPairRDD<MatrixIndexes, MatrixBlock> in1 = sec.getBinaryBlockRDDHandleForVariable(input1.getName());
    JavaPairRDD<MatrixIndexes, MatrixBlock> in2 = sec.getBinaryBlockRDDHandleForVariable(input2.getName());
    JavaPairRDD<MatrixIndexes, MatrixBlock> in3 = // matrix or literal 1
    input3.isLiteral() ? // matrix or literal 1
    null : sec.getBinaryBlockRDDHandleForVariable(input3.getName());
    // execute aggregate ternary operation
    AggregateTernaryOperator aggop = (AggregateTernaryOperator) _optr;
    JavaPairRDD<MatrixIndexes, MatrixBlock> out = null;
    if (in3 != null) {
        // 3 inputs
        out = in1.join(in2).join(in3).mapToPair(new RDDAggregateTernaryFunction(aggop));
    } else {
        // 2 inputs (third is literal 1)
        out = in1.join(in2).mapToPair(new RDDAggregateTernaryFunction2(aggop));
    }
    // aggregate partial results
    if (// tak+*
    aggop.indexFn instanceof ReduceAll) {
        // aggregate and create output (no lineage because scalar)
        MatrixBlock tmp = RDDAggregateUtils.sumStable(out.values());
        DoubleObject ret = new DoubleObject(tmp.getValue(0, 0));
        sec.setVariable(output.getName(), ret);
    } else if (// tack+* single block
    mcIn.dimsKnown() && mcIn.getCols() <= mcIn.getColsPerBlock()) {
        // single block aggregation and drop correction
        MatrixBlock ret = RDDAggregateUtils.aggStable(out, aggop.aggOp);
        ret.dropLastRowsOrColumns(aggop.aggOp.correctionLocation);
        // put output block into symbol table (no lineage because single block)
        // this also includes implicit maintenance of matrix characteristics
        sec.setMatrixOutput(output.getName(), ret, getExtendedOpcode());
    } else // tack+* multi block
    {
        // multi-block aggregation and drop correction
        out = RDDAggregateUtils.aggByKeyStable(out, aggop.aggOp, false);
        out = out.mapValues(new AggregateDropCorrectionFunction(aggop.aggOp));
        // put output RDD handle into symbol table
        updateUnaryAggOutputMatrixCharacteristics(sec, aggop.indexFn);
        sec.setRDDHandleForVariable(output.getName(), out);
        sec.addLineageRDD(output.getName(), input1.getName());
        sec.addLineageRDD(output.getName(), input2.getName());
        if (in3 != null)
            sec.addLineageRDD(output.getName(), input3.getName());
    }
}

Example 83 with MatrixBlock

use of org.apache.sysml.runtime.matrix.data.MatrixBlock in project incubator-systemml by apache.

the class AppendGSPInstruction method processInstruction.

@Override
public void processInstruction(ExecutionContext ec) {
    // general case append (map-extend, aggregate)
    SparkExecutionContext sec = (SparkExecutionContext) ec;
    checkBinaryAppendInputCharacteristics(sec, _cbind, false, false);
    MatrixCharacteristics mc1 = sec.getMatrixCharacteristics(input1.getName());
    MatrixCharacteristics mc2 = sec.getMatrixCharacteristics(input2.getName());
    JavaPairRDD<MatrixIndexes, MatrixBlock> in1 = sec.getBinaryBlockRDDHandleForVariable(input1.getName());
    JavaPairRDD<MatrixIndexes, MatrixBlock> in2 = sec.getBinaryBlockRDDHandleForVariable(input2.getName());
    JavaPairRDD<MatrixIndexes, MatrixBlock> out = null;
    // General case: This one needs shifting and merging and hence has huge performance hit.
    JavaPairRDD<MatrixIndexes, MatrixBlock> shifted_in2 = in2.flatMapToPair(new ShiftMatrix(mc1, mc2, _cbind));
    out = in1.cogroup(shifted_in2).mapToPair(new MergeWithShiftedBlocks(mc1, mc2, _cbind));
    // put output RDD handle into symbol table
    updateBinaryAppendOutputMatrixCharacteristics(sec, _cbind);
    sec.setRDDHandleForVariable(output.getName(), out);
    sec.addLineageRDD(output.getName(), input1.getName());
    sec.addLineageRDD(output.getName(), input2.getName());
}

Example 84 with MatrixBlock

use of org.apache.sysml.runtime.matrix.data.MatrixBlock in project incubator-systemml by apache.

the class BinUaggChainSPInstruction method processInstruction.

@Override
public void processInstruction(ExecutionContext ec) {
    SparkExecutionContext sec = (SparkExecutionContext) ec;
    // get input
    JavaPairRDD<MatrixIndexes, MatrixBlock> in = sec.getBinaryBlockRDDHandleForVariable(input1.getName());
    // execute unary builtin operation
    JavaPairRDD<MatrixIndexes, MatrixBlock> out = in.mapValues(new RDDBinUaggChainFunction(_bOp, _uaggOp));
    // set output RDD
    updateUnaryOutputMatrixCharacteristics(sec);
    sec.setRDDHandleForVariable(output.getName(), out);
    sec.addLineageRDD(output.getName(), input1.getName());
}

Example 85 with MatrixBlock

use of org.apache.sysml.runtime.matrix.data.MatrixBlock in project incubator-systemml by apache.

the class BinarySPInstruction method processMatrixMatrixBinaryInstruction.

/**
 * Common binary matrix-matrix process instruction
 *
 * @param ec execution context
 */
protected void processMatrixMatrixBinaryInstruction(ExecutionContext ec) {
    SparkExecutionContext sec = (SparkExecutionContext) ec;
    // sanity check dimensions
    checkMatrixMatrixBinaryCharacteristics(sec);
    updateBinaryOutputMatrixCharacteristics(sec);
    // Get input RDDs
    JavaPairRDD<MatrixIndexes, MatrixBlock> in1 = sec.getBinaryBlockRDDHandleForVariable(input1.getName());
    JavaPairRDD<MatrixIndexes, MatrixBlock> in2 = sec.getBinaryBlockRDDHandleForVariable(input2.getName());
    MatrixCharacteristics mc1 = sec.getMatrixCharacteristics(input1.getName());
    MatrixCharacteristics mc2 = sec.getMatrixCharacteristics(input2.getName());
    MatrixCharacteristics mcOut = sec.getMatrixCharacteristics(output.getName());
    BinaryOperator bop = (BinaryOperator) _optr;
    // vector replication if required (mv or outer operations)
    boolean rowvector = (mc2.getRows() == 1 && mc1.getRows() > 1);
    long numRepLeft = getNumReplicas(mc1, mc2, true);
    long numRepRight = getNumReplicas(mc1, mc2, false);
    if (numRepLeft > 1)
        in1 = in1.flatMapToPair(new ReplicateVectorFunction(false, numRepLeft));
    if (numRepRight > 1)
        in2 = in2.flatMapToPair(new ReplicateVectorFunction(rowvector, numRepRight));
    int numPrefPart = SparkUtils.isHashPartitioned(in1) ? in1.getNumPartitions() : SparkUtils.isHashPartitioned(in2) ? in2.getNumPartitions() : Math.min(in1.getNumPartitions() + in2.getNumPartitions(), 2 * SparkUtils.getNumPreferredPartitions(mcOut));
    // execute binary operation
    JavaPairRDD<MatrixIndexes, MatrixBlock> out = in1.join(in2, numPrefPart).mapValues(new MatrixMatrixBinaryOpFunction(bop));
    // set output RDD
    sec.setRDDHandleForVariable(output.getName(), out);
    sec.addLineageRDD(output.getName(), input1.getName());
    sec.addLineageRDD(output.getName(), input2.getName());
}