Examples with BinaryOperator org.apache.sysml.runtime.matrix.operators.BinaryOperator used on opensource projects

Example 16 with BinaryOperator

use of org.apache.sysml.runtime.matrix.operators.BinaryOperator in project incubator-systemml by apache.

the class CompressedMatrixBlock method chainMatrixMultOperations.

@Override
public MatrixBlock chainMatrixMultOperations(MatrixBlock v, MatrixBlock w, MatrixBlock out, ChainType ctype, int k) {
    // call uncompressed matrix mult if necessary
    if (!isCompressed()) {
        return super.chainMatrixMultOperations(v, w, out, ctype, k);
    }
    // multi-threaded mmchain of single uncompressed colgroup
    if (isSingleUncompressedGroup()) {
        return ((ColGroupUncompressed) _colGroups.get(0)).getData().chainMatrixMultOperations(v, w, out, ctype, k);
    }
    Timing time = LOG.isDebugEnabled() ? new Timing(true) : null;
    // prepare result
    if (out != null)
        out.reset(clen, 1, false);
    else
        out = new MatrixBlock(clen, 1, false);
    // empty block handling
    if (isEmptyBlock(false))
        return out;
    // compute matrix mult
    MatrixBlock tmp = new MatrixBlock(rlen, 1, false);
    rightMultByVector(v, tmp, k);
    if (ctype == ChainType.XtwXv) {
        BinaryOperator bop = new BinaryOperator(Multiply.getMultiplyFnObject());
        LibMatrixBincell.bincellOpInPlace(tmp, w, bop);
    }
    leftMultByVectorTranspose(_colGroups, tmp, out, true, k);
    if (LOG.isDebugEnabled())
        LOG.debug("Compressed MMChain k=" + k + " in " + time.stop());
    return out;
}

Example 17 with BinaryOperator

use of org.apache.sysml.runtime.matrix.operators.BinaryOperator in project incubator-systemml by apache.

the class CompressedMatrixBlock method chainMatrixMultOperations.

@Override
public MatrixBlock chainMatrixMultOperations(MatrixBlock v, MatrixBlock w, MatrixBlock out, ChainType ctype) {
    // call uncompressed matrix mult if necessary
    if (!isCompressed()) {
        return super.chainMatrixMultOperations(v, w, out, ctype);
    }
    // single-threaded mmchain of single uncompressed colgroup
    if (isSingleUncompressedGroup()) {
        return ((ColGroupUncompressed) _colGroups.get(0)).getData().chainMatrixMultOperations(v, w, out, ctype);
    }
    // prepare result
    if (out != null)
        out.reset(clen, 1, false);
    else
        out = new MatrixBlock(clen, 1, false);
    // empty block handling
    if (isEmptyBlock(false))
        return out;
    // compute matrix mult
    MatrixBlock tmp = new MatrixBlock(rlen, 1, false);
    rightMultByVector(v, tmp);
    if (ctype == ChainType.XtwXv) {
        BinaryOperator bop = new BinaryOperator(Multiply.getMultiplyFnObject());
        LibMatrixBincell.bincellOpInPlace(tmp, w, bop);
    }
    leftMultByVectorTranspose(_colGroups, tmp, out, true, true);
    return out;
}

Example 18 with BinaryOperator

use of org.apache.sysml.runtime.matrix.operators.BinaryOperator in project incubator-systemml by apache.

the class BuiltinBinaryGPUInstruction method parseInstruction.

public static BuiltinBinaryGPUInstruction parseInstruction(String str) {
    CPOperand in1 = new CPOperand("", Expression.ValueType.UNKNOWN, Expression.DataType.UNKNOWN);
    CPOperand in2 = new CPOperand("", Expression.ValueType.UNKNOWN, Expression.DataType.UNKNOWN);
    CPOperand out = new CPOperand("", Expression.ValueType.UNKNOWN, Expression.DataType.UNKNOWN);
    String[] parts = InstructionUtils.getInstructionPartsWithValueType(str);
    InstructionUtils.checkNumFields(parts, 3);
    String opcode = parts[0];
    in1.split(parts[1]);
    in2.split(parts[2]);
    out.split(parts[3]);
    // check for valid data type of output
    if ((in1.getDataType() == Expression.DataType.MATRIX || in2.getDataType() == Expression.DataType.MATRIX) && out.getDataType() != Expression.DataType.MATRIX)
        throw new DMLRuntimeException("Element-wise matrix operations between variables " + in1.getName() + " and " + in2.getName() + " must produce a matrix, which " + out.getName() + " is not");
    // Determine appropriate Function Object based on opcode
    ValueFunction func = Builtin.getBuiltinFnObject(opcode);
    boolean isMatrixMatrix = in1.getDataType() == Expression.DataType.MATRIX && in2.getDataType() == Expression.DataType.MATRIX;
    boolean isMatrixScalar = (in1.getDataType() == Expression.DataType.MATRIX && in2.getDataType() == Expression.DataType.SCALAR) || (in1.getDataType() == Expression.DataType.SCALAR && in2.getDataType() == Expression.DataType.MATRIX);
    if (in1.getDataType() == Expression.DataType.SCALAR && in2.getDataType() == Expression.DataType.SCALAR)
        throw new DMLRuntimeException("GPU : Unsupported GPU builtin operations on 2 scalars");
    else if (isMatrixMatrix && opcode.equals("solve"))
        return new MatrixMatrixBuiltinGPUInstruction(new BinaryOperator(func), in1, in2, out, opcode, str, 2);
    else if (isMatrixScalar && (opcode.equals("min") || opcode.equals("max")))
        return new ScalarMatrixBuiltinGPUInstruction(new BinaryOperator(func), in1, in2, out, opcode, str, 2);
    else
        throw new DMLRuntimeException("GPU : Unsupported GPU builtin operations on a matrix and a scalar:" + opcode);
}

Example 19 with BinaryOperator

use of org.apache.sysml.runtime.matrix.operators.BinaryOperator in project incubator-systemml by apache.

the class MatrixMatrixArithmeticGPUInstruction method processInstruction.

@Override
public void processInstruction(ExecutionContext ec) {
    GPUStatistics.incrementNoOfExecutedGPUInst();
    MatrixObject in1 = getMatrixInputForGPUInstruction(ec, _input1.getName());
    MatrixObject in2 = getMatrixInputForGPUInstruction(ec, _input2.getName());
    // TODO: make hop level changes for this
    boolean isLeftTransposed = false;
    boolean isRightTransposed = false;
    long rlen1 = in1.getNumRows();
    long clen1 = in1.getNumColumns();
    long rlen2 = in2.getNumRows();
    long clen2 = in2.getNumColumns();
    // Assume ordinary binary op
    long rlen = rlen1;
    long clen = clen1;
    // Outer binary op ( [100,1] + [1,100] or [100,100] + [100,1]
    if (rlen1 != rlen2 || clen1 != clen2) {
        rlen = rlen1 > rlen2 ? rlen1 : rlen2;
        clen = clen1 > clen2 ? clen1 : clen2;
    }
    ec.setMetaData(_output.getName(), (int) rlen, (int) clen);
    BinaryOperator bop = (BinaryOperator) _optr;
    LibMatrixCUDA.matrixMatrixArithmetic(ec, ec.getGPUContext(0), getExtendedOpcode(), in1, in2, _output.getName(), isLeftTransposed, isRightTransposed, bop);
    ec.releaseMatrixInputForGPUInstruction(_input1.getName());
    ec.releaseMatrixInputForGPUInstruction(_input2.getName());
    ec.releaseMatrixOutputForGPUInstruction(_output.getName());
}

Example 20 with BinaryOperator

use of org.apache.sysml.runtime.matrix.operators.BinaryOperator in project incubator-systemml by apache.

the class MatrixMatrixRelationalBinaryGPUInstruction method processInstruction.

@Override
public void processInstruction(ExecutionContext ec) {
    GPUStatistics.incrementNoOfExecutedGPUInst();
    MatrixObject in1 = getMatrixInputForGPUInstruction(ec, _input1.getName());
    MatrixObject in2 = getMatrixInputForGPUInstruction(ec, _input2.getName());
    long rlen1 = in1.getNumRows();
    long clen1 = in1.getNumColumns();
    long rlen2 = in2.getNumRows();
    long clen2 = in2.getNumColumns();
    // Assume ordinary binary op
    long rlen = rlen1;
    long clen = clen1;
    // Outer binary op ( [100,1] + [1,100] or [100,100] + [100,1]
    if (rlen1 != rlen2 || clen1 != clen2) {
        rlen = rlen1 > rlen2 ? rlen1 : rlen2;
        clen = clen1 > clen2 ? clen1 : clen2;
    }
    ec.setMetaData(_output.getName(), (int) rlen, (int) clen);
    BinaryOperator bop = (BinaryOperator) _optr;
    LibMatrixCUDA.matrixMatrixRelational(ec, ec.getGPUContext(0), getExtendedOpcode(), in1, in2, _output.getName(), bop);
    ec.releaseMatrixInputForGPUInstruction(_input1.getName());
    ec.releaseMatrixInputForGPUInstruction(_input2.getName());
    ec.releaseMatrixOutputForGPUInstruction(_output.getName());
}