Examples with CompressedMatrixBlock org.apache.sysml.runtime.compress.CompressedMatrixBlock used on opensource projects

Example 16 with CompressedMatrixBlock

use of org.apache.sysml.runtime.compress.CompressedMatrixBlock in project incubator-systemml by apache.

the class LargeMatrixVectorMultTest method runMatrixVectorMultTest.

/**
	 * 
	 * @param mb
	 */
private void runMatrixVectorMultTest(SparsityType sptype, ValueType vtype, boolean compress) {
    try {
        //prepare sparsity for input data
        double sparsity = -1;
        switch(sptype) {
            case DENSE:
                sparsity = sparsity1;
                break;
            case SPARSE:
                sparsity = sparsity2;
                break;
            case EMPTY:
                sparsity = sparsity3;
                break;
        }
        //generate input data
        double min = (vtype == ValueType.CONST) ? 10 : -10;
        double[][] input = TestUtils.generateTestMatrix(rows, cols, min, 10, sparsity, 7);
        if (vtype == ValueType.RAND_ROUND_OLE || vtype == ValueType.RAND_ROUND_DDC) {
            CompressedMatrixBlock.ALLOW_DDC_ENCODING = (vtype == ValueType.RAND_ROUND_DDC);
            input = TestUtils.round(input);
        }
        MatrixBlock mb = DataConverter.convertToMatrixBlock(input);
        MatrixBlock vector = DataConverter.convertToMatrixBlock(TestUtils.generateTestMatrix(cols, 1, 1, 1, 1.0, 3));
        //compress given matrix block
        CompressedMatrixBlock cmb = new CompressedMatrixBlock(mb);
        if (compress)
            cmb.compress();
        //matrix-vector uncompressed
        AggregateOperator aop = new AggregateOperator(0, Plus.getPlusFnObject());
        AggregateBinaryOperator abop = new AggregateBinaryOperator(Multiply.getMultiplyFnObject(), aop);
        MatrixBlock ret1 = (MatrixBlock) mb.aggregateBinaryOperations(mb, vector, new MatrixBlock(), abop);
        //matrix-vector compressed
        MatrixBlock ret2 = (MatrixBlock) cmb.aggregateBinaryOperations(cmb, vector, new MatrixBlock(), abop);
        //compare result with input
        double[][] d1 = DataConverter.convertToDoubleMatrix(ret1);
        double[][] d2 = DataConverter.convertToDoubleMatrix(ret2);
        TestUtils.compareMatrices(d1, d2, rows, 1, 0.0000001);
    } catch (Exception ex) {
        throw new RuntimeException(ex);
    } finally {
        CompressedMatrixBlock.ALLOW_DDC_ENCODING = true;
    }
}

Example 17 with CompressedMatrixBlock

use of org.apache.sysml.runtime.compress.CompressedMatrixBlock in project incubator-systemml by apache.

the class LargeParMatrixVectorMultTest method runMatrixVectorMultTest.

/**
	 * 
	 * @param mb
	 */
private void runMatrixVectorMultTest(SparsityType sptype, ValueType vtype, boolean compress) {
    try {
        //prepare sparsity for input data
        double sparsity = -1;
        switch(sptype) {
            case DENSE:
                sparsity = sparsity1;
                break;
            case SPARSE:
                sparsity = sparsity2;
                break;
            case EMPTY:
                sparsity = sparsity3;
                break;
        }
        //generate input data
        double min = (vtype == ValueType.CONST) ? 10 : -10;
        double[][] input = TestUtils.generateTestMatrix(rows, cols, min, 10, sparsity, 7);
        if (vtype == ValueType.RAND_ROUND_OLE || vtype == ValueType.RAND_ROUND_DDC) {
            CompressedMatrixBlock.ALLOW_DDC_ENCODING = (vtype == ValueType.RAND_ROUND_DDC);
            input = TestUtils.round(input);
        }
        MatrixBlock mb = DataConverter.convertToMatrixBlock(input);
        MatrixBlock vector = DataConverter.convertToMatrixBlock(TestUtils.generateTestMatrix(cols, 1, 1, 1, 1.0, 3));
        //compress given matrix block
        CompressedMatrixBlock cmb = new CompressedMatrixBlock(mb);
        if (compress)
            cmb.compress();
        //matrix-vector uncompressed
        AggregateOperator aop = new AggregateOperator(0, Plus.getPlusFnObject());
        AggregateBinaryOperator abop = new AggregateBinaryOperator(Multiply.getMultiplyFnObject(), aop, InfrastructureAnalyzer.getLocalParallelism());
        MatrixBlock ret1 = (MatrixBlock) mb.aggregateBinaryOperations(mb, vector, new MatrixBlock(), abop);
        //matrix-vector compressed
        MatrixBlock ret2 = (MatrixBlock) cmb.aggregateBinaryOperations(cmb, vector, new MatrixBlock(), abop);
        //compare result with input
        double[][] d1 = DataConverter.convertToDoubleMatrix(ret1);
        double[][] d2 = DataConverter.convertToDoubleMatrix(ret2);
        TestUtils.compareMatrices(d1, d2, rows, 1, 0.0000001);
    } catch (Exception ex) {
        throw new RuntimeException(ex);
    } finally {
        CompressedMatrixBlock.ALLOW_DDC_ENCODING = true;
    }
}

Example 18 with CompressedMatrixBlock

use of org.apache.sysml.runtime.compress.CompressedMatrixBlock in project incubator-systemml by apache.

the class LargeParUnaryAggregateTest method runUnaryAggregateTest.

/**
	 * 
	 * @param mb
	 */
private void runUnaryAggregateTest(SparsityType sptype, ValueType vtype, AggType aggtype, boolean compress) {
    try {
        //prepare sparsity for input data
        double sparsity = -1;
        switch(sptype) {
            case DENSE:
                sparsity = sparsity1;
                break;
            case SPARSE:
                sparsity = sparsity2;
                break;
            case EMPTY:
                sparsity = sparsity3;
                break;
        }
        //generate input data
        double min = (vtype == ValueType.CONST) ? 10 : -10;
        double[][] input = TestUtils.generateTestMatrix(rows, cols, min, 10, sparsity, 7);
        if (vtype == ValueType.RAND_ROUND_OLE || vtype == ValueType.RAND_ROUND_DDC) {
            CompressedMatrixBlock.ALLOW_DDC_ENCODING = (vtype == ValueType.RAND_ROUND_DDC);
            input = TestUtils.round(input);
        }
        MatrixBlock mb = DataConverter.convertToMatrixBlock(input);
        //uc group
        mb = mb.appendOperations(MatrixBlock.seqOperations(0.1, rows - 0.1, 1), new MatrixBlock());
        //prepare unary aggregate operator
        AggregateUnaryOperator auop = null;
        switch(aggtype) {
            case SUM:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uak+");
                break;
            case ROWSUMS:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uark+");
                break;
            case COLSUMS:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uack+");
                break;
            case SUMSQ:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uasqk+");
                break;
            case ROWSUMSSQ:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uarsqk+");
                break;
            case COLSUMSSQ:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uacsqk+");
                break;
            case MAX:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uamax");
                break;
            case ROWMAXS:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uarmax");
                break;
            case COLMAXS:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uacmax");
                break;
            case MIN:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uamin");
                break;
            case ROWMINS:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uarmin");
                break;
            case COLMINS:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uacmin");
                break;
        }
        auop.setNumThreads(InfrastructureAnalyzer.getLocalParallelism());
        //compress given matrix block
        CompressedMatrixBlock cmb = new CompressedMatrixBlock(mb);
        if (compress)
            cmb.compress();
        //matrix-vector uncompressed						
        MatrixBlock ret1 = (MatrixBlock) mb.aggregateUnaryOperations(auop, new MatrixBlock(), 1000, 1000, null, true);
        //matrix-vector compressed
        MatrixBlock ret2 = (MatrixBlock) cmb.aggregateUnaryOperations(auop, new MatrixBlock(), 1000, 1000, null, true);
        //compare result with input
        double[][] d1 = DataConverter.convertToDoubleMatrix(ret1);
        double[][] d2 = DataConverter.convertToDoubleMatrix(ret2);
        int dim1 = (aggtype == AggType.ROWSUMS || aggtype == AggType.ROWSUMSSQ || aggtype == AggType.ROWMINS || aggtype == AggType.ROWMINS) ? rows : 1;
        int dim2 = (aggtype == AggType.COLSUMS || aggtype == AggType.COLSUMSSQ || aggtype == AggType.COLMAXS || aggtype == AggType.COLMINS) ? cols : 1;
        TestUtils.compareMatrices(d1, d2, dim1, dim2, 0.000000001);
    } catch (Exception ex) {
        throw new RuntimeException(ex);
    } finally {
        CompressedMatrixBlock.ALLOW_DDC_ENCODING = true;
    }
}

Example 19 with CompressedMatrixBlock

use of org.apache.sysml.runtime.compress.CompressedMatrixBlock in project incubator-systemml by apache.

the class AggregateBinaryCPInstruction method processInstruction.

@Override
public void processInstruction(ExecutionContext ec) throws DMLRuntimeException {
    //get inputs
    MatrixBlock matBlock1 = ec.getMatrixInput(input1.getName());
    MatrixBlock matBlock2 = ec.getMatrixInput(input2.getName());
    //compute matrix multiplication
    AggregateBinaryOperator ab_op = (AggregateBinaryOperator) _optr;
    MatrixBlock main = (matBlock2 instanceof CompressedMatrixBlock) ? matBlock2 : matBlock1;
    MatrixBlock ret = (MatrixBlock) main.aggregateBinaryOperations(matBlock1, matBlock2, new MatrixBlock(), ab_op);
    //release inputs/outputs
    ec.releaseMatrixInput(input1.getName());
    ec.releaseMatrixInput(input2.getName());
    ec.setMatrixOutput(output.getName(), ret);
}

Example 20 with CompressedMatrixBlock

use of org.apache.sysml.runtime.compress.CompressedMatrixBlock in project incubator-systemml by apache.

the class CompressionCPInstruction method processInstruction.

@Override
public void processInstruction(ExecutionContext ec) throws DMLRuntimeException {
    //get matrix block input
    MatrixBlock in = ec.getMatrixInput(input1.getName());
    //compress the matrix block
    CompressedMatrixBlock cmb = new CompressedMatrixBlock(in);
    cmb.compress(OptimizerUtils.getConstrainedNumThreads(-1));
    //set output and release input
    ec.releaseMatrixInput(input1.getName());
    ec.setMatrixOutput(output.getName(), cmb);
}