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

Example 71 with CompressedMatrixBlock

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

the class LargeParUnaryAggregateTest method runUnaryAggregateTest.

private static 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.append(MatrixBlock.seqOperations(0.1, rows - 0.1, 1), new MatrixBlock());
        // prepare unary aggregate operator
        AggregateUnaryOperator auop = null;
        int k = InfrastructureAnalyzer.getLocalParallelism();
        switch(aggtype) {
            case SUM:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uak+", k);
                break;
            case ROWSUMS:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uark+", k);
                break;
            case COLSUMS:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uack+", k);
                break;
            case SUMSQ:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uasqk+", k);
                break;
            case ROWSUMSSQ:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uarsqk+", k);
                break;
            case COLSUMSSQ:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uacsqk+", k);
                break;
            case MAX:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uamax", k);
                break;
            case ROWMAXS:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uarmax", k);
                break;
            case COLMAXS:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uacmax", k);
                break;
            case MIN:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uamin", k);
                break;
            case ROWMINS:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uarmin", k);
                break;
            case COLMINS:
                auop = InstructionUtils.parseBasicAggregateUnaryOperator("uacmin", k);
                break;
        }
        // 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 : 1;
        TestUtils.compareMatrices(d1, d2, dim1, dim2, 0.000000001);
    } catch (Exception ex) {
        throw new RuntimeException(ex);
    } finally {
        CompressedMatrixBlock.ALLOW_DDC_ENCODING = true;
    }
}

Example 72 with CompressedMatrixBlock

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

the class BasicMatrixAppendTest method runMatrixAppendTest.

private static void runMatrixAppendTest(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, cols1, 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(rows, cols2, 1, 1, 1.0, 3));
        // compress given matrix block
        CompressedMatrixBlock cmb = new CompressedMatrixBlock(mb);
        if (compress)
            cmb.compress();
        // matrix-vector uncompressed
        MatrixBlock ret1 = (MatrixBlock) mb.append(vector, new MatrixBlock());
        // matrix-vector compressed
        MatrixBlock ret2 = cmb.append(vector, new MatrixBlock());
        if (compress)
            ret2 = ((CompressedMatrixBlock) ret2).decompress();
        // compare result with input
        double[][] d1 = DataConverter.convertToDoubleMatrix(ret1);
        double[][] d2 = DataConverter.convertToDoubleMatrix(ret2);
        TestUtils.compareMatrices(d1, d2, rows, cols1 + cols2, 0);
    } catch (Exception ex) {
        throw new RuntimeException(ex);
    } finally {
        CompressedMatrixBlock.ALLOW_DDC_ENCODING = true;
    }
}

Example 73 with CompressedMatrixBlock

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

the class BasicMatrixMultChainTest method runMatrixMultChainTest.

private static void runMatrixMultChainTest(SparsityType sptype, ValueType vtype, ChainType ctype, 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 vector1 = DataConverter.convertToMatrixBlock(TestUtils.generateTestMatrix(cols, 1, 0, 1, 1.0, 3));
        MatrixBlock vector2 = (ctype == ChainType.XtwXv) ? DataConverter.convertToMatrixBlock(TestUtils.generateTestMatrix(rows, 1, 0, 1, 1.0, 3)) : null;
        // compress given matrix block
        CompressedMatrixBlock cmb = new CompressedMatrixBlock(mb);
        if (compress)
            cmb.compress();
        // matrix-vector uncompressed
        MatrixBlock ret1 = (MatrixBlock) mb.chainMatrixMultOperations(vector1, vector2, new MatrixBlock(), ctype);
        // matrix-vector compressed
        MatrixBlock ret2 = (MatrixBlock) cmb.chainMatrixMultOperations(vector1, vector2, new MatrixBlock(), ctype);
        // compare result with input
        double[][] d1 = DataConverter.convertToDoubleMatrix(ret1);
        double[][] d2 = DataConverter.convertToDoubleMatrix(ret2);
        TestUtils.compareMatrices(d1, d2, cols, 1, 0.0000001);
    } catch (Exception ex) {
        throw new RuntimeException(ex);
    } finally {
        CompressedMatrixBlock.ALLOW_DDC_ENCODING = true;
    }
}

Example 74 with CompressedMatrixBlock

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

the class BasicMatrixTransposeSelfMultTest method runTransposeSelfMatrixMultTest.

private static void runTransposeSelfMatrixMultTest(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);
        // compress given matrix block
        CompressedMatrixBlock cmb = new CompressedMatrixBlock(mb);
        if (compress)
            cmb.compress();
        // matrix-vector uncompressed
        MatrixBlock ret1 = mb.transposeSelfMatrixMultOperations(new MatrixBlock(), MMTSJType.LEFT);
        // matrix-vector compressed
        MatrixBlock ret2 = cmb.transposeSelfMatrixMultOperations(new MatrixBlock(), MMTSJType.LEFT);
        // compare result with input
        double[][] d1 = DataConverter.convertToDoubleMatrix(ret1);
        double[][] d2 = DataConverter.convertToDoubleMatrix(ret2);
        TestUtils.compareMatrices(d1, d2, cols, cols, 0.0000001);
    } catch (Exception ex) {
        throw new RuntimeException(ex);
    } finally {
        CompressedMatrixBlock.ALLOW_DDC_ENCODING = true;
    }
}

Example 75 with CompressedMatrixBlock

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

the class BasicMatrixVectorMultTest method runMatrixVectorMultTest.

private static 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 = mb.aggregateBinaryOperations(mb, vector, new MatrixBlock(), abop);
        // matrix-vector compressed
        MatrixBlock ret2 = 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;
    }
}