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

Example 1 with SparseBlockCSR

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

the class GPUObject method copyFromDeviceToHost.

protected void copyFromDeviceToHost() throws DMLRuntimeException {
    LOG.trace("GPU : copyFromDeviceToHost, on " + this + ", GPUContext=" + getGPUContext());
    if (getJcudaDenseMatrixPtr() != null && getJcudaSparseMatrixPtr() != null) {
        throw new DMLRuntimeException("Invalid state : JCuda dense/sparse pointer are both allocated");
    }
    if (getJcudaDenseMatrixPtr() != null) {
        long start = 0;
        if (DMLScript.STATISTICS)
            start = System.nanoTime();
        MatrixBlock tmp = new MatrixBlock(toIntExact(mat.getNumRows()), toIntExact(mat.getNumColumns()), false);
        tmp.allocateDenseBlock();
        double[] data = tmp.getDenseBlock();
        cudaMemcpy(Pointer.to(data), getJcudaDenseMatrixPtr(), getDoubleSizeOf(data.length), cudaMemcpyDeviceToHost);
        tmp.recomputeNonZeros();
        mat.acquireModify(tmp);
        mat.release();
        if (DMLScript.STATISTICS)
            GPUStatistics.cudaFromDevTime.addAndGet(System.nanoTime() - start);
        if (DMLScript.STATISTICS)
            GPUStatistics.cudaFromDevCount.addAndGet(1);
    } else if (getJcudaSparseMatrixPtr() != null) {
        if (!LibMatrixCUDA.isInSparseFormat(getGPUContext(), mat))
            throw new DMLRuntimeException("Block not in sparse format on host yet the device sparse matrix pointer is not null");
        if (this.isSparseAndEmpty()) {
            // Empty Block
            MatrixBlock tmp = new MatrixBlock();
            mat.acquireModify(tmp);
            mat.release();
        } else {
            long start = 0;
            if (DMLScript.STATISTICS)
                start = System.nanoTime();
            int rows = toIntExact(mat.getNumRows());
            int cols = toIntExact(mat.getNumColumns());
            int nnz = toIntExact(getJcudaSparseMatrixPtr().nnz);
            int[] rowPtr = new int[rows + 1];
            int[] colInd = new int[nnz];
            double[] values = new double[nnz];
            CSRPointer.copyToHost(getJcudaSparseMatrixPtr(), rows, nnz, rowPtr, colInd, values);
            SparseBlockCSR sparseBlock = new SparseBlockCSR(rowPtr, colInd, values, nnz);
            MatrixBlock tmp = new MatrixBlock(rows, cols, nnz, sparseBlock);
            mat.acquireModify(tmp);
            mat.release();
            if (DMLScript.STATISTICS)
                GPUStatistics.cudaFromDevTime.addAndGet(System.nanoTime() - start);
            if (DMLScript.STATISTICS)
                GPUStatistics.cudaFromDevCount.addAndGet(1);
        }
    } else {
        throw new DMLRuntimeException("Cannot copy from device to host as JCuda dense/sparse pointer is not allocated");
    }
    dirty = false;
}

Example 2 with SparseBlockCSR

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

the class SparseBlockDelete method runSparseBlockDeleteTest.

/**
	 * 
	 * @param btype
	 * @param sparsity
	 */
private void runSparseBlockDeleteTest(SparseBlock.Type btype, double sparsity) {
    try {
        //data generation
        double[][] A = getRandomMatrix(rows, cols, -10, 10, sparsity, 456);
        //init sparse block
        SparseBlock sblock = null;
        MatrixBlock mbtmp = DataConverter.convertToMatrixBlock(A);
        SparseBlock srtmp = mbtmp.getSparseBlock();
        switch(btype) {
            case MCSR:
                sblock = new SparseBlockMCSR(srtmp);
                break;
            case CSR:
                sblock = new SparseBlockCSR(srtmp);
                break;
            case COO:
                sblock = new SparseBlockCOO(srtmp);
                break;
        }
        //delete range per row via set
        for (int i = 0; i < rows; i++) for (int j = cl; j < cu; j++) {
            A[i][j] = 0;
            sblock.set(i, j, 0);
        }
        //check for correct number of non-zeros
        int[] rnnz = new int[rows];
        int nnz = 0;
        for (int i = 0; i < rows; i++) {
            for (int j = 0; j < cols; j++) rnnz[i] += (A[i][j] != 0) ? 1 : 0;
            nnz += rnnz[i];
        }
        if (nnz != sblock.size())
            Assert.fail("Wrong number of non-zeros: " + sblock.size() + ", expected: " + nnz);
        //check correct isEmpty return
        for (int i = 0; i < rows; i++) if (sblock.isEmpty(i) != (rnnz[i] == 0))
            Assert.fail("Wrong isEmpty(row) result for row nnz: " + rnnz[i]);
        //check correct values	
        Iterator<IJV> iter = sblock.getIterator();
        int count = 0;
        while (iter.hasNext()) {
            IJV cell = iter.next();
            if (cell.getV() != A[cell.getI()][cell.getJ()])
                Assert.fail("Wrong value returned by iterator: " + cell.getV() + ", expected: " + A[cell.getI()][cell.getJ()]);
            count++;
        }
        if (count != nnz)
            Assert.fail("Wrong number of values returned by iterator: " + count + ", expected: " + nnz);
    } catch (Exception ex) {
        ex.printStackTrace();
        throw new RuntimeException(ex);
    }
}

Example 3 with SparseBlockCSR

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

the class SparseBlockGetFirstIndex method runSparseBlockGetFirstIndexTest.

/**
	 * 
	 * @param sparseM1
	 * @param sparseM2
	 * @param instType
	 */
private void runSparseBlockGetFirstIndexTest(SparseBlock.Type btype, double sparsity, IndexType itype) {
    try {
        //data generation
        double[][] A = getRandomMatrix(rows, cols, -10, 10, sparsity, 3456);
        //init sparse block
        SparseBlock sblock = null;
        MatrixBlock mbtmp = DataConverter.convertToMatrixBlock(A);
        SparseBlock srtmp = mbtmp.getSparseBlock();
        switch(btype) {
            case MCSR:
                sblock = new SparseBlockMCSR(srtmp);
                break;
            case CSR:
                sblock = new SparseBlockCSR(srtmp);
                break;
            case COO:
                sblock = new SparseBlockCOO(srtmp);
                break;
        }
        //check for correct number of non-zeros
        int[] rnnz = new int[rows];
        int nnz = 0;
        for (int i = 0; i < rows; i++) {
            for (int j = 0; j < cols; j++) rnnz[i] += (A[i][j] != 0) ? 1 : 0;
            nnz += rnnz[i];
        }
        if (nnz != sblock.size())
            Assert.fail("Wrong number of non-zeros: " + sblock.size() + ", expected: " + nnz);
        //check correct isEmpty return
        for (int i = 0; i < rows; i++) if (sblock.isEmpty(i) != (rnnz[i] == 0))
            Assert.fail("Wrong isEmpty(row) result for row nnz: " + rnnz[i]);
        //check correct index values	
        for (int i = 0; i < rows; i++) {
            int ix = getFirstIx(A, i, i, itype);
            int sixpos = -1;
            switch(itype) {
                case GT:
                    sixpos = sblock.posFIndexGT(i, i);
                    break;
                case GTE:
                    sixpos = sblock.posFIndexGTE(i, i);
                    break;
                case LTE:
                    sixpos = sblock.posFIndexLTE(i, i);
                    break;
            }
            int six = (sixpos >= 0) ? sblock.indexes(i)[sixpos] : -1;
            if (six != ix) {
                Assert.fail("Wrong index returned by index probe (" + itype.toString() + "," + i + "): " + six + ", expected: " + ix);
            }
        }
    } catch (Exception ex) {
        ex.printStackTrace();
        throw new RuntimeException(ex);
    }
}

Example 4 with SparseBlockCSR

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

the class SparseBlockGetSet method runSparseBlockGetSetTest.

/**
	 * 
	 * @param sparseM1
	 * @param sparseM2
	 * @param instType
	 */
private void runSparseBlockGetSetTest(SparseBlock.Type btype, double sparsity, InitType itype) {
    try {
        //data generation
        double[][] A = getRandomMatrix(rows, cols, -10, 10, sparsity, 7654321);
        //init sparse block
        SparseBlock sblock = null;
        if (itype == InitType.BULK) {
            MatrixBlock mbtmp = DataConverter.convertToMatrixBlock(A);
            SparseBlock srtmp = mbtmp.getSparseBlock();
            switch(btype) {
                case MCSR:
                    sblock = new SparseBlockMCSR(srtmp);
                    break;
                case CSR:
                    sblock = new SparseBlockCSR(srtmp);
                    break;
                case COO:
                    sblock = new SparseBlockCOO(srtmp);
                    break;
            }
        } else if (itype == InitType.SEQ_SET || itype == InitType.RAND_SET) {
            switch(btype) {
                case MCSR:
                    sblock = new SparseBlockMCSR(rows, cols);
                    break;
                case CSR:
                    sblock = new SparseBlockCSR(rows, cols);
                    break;
                case COO:
                    sblock = new SparseBlockCOO(rows, cols);
                    break;
            }
            if (itype == InitType.SEQ_SET) {
                for (int i = 0; i < rows; i++) for (int j = 0; j < cols; j++) sblock.append(i, j, A[i][j]);
            } else if (itype == InitType.RAND_SET) {
                LongLongDoubleHashMap map = new LongLongDoubleHashMap();
                for (int i = 0; i < rows; i++) for (int j = 0; j < cols; j++) map.addValue(i, j, A[i][j]);
                for (//random hash order
                LLDoubleEntry e : //random hash order
                map.extractValues()) sblock.set((int) e.key1, (int) e.key2, e.value);
            }
        }
        //check basic meta data
        if (sblock.numRows() != rows)
            Assert.fail("Wrong number of rows: " + sblock.numRows() + ", expected: " + rows);
        //check for correct number of non-zeros
        int[] rnnz = new int[rows];
        int nnz = 0;
        for (int i = 0; i < rows; i++) {
            for (int j = 0; j < cols; j++) rnnz[i] += (A[i][j] != 0) ? 1 : 0;
            nnz += rnnz[i];
        }
        if (nnz != sblock.size())
            Assert.fail("Wrong number of non-zeros: " + sblock.size() + ", expected: " + nnz);
        //check correct isEmpty return
        for (int i = 0; i < rows; i++) if (sblock.isEmpty(i) != (rnnz[i] == 0))
            Assert.fail("Wrong isEmpty(row) result for row nnz: " + rnnz[i]);
        //check correct values			
        for (int i = 0; i < rows; i++) if (!sblock.isEmpty(i))
            for (int j = 0; j < cols; j++) {
                double tmp = sblock.get(i, j);
                if (tmp != A[i][j])
                    Assert.fail("Wrong get value for cell (" + i + "," + j + "): " + tmp + ", expected: " + A[i][j]);
            }
    } catch (Exception ex) {
        ex.printStackTrace();
        throw new RuntimeException(ex);
    }
}

Example 5 with SparseBlockCSR

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

the class SparseBlockIndexRange method runSparseBlockIndexRangeTest.

/**
	 * 
	 * @param btype
	 * @param sparsity
	 */
private void runSparseBlockIndexRangeTest(SparseBlock.Type btype, double sparsity, UpdateType utype) {
    try {
        //data generation
        double[][] A = getRandomMatrix(rows, cols, -10, 10, sparsity, 456);
        //init sparse block
        SparseBlock sblock = null;
        MatrixBlock mbtmp = DataConverter.convertToMatrixBlock(A);
        SparseBlock srtmp = mbtmp.getSparseBlock();
        switch(btype) {
            case MCSR:
                sblock = new SparseBlockMCSR(srtmp);
                break;
            case CSR:
                sblock = new SparseBlockCSR(srtmp);
                break;
            case COO:
                sblock = new SparseBlockCOO(srtmp);
                break;
        }
        //delete range per row via set
        if (utype == UpdateType.DELETE) {
            for (int i = 0; i < rows; i++) {
                sblock.deleteIndexRange(i, cl, cu);
                Arrays.fill(A[i], cl, cu, 0);
            }
        } else if (utype == UpdateType.INSERT) {
            double[] vals = new double[cu - cl];
            for (int j = cl; j < cu; j++) vals[j - cl] = j;
            for (int i = 0; i < rows; i++) {
                sblock.setIndexRange(i, cl, cu, vals, 0, cu - cl);
                System.arraycopy(vals, 0, A[i], cl, cu - cl);
            }
        }
        //check for correct number of non-zeros
        int[] rnnz = new int[rows];
        int nnz = 0;
        for (int i = 0; i < rows; i++) {
            for (int j = 0; j < cols; j++) rnnz[i] += (A[i][j] != 0) ? 1 : 0;
            nnz += rnnz[i];
        }
        if (nnz != sblock.size())
            Assert.fail("Wrong number of non-zeros: " + sblock.size() + ", expected: " + nnz);
        //check correct isEmpty return
        for (int i = 0; i < rows; i++) if (sblock.isEmpty(i) != (rnnz[i] == 0))
            Assert.fail("Wrong isEmpty(row) result for row nnz: " + rnnz[i]);
        //check correct values	
        Iterator<IJV> iter = sblock.getIterator();
        int count = 0;
        while (iter.hasNext()) {
            IJV cell = iter.next();
            if (cell.getV() != A[cell.getI()][cell.getJ()])
                Assert.fail("Wrong value returned by iterator: " + cell.getV() + ", expected: " + A[cell.getI()][cell.getJ()]);
            count++;
        }
        if (count != nnz)
            Assert.fail("Wrong number of values returned by iterator: " + count + ", expected: " + nnz);
    } catch (Exception ex) {
        ex.printStackTrace();
        throw new RuntimeException(ex);
    }
}