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<div class="title">Writing by Contiguous Hyperslab </div> </div>
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<div class="textblock"><p>Navigate back: <a class="el" href="index.html">Main</a> / <a class="el" href="_getting_started.html">Getting Started with HDF5</a> / <a class="el" href="_intro_par_h_d_f5.html">A Brief Introduction to Parallel HDF5</a> </p><hr />
<p>This example shows how to write a contiguous buffer in memory to a contiguous hyperslab in a file. In this case, each parallel process writes a contiguous hyperslab to the file.</p>
<p>In the C example (figure a), each hyperslab in memory consists of an equal number of consecutive rows. In the FORTRAN 90 example (figure b), each hyperslab in memory consists of an equal number of consecutive columns. This reflects the difference in the storage order for C and FORTRAN 90. </p><table class="doxtable">
<tr>
<th><b>Figure a</b> C Example </th><th><b>Figure b</b> Fortran Example </th></tr>
<tr>
<td><div class="image">
<img src="pcont_hy_figa.gif" alt=""/>
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<h1><a class="anchor" id="secIntroParContHyperslabC"></a>
Writing a Contiguous Hyperslab in C</h1>
<p>In this example, you have a dataset of 8 (rows) x 5 (columns) and each process writes an equal number of rows to the dataset. The dataset hyperslab is defined as follows: </p><div class="fragment"><div class="line">count [0] = dimsf [0] / number_processes</div>
<div class="line">count [1] = dimsf [1]</div>
</div><!-- fragment --><p> where, </p><div class="fragment"><div class="line">dimsf [0] is the number of rows in the dataset</div>
<div class="line">dimsf [1] is the number of columns in the dataset</div>
</div><!-- fragment --><p> The offset for the hyperslab is different for each process: </p><div class="fragment"><div class="line">offset [0] = k * count[0]</div>
<div class="line">offset [1] = 0</div>
</div><!-- fragment --><p> where, </p><div class="fragment"><div class="line"><span class="stringliteral">"k"</span> is the process <span class="keywordtype">id</span> number</div>
<div class="line">count [0] is the number of rows written in each hyperslab</div>
<div class="line">offset [1] = 0 indicates to start at the beginning of the row</div>
</div><!-- fragment --><p>The number of processes that you could use would be 1, 2, 4, or 8. The number of rows that would be written by each slab is as follows: </p><table class="doxtable">
<tr>
<th><b>Processes</b> </th><th><b>Size of count<a href="\# of rows">0</a> </b> </th></tr>
<tr>
<td>1</td><td>8 </td></tr>
<tr>
<td>2</td><td>4 </td></tr>
<tr>
<td>4</td><td>2 </td></tr>
<tr>
<td>8</td><td>1 </td></tr>
</table>
<p>If using 4 processes, then process 1 would look like: </p><table class="doxtable">
<tr>
<td><div class="image">
<img src="pcont_hy_figc.gif" alt=""/>
</div>
</td></tr>
</table>
<p>The code would look like the following: </p><div class="fragment"><div class="line">71 <span class="comment">/*</span></div>
<div class="line"><span class="comment">72 * Each process defines dataset in memory and writes it to the hyperslab</span></div>
<div class="line"><span class="comment">73 * in the file.</span></div>
<div class="line"><span class="comment">74 */</span></div>
<div class="line">75 count[0] = dimsf[0]/mpi_size;</div>
<div class="line">76 count[1] = dimsf[1];</div>
<div class="line">77 offset[0] = mpi_rank * count[0];</div>
<div class="line">78 offset[1] = 0;</div>
<div class="line">79 memspace = <a class="code" href="group___h5_s.html#ga8e35eea5738b4805856eac7d595254ae">H5Screate_simple</a>(RANK, count, NULL);</div>
<div class="line">80</div>
<div class="line">81 <span class="comment">/*</span></div>
<div class="line"><span class="comment">82 * Select hyperslab in the file.</span></div>
<div class="line"><span class="comment">83 */</span></div>
<div class="line">84 filespace = <a class="code" href="group___h5_d.html#gad42a46be153d895d8c28a11ebf5a0d0a">H5Dget_space</a>(dset_id);</div>
<div class="line">85 <a class="code" href="group___h5_s.html#ga6adfdf1b95dc108a65bf66e97d38536d">H5Sselect_hyperslab</a>(filespace, <a class="code" href="_h5_spublic_8h.html#a10093bab27cc5720efdab3186993da0fab90faf3dc59ecf6f28197ef471141550">H5S_SELECT_SET</a>, offset, NULL, count, NULL);</div>
<div class="ttc" id="a_h5_spublic_8h_html_a10093bab27cc5720efdab3186993da0fab90faf3dc59ecf6f28197ef471141550"><div class="ttname"><a href="_h5_spublic_8h.html#a10093bab27cc5720efdab3186993da0fab90faf3dc59ecf6f28197ef471141550">H5S_SELECT_SET</a></div><div class="ttdeci">@ H5S_SELECT_SET</div><div class="ttdef"><b>Definition:</b> H5Spublic.h:87</div></div>
<div class="ttc" id="agroup___h5_d_html_gad42a46be153d895d8c28a11ebf5a0d0a"><div class="ttname"><a href="group___h5_d.html#gad42a46be153d895d8c28a11ebf5a0d0a">H5Dget_space</a></div><div class="ttdeci">hid_t H5Dget_space(hid_t dset_id)</div><div class="ttdoc">Returns an identifier for a copy of the dataspace for a dataset.</div></div>
<div class="ttc" id="agroup___h5_s_html_ga6adfdf1b95dc108a65bf66e97d38536d"><div class="ttname"><a href="group___h5_s.html#ga6adfdf1b95dc108a65bf66e97d38536d">H5Sselect_hyperslab</a></div><div class="ttdeci">herr_t H5Sselect_hyperslab(hid_t space_id, H5S_seloper_t op, const hsize_t start[], const hsize_t stride[], const hsize_t count[], const hsize_t block[])</div><div class="ttdoc">Selects a hyperslab region to add to the current selected region.</div></div>
<div class="ttc" id="agroup___h5_s_html_ga8e35eea5738b4805856eac7d595254ae"><div class="ttname"><a href="group___h5_s.html#ga8e35eea5738b4805856eac7d595254ae">H5Screate_simple</a></div><div class="ttdeci">hid_t H5Screate_simple(int rank, const hsize_t dims[], const hsize_t maxdims[])</div><div class="ttdoc">Creates a new simple dataspace and opens it for access.</div></div>
</div><!-- fragment --><p>Below is the example program: </p><table class="doxtable">
<tr>
<td><a href="https://github.com/HDFGroup/hdf5-examples/blob/master/C/H5Parallel/ph5_hyperslab_by_row.c">hyperslab_by_row.c</a> </td></tr>
</table>
<p>If using this example with 4 processes, then, </p><ul>
<li>Process 0 writes "10"s to the file. </li>
<li>Process 1 writes "11"s. </li>
<li>Process 2 writes "12"s. </li>
<li>Process 3 writes "13"s.</li>
</ul>
<p>The following is the output from h5dump for the HDF5 file created by this example using 4 processes: </p><div class="fragment"><div class="line">HDF5 <span class="stringliteral">"SDS_row.h5"</span> {</div>
<div class="line">GROUP <span class="stringliteral">"/"</span> {</div>
<div class="line"> DATASET <span class="stringliteral">"IntArray"</span> {</div>
<div class="line"> DATATYPE <a class="code" href="group___p_d_t_s_t_d.html#ga37e8a6be7ee64587c2a282b965019bb8">H5T_STD_I32BE</a> </div>
<div class="line"> DATASPACE SIMPLE { ( 8, 5 ) / ( 8, 5 ) } </div>
<div class="line"> DATA {</div>
<div class="line"> 10, 10, 10, 10, 10,</div>
<div class="line"> 10, 10, 10, 10, 10,</div>
<div class="line"> 11, 11, 11, 11, 11,</div>
<div class="line"> 11, 11, 11, 11, 11,</div>
<div class="line"> 12, 12, 12, 12, 12,</div>
<div class="line"> 12, 12, 12, 12, 12,</div>
<div class="line"> 13, 13, 13, 13, 13,</div>
<div class="line"> 13, 13, 13, 13, 13</div>
<div class="line"> } </div>
<div class="line"> } </div>
<div class="line">} </div>
<div class="line">} </div>
<div class="ttc" id="agroup___p_d_t_s_t_d_html_ga37e8a6be7ee64587c2a282b965019bb8"><div class="ttname"><a href="group___p_d_t_s_t_d.html#ga37e8a6be7ee64587c2a282b965019bb8">H5T_STD_I32BE</a></div><div class="ttdeci">#define H5T_STD_I32BE</div><div class="ttdef"><b>Definition:</b> H5Tpublic.h:305</div></div>
</div><!-- fragment --><h1><a class="anchor" id="secIntroParContHyperslabFort"></a>
Writing a Contiguous Hyperslab in Fortran</h1>
<p>In this example you have a dataset of 5 (rows) x 8 (columns). Since a contiguous hyperslab in Fortran 90 consists of consecutive columns, each process will be writing an equal number of columns to the dataset.</p>
<p>You would define the size of the hyperslab to write to the dataset as follows: </p><div class="fragment"><div class="line">count(1) = dimsf(1)</div>
<div class="line">count(2) = dimsf(2) / number_of_processes</div>
</div><!-- fragment --><p>where, </p><div class="fragment"><div class="line">dimsf(1) is the number of rows in the dataset</div>
<div class="line">dimsf(2) is the number of columns</div>
</div><!-- fragment --><p>The offset for the hyperslab dimension would be different for each process: </p><div class="fragment"><div class="line">offset (1) = 0</div>
<div class="line">offset (2) = k * count (2)</div>
</div><!-- fragment --><p>where, </p><div class="fragment"><div class="line">offset (1) = 0 indicates to start at the beginning of the column</div>
<div class="line"><span class="stringliteral">"k"</span> is the process <span class="keywordtype">id</span> number</div>
<div class="line"><span class="stringliteral">"count(2) is the number of columns to be written by each hyperslab</span></div>
</div><!-- fragment --><p>The number of processes that could be used in this example are 1, 2, 4, or 8. The number of columns that could be written by each slab is as follows: </p><table class="doxtable">
<tr>
<th><b>Processes</b> </th><th><b>Size of count (2)(# of columns) </b> </th></tr>
<tr>
<td>1</td><td>8 </td></tr>
<tr>
<td>2</td><td>4 </td></tr>
<tr>
<td>4</td><td>2 </td></tr>
<tr>
<td>8</td><td>1 </td></tr>
</table>
<p>If using 4 processes, the offset and count parameters for Process 1 would look like: </p><table class="doxtable">
<tr>
<td><div class="image">
<img src="pcont_hy_figd.gif" alt=""/>
</div>
</td></tr>
</table>
<p>The code would look like the following: </p><div class="fragment"><div class="line">69 ! Each process defines dataset in memory and writes it to the hyperslab</div>
<div class="line">70 ! in the file.</div>
<div class="line">71 !</div>
<div class="line">72 count(1) = dimsf(1)</div>
<div class="line">73 count(2) = dimsf(2)/mpi_size</div>
<div class="line">74 offset(1) = 0</div>
<div class="line">75 offset(2) = mpi_rank * count(2)</div>
<div class="line">76 CALL <a class="code" href="group___f_h5_s.html#ga54083c84fd4be392ac770cf223cd6cf4">h5screate_simple_f</a>(rank, count, memspace, error)</div>
<div class="line">77 !</div>
<div class="line">78 ! Select hyperslab in the file.</div>
<div class="line">79 !</div>
<div class="line">80 CALL <a class="code" href="group___f_h5_d.html#gafb8a6067c9e7ef80ee48c0054e584ad7">h5dget_space_f</a>(dset_id, filespace, error)</div>
<div class="line">81 CALL <a class="code" href="group___f_h5_s.html#ga82aeb8a0da64f827e8a852eaab701ff9">h5sselect_hyperslab_f</a> (filespace, H5S_SELECT_SET_F, offset, count, error)</div>
<div class="ttc" id="agroup___f_h5_d_html_gafb8a6067c9e7ef80ee48c0054e584ad7"><div class="ttname"><a href="group___f_h5_d.html#gafb8a6067c9e7ef80ee48c0054e584ad7">h5d::h5dget_space_f</a></div><div class="ttdeci">subroutine h5dget_space_f(dataset_id, dataspace_id, hdferr)</div><div class="ttdoc">Returns an identifier for a copy of the dataspace for a dataset.</div><div class="ttdef"><b>Definition:</b> H5Dff.F90:1340</div></div>
<div class="ttc" id="agroup___f_h5_s_html_ga54083c84fd4be392ac770cf223cd6cf4"><div class="ttname"><a href="group___f_h5_s.html#ga54083c84fd4be392ac770cf223cd6cf4">h5s::h5screate_simple_f</a></div><div class="ttdeci">subroutine h5screate_simple_f(rank, dims, space_id, hdferr, maxdims)</div><div class="ttdoc">Creates a new simple data space and opens it for access.</div><div class="ttdef"><b>Definition:</b> H5Sff.F90:59</div></div>
<div class="ttc" id="agroup___f_h5_s_html_ga82aeb8a0da64f827e8a852eaab701ff9"><div class="ttname"><a href="group___f_h5_s.html#ga82aeb8a0da64f827e8a852eaab701ff9">h5s::h5sselect_hyperslab_f</a></div><div class="ttdeci">subroutine h5sselect_hyperslab_f(space_id, OPERATOR, start, count, hdferr, stride, BLOCK)</div><div class="ttdoc">Selects a hyperslab region to add to the current selected region.</div><div class="ttdef"><b>Definition:</b> H5Sff.F90:906</div></div>
</div><!-- fragment --><p>Below is the F90 example program which illustrates how to write contiguous hyperslabs by column in Parallel HDF5: </p><table class="doxtable">
<tr>
<td><a href="https://github.com/HDFGroup/hdf5-examples/blob/master/Fortran/H5Parallel/ph5_f90_hyperslab_by_col.F90">hyperslab_by_col.F90</a> </td></tr>
</table>
<p>If you run this program with 4 processes and look at the output with h5dump you will notice that the output is much like the output shown above for the C example. This is because h5dump is written in C. The data would be displayed in columns if it was printed using Fortran 90 code.</p>
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