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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"><html xmlns="http://www.w3.org/1999/xhtml"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8" /><title>Design</title><meta name="generator" content="DocBook XSL-NS Stylesheets V1.78.1" /><meta name="keywords" content="C++, library, parallel" /><meta name="keywords" content="ISO C++, library" /><meta name="keywords" content="ISO C++, runtime, library" /><link rel="home" href="../index.html" title="The GNU C++ Library" /><link rel="up" href="parallel_mode.html" title="Chapter 18. Parallel Mode" /><link rel="prev" href="parallel_mode_using.html" title="Using" /><link rel="next" href="parallel_mode_test.html" title="Testing" /></head><body><div class="navheader"><table width="100%" summary="Navigation header"><tr><th colspan="3" align="center">Design</th></tr><tr><td width="20%" align="left"><a accesskey="p" href="parallel_mode_using.html">Prev</a> </td><th width="60%" align="center">Chapter 18. Parallel Mode</th><td width="20%" align="right"> <a accesskey="n" href="parallel_mode_test.html">Next</a></td></tr></table><hr /></div><div class="section"><div class="titlepage"><div><div><h2 class="title" style="clear: both"><a id="manual.ext.parallel_mode.design"></a>Design</h2></div></div></div><p>
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</p><div class="section"><div class="titlepage"><div><div><h3 class="title"><a id="parallel_mode.design.intro"></a>Interface Basics</h3></div></div></div><p>
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All parallel algorithms are intended to have signatures that are
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equivalent to the ISO C++ algorithms replaced. For instance, the
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<code class="function">std::adjacent_find</code> function is declared as:
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</p><pre class="programlisting">
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namespace std
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{
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template<typename _FIter>
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_FIter
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adjacent_find(_FIter, _FIter);
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}
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</pre><p>
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Which means that there should be something equivalent for the parallel
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version. Indeed, this is the case:
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</p><pre class="programlisting">
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namespace std
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{
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namespace __parallel
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{
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template<typename _FIter>
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_FIter
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adjacent_find(_FIter, _FIter);
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...
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}
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}
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</pre><p>But.... why the ellipses?
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</p><p> The ellipses in the example above represent additional overloads
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required for the parallel version of the function. These additional
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overloads are used to dispatch calls from the ISO C++ function
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signature to the appropriate parallel function (or sequential
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function, if no parallel functions are deemed worthy), based on either
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compile-time or run-time conditions.
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</p><p> The available signature options are specific for the different
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algorithms/algorithm classes.</p><p> The general view of overloads for the parallel algorithms look like this:
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</p><div class="itemizedlist"><ul class="itemizedlist" style="list-style-type: disc; "><li class="listitem"><p>ISO C++ signature</p></li><li class="listitem"><p>ISO C++ signature + sequential_tag argument</p></li><li class="listitem"><p>ISO C++ signature + algorithm-specific tag type
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(several signatures)</p></li></ul></div><p> Please note that the implementation may use additional functions
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(designated with the <code class="code">_switch</code> suffix) to dispatch from the
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ISO C++ signature to the correct parallel version. Also, some of the
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algorithms do not have support for run-time conditions, so the last
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overload is therefore missing.
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</p></div><div class="section"><div class="titlepage"><div><div><h3 class="title"><a id="parallel_mode.design.tuning"></a>Configuration and Tuning</h3></div></div></div><div class="section"><div class="titlepage"><div><div><h4 class="title"><a id="parallel_mode.design.tuning.omp"></a>Setting up the OpenMP Environment</h4></div></div></div><p>
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Several aspects of the overall runtime environment can be manipulated
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by standard OpenMP function calls.
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</p><p>
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To specify the number of threads to be used for the algorithms globally,
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use the function <code class="function">omp_set_num_threads</code>. An example:
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</p><pre class="programlisting">
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#include <stdlib.h>
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#include <omp.h>
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int main()
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{
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// Explicitly set number of threads.
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const int threads_wanted = 20;
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omp_set_dynamic(false);
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omp_set_num_threads(threads_wanted);
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// Call parallel mode algorithms.
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return 0;
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}
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</pre><p>
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Some algorithms allow the number of threads being set for a particular call,
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by augmenting the algorithm variant.
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See the next section for further information.
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</p><p>
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Other parts of the runtime environment able to be manipulated include
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nested parallelism (<code class="function">omp_set_nested</code>), schedule kind
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(<code class="function">omp_set_schedule</code>), and others. See the OpenMP
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documentation for more information.
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</p></div><div class="section"><div class="titlepage"><div><div><h4 class="title"><a id="parallel_mode.design.tuning.compile"></a>Compile Time Switches</h4></div></div></div><p>
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To force an algorithm to execute sequentially, even though parallelism
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is switched on in general via the macro <code class="constant">_GLIBCXX_PARALLEL</code>,
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add <code class="classname">__gnu_parallel::sequential_tag()</code> to the end
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of the algorithm's argument list.
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</p><p>
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Like so:
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</p><pre class="programlisting">
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std::sort(v.begin(), v.end(), __gnu_parallel::sequential_tag());
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</pre><p>
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Some parallel algorithm variants can be excluded from compilation by
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preprocessor defines. See the doxygen documentation on
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<code class="code">compiletime_settings.h</code> and <code class="code">features.h</code> for details.
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</p><p>
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For some algorithms, the desired variant can be chosen at compile-time by
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appending a tag object. The available options are specific to the particular
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algorithm (class).
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</p><p>
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For the "embarrassingly parallel" algorithms, there is only one "tag object
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type", the enum _Parallelism.
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It takes one of the following values,
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<code class="code">__gnu_parallel::parallel_tag</code>,
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<code class="code">__gnu_parallel::balanced_tag</code>,
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<code class="code">__gnu_parallel::unbalanced_tag</code>,
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<code class="code">__gnu_parallel::omp_loop_tag</code>,
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<code class="code">__gnu_parallel::omp_loop_static_tag</code>.
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This means that the actual parallelization strategy is chosen at run-time.
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(Choosing the variants at compile-time will come soon.)
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</p><p>
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For the following algorithms in general, we have
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<code class="code">__gnu_parallel::parallel_tag</code> and
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<code class="code">__gnu_parallel::default_parallel_tag</code>, in addition to
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<code class="code">__gnu_parallel::sequential_tag</code>.
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<code class="code">__gnu_parallel::default_parallel_tag</code> chooses the default
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algorithm at compiletime, as does omitting the tag.
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<code class="code">__gnu_parallel::parallel_tag</code> postpones the decision to runtime
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(see next section).
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For all tags, the number of threads desired for this call can optionally be
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passed to the respective tag's constructor.
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</p><p>
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The <code class="code">multiway_merge</code> algorithm comes with the additional choices,
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<code class="code">__gnu_parallel::exact_tag</code> and
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<code class="code">__gnu_parallel::sampling_tag</code>.
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Exact and sampling are the two available splitting strategies.
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</p><p>
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For the <code class="code">sort</code> and <code class="code">stable_sort</code> algorithms, there are
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several additional choices, namely
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<code class="code">__gnu_parallel::multiway_mergesort_tag</code>,
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<code class="code">__gnu_parallel::multiway_mergesort_exact_tag</code>,
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<code class="code">__gnu_parallel::multiway_mergesort_sampling_tag</code>,
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<code class="code">__gnu_parallel::quicksort_tag</code>, and
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<code class="code">__gnu_parallel::balanced_quicksort_tag</code>.
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Multiway mergesort comes with the two splitting strategies for multi-way
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merging. The quicksort options cannot be used for <code class="code">stable_sort</code>.
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</p></div><div class="section"><div class="titlepage"><div><div><h4 class="title"><a id="parallel_mode.design.tuning.settings"></a>Run Time Settings and Defaults</h4></div></div></div><p>
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The default parallelization strategy, the choice of specific algorithm
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strategy, the minimum threshold limits for individual parallel
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algorithms, and aspects of the underlying hardware can be specified as
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desired via manipulation
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of <code class="classname">__gnu_parallel::_Settings</code> member data.
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</p><p>
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First off, the choice of parallelization strategy: serial, parallel,
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or heuristically deduced. This corresponds
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to <code class="code">__gnu_parallel::_Settings::algorithm_strategy</code> and is a
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value of enum <span class="type">__gnu_parallel::_AlgorithmStrategy</span>
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type. Choices
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include: <span class="type">heuristic</span>, <span class="type">force_sequential</span>,
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and <span class="type">force_parallel</span>. The default is <span class="type">heuristic</span>.
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</p><p>
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Next, the sub-choices for algorithm variant, if not fixed at compile-time.
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Specific algorithms like <code class="function">find</code> or <code class="function">sort</code>
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can be implemented in multiple ways: when this is the case,
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a <code class="classname">__gnu_parallel::_Settings</code> member exists to
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pick the default strategy. For
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example, <code class="code">__gnu_parallel::_Settings::sort_algorithm</code> can
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have any values of
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enum <span class="type">__gnu_parallel::_SortAlgorithm</span>: <span class="type">MWMS</span>, <span class="type">QS</span>,
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or <span class="type">QS_BALANCED</span>.
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</p><p>
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Likewise for setting the minimal threshold for algorithm
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parallelization. Parallelism always incurs some overhead. Thus, it is
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not helpful to parallelize operations on very small sets of
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data. Because of this, measures are taken to avoid parallelizing below
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a certain, pre-determined threshold. For each algorithm, a minimum
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problem size is encoded as a variable in the
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active <code class="classname">__gnu_parallel::_Settings</code> object. This
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threshold variable follows the following naming scheme:
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<code class="code">__gnu_parallel::_Settings::[algorithm]_minimal_n</code>. So,
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for <code class="function">fill</code>, the threshold variable
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is <code class="code">__gnu_parallel::_Settings::fill_minimal_n</code>,
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</p><p>
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Finally, hardware details like L1/L2 cache size can be hardwired
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via <code class="code">__gnu_parallel::_Settings::L1_cache_size</code> and friends.
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</p><p>
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</p><p>
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All these configuration variables can be changed by the user, if
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desired.
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There exists one global instance of the class <code class="classname">_Settings</code>,
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i. e. it is a singleton. It can be read and written by calling
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<code class="code">__gnu_parallel::_Settings::get</code> and
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<code class="code">__gnu_parallel::_Settings::set</code>, respectively.
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Please note that the first call return a const object, so direct manipulation
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is forbidden.
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See <a class="link" href="http://gcc.gnu.org/onlinedocs/libstdc++/latest-doxygen/a01005.html" target="_top">
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<code class="filename">settings.h</code></a>
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for complete details.
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</p><p>
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A small example of tuning the default:
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</p><pre class="programlisting">
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#include <parallel/algorithm>
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#include <parallel/settings.h>
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int main()
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{
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__gnu_parallel::_Settings s;
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s.algorithm_strategy = __gnu_parallel::force_parallel;
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__gnu_parallel::_Settings::set(s);
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// Do work... all algorithms will be parallelized, always.
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return 0;
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}
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</pre></div></div><div class="section"><div class="titlepage"><div><div><h3 class="title"><a id="parallel_mode.design.impl"></a>Implementation Namespaces</h3></div></div></div><p> One namespace contain versions of code that are always
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explicitly sequential:
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<code class="code">__gnu_serial</code>.
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</p><p> Two namespaces contain the parallel mode:
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<code class="code">std::__parallel</code> and <code class="code">__gnu_parallel</code>.
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</p><p> Parallel implementations of standard components, including
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template helpers to select parallelism, are defined in <code class="code">namespace
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std::__parallel</code>. For instance, <code class="function">std::transform</code> from <code class="filename">algorithm</code> has a parallel counterpart in
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<code class="function">std::__parallel::transform</code> from <code class="filename">parallel/algorithm</code>. In addition, these parallel
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implementations are injected into <code class="code">namespace
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__gnu_parallel</code> with using declarations.
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</p><p> Support and general infrastructure is in <code class="code">namespace
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__gnu_parallel</code>.
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</p><p> More information, and an organized index of types and functions
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related to the parallel mode on a per-namespace basis, can be found in
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the generated source documentation.
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</p></div></div><div class="navfooter"><hr /><table width="100%" summary="Navigation footer"><tr><td width="40%" align="left"><a accesskey="p" href="parallel_mode_using.html">Prev</a> </td><td width="20%" align="center"><a accesskey="u" href="parallel_mode.html">Up</a></td><td width="40%" align="right"> <a accesskey="n" href="parallel_mode_test.html">Next</a></td></tr><tr><td width="40%" align="left" valign="top">Using </td><td width="20%" align="center"><a accesskey="h" href="../index.html">Home</a></td><td width="40%" align="right" valign="top"> Testing</td></tr></table></div></body></html> |