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<title>The Overhead in the Number Class Wrapper</title>
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<div class="titlepage"><div><div><h3 class="title">
<a name="boost_multiprecision.perf.overhead"></a><a class="link" href="overhead.html" title="The Overhead in the Number Class Wrapper">The Overhead in the
Number Class Wrapper</a>
</h3></div></div></div>
<p>
Using a simple <a href="http://www.boost.org/doc/libs/release/libs/multiprecision/doc/html/../../performance/arithmetic_backend.hpp" target="_top">backend
class</a> that wraps any <a href="https://en.cppreference.com/w/cpp/language/types" target="_top">fundamental
(built-in)</a> arithmetic type we can measure the overhead involved in
wrapping a type inside the <code class="computeroutput"><span class="identifier">number</span></code>
frontend, and the effect that turning on expression templates has. The following
table compares the performance between <code class="computeroutput"><span class="keyword">double</span></code>
and a <code class="computeroutput"><span class="keyword">double</span></code> wrapped inside
class <code class="computeroutput"><span class="identifier">number</span></code>:
</p>
<div class="table">
<a name="boost_multiprecision.perf.overhead.bessel_functions_16_digit_precis"></a><p class="title"><b>Table 1.12. Bessel Functions (16 digit precision)</b></p>
<div class="table-contents"><table class="table" summary="Bessel Functions (16 digit precision)">
<colgroup>
<col>
<col>
</colgroup>
<thead><tr>
<th>
<p>
Type
</p>
</th>
<th>
<p>
Time
</p>
</th>
</tr></thead>
<tbody>
<tr>
<td>
<p>
arithmetic_backend&lt;double&gt;
</p>
</td>
<td>
<p>
2.09301 (0.00133409s)
</p>
</td>
</tr>
<tr>
<td>
<p>
arithmetic_backend&lt;double&gt; - no expression templates
</p>
</td>
<td>
<p>
1 (0.000637403s)
</p>
</td>
</tr>
<tr>
<td>
<p>
double
</p>
</td>
<td>
<p>
1.07956 (0.000688113s)
</p>
</td>
</tr>
</tbody>
</table></div>
</div>
<br class="table-break"><p>
As you can see whether or not there is an overhead, and how large it is depends
on the actual situation, but the overhead is in any cases small. Expression
templates generally add a greater overhead the more complex the expression
becomes due to the logic of figuring out how to best unpack and evaluate
the expression, but of course this is also the situation where you save more
temporaries. For a "trivial" backend like this, saving temporaries
has no benefit, but for larger types it becomes a bigger win.
</p>
<p>
The following table compares arithmetic using either <code class="computeroutput"><span class="keyword">long</span>
<span class="keyword">long</span></code> or <code class="computeroutput"><span class="identifier">number</span><span class="special">&lt;</span><span class="identifier">arithmetic_backend</span><span class="special">&lt;</span><span class="keyword">long</span> <span class="keyword">long</span><span class="special">&gt;</span> <span class="special">&gt;</span></code> for the <a href="http://www.boost.org/doc/libs/release/libs/multiprecision/doc/html/../../performance/voronoi_performance.cpp" target="_top">voronoi-diagram
builder test</a>:
</p>
<div class="informaltable"><table class="table">
<colgroup>
<col>
<col>
</colgroup>
<thead><tr>
<th>
<p>
Type
</p>
</th>
<th>
<p>
Relative time
</p>
</th>
</tr></thead>
<tbody>
<tr>
<td>
<p>
<code class="computeroutput"><span class="identifier">int64_t</span></code>
</p>
</td>
<td>
<p>
<span class="bold"><strong>1.0</strong></span>(0.0128646s)
</p>
</td>
</tr>
<tr>
<td>
<p>
<code class="computeroutput"><span class="identifier">number</span><span class="special">&lt;</span><span class="identifier">arithmetic_backend</span><span class="special">&lt;</span><span class="identifier">int64_t</span><span class="special">&gt;,</span>
<span class="identifier">et_off</span><span class="special">&gt;</span></code>
</p>
</td>
<td>
<p>
1.005 (0.0129255s)
</p>
</td>
</tr>
</tbody>
</table></div>
<p>
This test involves mainly creating a lot of temporaries and performing a
small amount of arithmetic on them, with very little difference in performance
between the native and "wrapped" types.
</p>
<div class="table">
<a name="boost_multiprecision.perf.overhead.platform"></a><p class="title"><b>Table 1.13. Platform Details</b></p>
<div class="table-contents"><table class="table" summary="Platform Details">
<colgroup>
<col>
<col>
</colgroup>
<thead><tr>
<th>
<p>
Platform
</p>
</th>
<th>
<p>
Linux 5.3.0-24-generic, version #26-Ubuntu SMP Thu Nov 14 01:33:18
UTC 2019, x86_64
</p>
</th>
</tr></thead>
<tbody>
<tr>
<td>
<p>
Compiler
</p>
</td>
<td>
<p>
GNU C++ version 9.2.1 20191008
</p>
</td>
</tr>
<tr>
<td>
<p>
Boost
</p>
</td>
<td>
<p>
1.72.0
</p>
</td>
</tr>
<tr>
<td>
<p>
Run date
</p>
</td>
<td>
<p>
Dec 13 2019
</p>
</td>
</tr>
</tbody>
</table></div>
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