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<title>Comparison of Cube Root Finding Algorithms</title>
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<div class="section">
<div class="titlepage"><div><div><h4 class="title">
<a name="math_toolkit.roots.root_comparison.cbrt_comparison"></a><a class="link" href="cbrt_comparison.html" title="Comparison of Cube Root Finding Algorithms">Comparison
of Cube Root Finding Algorithms</a>
</h4></div></div></div>
<p>
In the table below, the cube root of 28 was computed for three <a href="http://en.cppreference.com/w/cpp/language/types" target="_top">fundamental
types</a> floating-point types, and one <a href="../../../../../../../libs/multiprecision/doc/html/index.html" target="_top">Boost.Multiprecision</a>
type <a href="../../../../../../../libs/multiprecision/doc/html/boost_multiprecision/tut/floats/cpp_bin_float.html" target="_top">cpp_bin_float</a>
using 50 decimal digit precision, using four algorithms.
</p>
<p>
The 'exact' answer was computed using a 100 decimal digit type:
</p>
<pre class="programlisting"><span class="identifier">cpp_bin_float_100</span> <span class="identifier">full_answer</span> <span class="special">(</span><span class="string">"3.036588971875662519420809578505669635581453977248111123242141654169177268411884961770250390838097895"</span><span class="special">);</span>
</pre>
<p>
Times were measured using <a href="../../../../../../../libs/timer/doc/index.html" target="_top">Boost.Timer</a>
using <code class="computeroutput"><span class="keyword">class</span> <span class="identifier">cpu_timer</span></code>.
</p>
<div class="itemizedlist"><ul class="itemizedlist" style="list-style-type: disc; ">
<li class="listitem">
<span class="emphasis"><em>Its</em></span> is the number of iterations taken to find
the root.
</li>
<li class="listitem">
<span class="emphasis"><em>Times</em></span> is the CPU time-taken in arbitrary units.
</li>
<li class="listitem">
<span class="emphasis"><em>Norm</em></span> is a normalized time, in comparison to the
quickest algorithm (with value 1.00).
</li>
<li class="listitem">
<span class="emphasis"><em>Dis</em></span> is the distance from the nearest representation
of the 'exact' root in bits. Distance from the 'exact' answer is measured
by using function <a href="../../../../../../../libs/math/doc/html/math_toolkit/next_float/float_distance.html" target="_top">Boost.Math
float_distance</a>. One or two bits distance means that all results
are effectively 'correct'. Zero means 'exact' - the nearest <a href="http://en.wikipedia.org/wiki/Floating_point#Representable_numbers.2C_conversion_and_rounding" target="_top">representable</a>
value for the floating-point type.
</li>
</ul></div>
<p>
The cube-root function is a simple function, and is a contrived example
for root-finding. It does allow us to investigate some of the factors controlling
efficiency that may be extrapolated to more complex functions.
</p>
<p>
The program used was <a href="../../../../../example/root_finding_algorithms.cpp" target="_top">root_finding_algorithms.cpp</a>.
100000 evaluations of each floating-point type and algorithm were used
and the CPU times were judged from repeat runs to have an uncertainty of
10 %. Comparing MSVC for <code class="computeroutput"><span class="keyword">double</span></code>
and <code class="computeroutput"><span class="keyword">long</span> <span class="keyword">double</span></code>
(which are identical on this patform) may give a guide to uncertainty of
timing.
</p>
<p>
The requested precision was set as follows:
</p>
<div class="informaltable"><table class="table">
<colgroup>
<col>
<col>
</colgroup>
<thead><tr>
<th>
<p>
Function
</p>
</th>
<th>
<p>
Precision Requested
</p>
</th>
</tr></thead>
<tbody>
<tr>
<td>
<p>
TOMS748
</p>
</td>
<td>
<p>
numeric_limits&lt;T&gt;::digits - 2
</p>
</td>
</tr>
<tr>
<td>
<p>
Newton
</p>
</td>
<td>
<p>
floor(numeric_limits&lt;T&gt;::digits * 0.6)
</p>
</td>
</tr>
<tr>
<td>
<p>
Halley
</p>
</td>
<td>
<p>
floor(numeric_limits&lt;T&gt;::digits * 0.4)
</p>
</td>
</tr>
<tr>
<td>
<p>
Schr&#246;der
</p>
</td>
<td>
<p>
floor(numeric_limits&lt;T&gt;::digits * 0.4)
</p>
</td>
</tr>
</tbody>
</table></div>
<div class="itemizedlist"><ul class="itemizedlist" style="list-style-type: disc; ">
<li class="listitem">
The C++ Standard cube root function <a href="http://en.cppreference.com/w/cpp/numeric/math/cbrt" target="_top">std::cbrt</a>
is only defined for built-in or fundamental types, so cannot be used
with any User-Defined floating-point types like <a href="../../../../../../../libs/multiprecision/doc/html/index.html" target="_top">Boost.Multiprecision</a>.
This, and that the cube function is so impeccably-behaved, allows the
implementer to use many tricks to achieve a fast computation. On some
platforms,<code class="computeroutput"><span class="identifier">std</span><span class="special">::</span><span class="identifier">cbrt</span></code> appeared several times as quick
as the more general <code class="computeroutput"><span class="identifier">boost</span><span class="special">::</span><span class="identifier">math</span><span class="special">::</span><span class="identifier">cbrt</span></code>,
on other platforms / compiler options <code class="computeroutput"><span class="identifier">boost</span><span class="special">::</span><span class="identifier">math</span><span class="special">::</span><span class="identifier">cbrt</span></code>
is noticeably faster. In general, the results are highly dependent
on the code-generation / processor architecture selection compiler
options used. One can assume that the standard library will have been
compiled with options <span class="emphasis"><em>nearly</em></span> optimal for the platform
it was installed on, where as the user has more choice over the options
used for Boost.Math. Pick something too general/conservative and performance
suffers, while selecting options that make use of the latest instruction
set opcodes speed's things up noticeably.
</li>
<li class="listitem">
Two compilers in optimise mode were compared: GCC 4.9.1 using Netbeans
IDS and Microsoft Visual Studio 2013 (Update 1) on the same hardware.
The number of iterations seemed consistent, but the relative run-times
surprisingly different.
</li>
<li class="listitem">
<code class="computeroutput"><span class="identifier">boost</span><span class="special">::</span><span class="identifier">math</span><span class="special">::</span><span class="identifier">cbrt</span></code> allows use with <span class="emphasis"><em>any
user-defined floating-point type</em></span>, conveniently <a href="../../../../../../../libs/multiprecision/doc/html/index.html" target="_top">Boost.Multiprecision</a>.
It too can take some advantage of the good-behaviour of the cube function,
compared to the more general implementation in the nth root-finding
examples. For example, it uses a polynomial approximation to generate
a better guess than dividing the exponent by three, and can avoid the
complex checks in <a class="link" href="../roots_deriv.html#math_toolkit.roots.roots_deriv.newton">Newton-Raphson
iteration</a> required to prevent the search going wildly off-track.
For a known precision, it may also be possible to fix the number of
iterations, allowing inlining and loop unrolling. It also algebraically
simplifies the Halley steps leading to a big reduction in the number
of floating point operations required compared to a "black box"
implementation that calculates the derivatives seperately and then
combines them in the Halley code. Typically, it was found that computation
using type <code class="computeroutput"><span class="keyword">double</span></code> took
a few times longer when using the various root-finding algorithms directly
rather than the hand coded/optimized <code class="computeroutput"><span class="identifier">cbrt</span></code>
routine.
</li>
<li class="listitem">
The importance of getting a good guess can be seen by the iteration
count for the multiprecision case: here we "cheat" a little
and use the cube-root calculated to double precision as the initial
guess. The limitation of this tactic is that the range of possible
(exponent) values may be less than the multiprecision type.
</li>
<li class="listitem">
For <a href="http://en.cppreference.com/w/cpp/language/types" target="_top">fundamental
types</a>, there was little to choose between the three derivative
methods, but for <a href="../../../../../../../libs/multiprecision/doc/html/boost_multiprecision/tut/floats/cpp_bin_float.html" target="_top">cpp_bin_float</a>,
<a class="link" href="../roots_deriv.html#math_toolkit.roots.roots_deriv.newton">Newton-Raphson
iteration</a> was twice as fast. Note that the cube-root is an extreme
test case as the cost of calling the functor is so cheap that the runtimes
are largely dominated by the complexity of the iteration code.
</li>
<li class="listitem">
Compiling with optimisation halved computation times, and any differences
between algorithms became nearly negligible. The optimisation speed-up
of the <a href="http://portal.acm.org/citation.cfm?id=210111" target="_top">TOMS
Algorithm 748: enclosing zeros of continuous functions</a> was
especially noticable.
</li>
<li class="listitem">
Using a multiprecision type like <code class="computeroutput"><span class="identifier">cpp_bin_float_50</span></code>
for a precision of 50 decimal digits took a lot longer, as expected
because most computation uses software rather than 64-bit floating-point
hardware. Speeds are often more than 50 times slower.
</li>
<li class="listitem">
Using <code class="computeroutput"><span class="identifier">cpp_bin_float_50</span></code>,
<a href="http://portal.acm.org/citation.cfm?id=210111" target="_top">TOMS Algorithm
748: enclosing zeros of continuous functions</a> was much slower
showing the benefit of using derivatives. <a class="link" href="../roots_deriv.html#math_toolkit.roots.roots_deriv.newton">Newton-Raphson
iteration</a> was found to be twice as quick as either of the second-derivative
methods: this is an extreme case though, the function and its derivatives
are so cheap to compute that we're really measuring the complexity
of the boilerplate root-finding code.
</li>
<li class="listitem">
For multiprecision types only one or two extra <span class="emphasis"><em>iterations</em></span>
are needed to get the remaining 35 digits, whatever the algorithm used.
(The time taken was of course much greater for these types).
</li>
<li class="listitem">
Using a 100 decimal-digit type only doubled the time and required only
a very few more iterations, so the cost of extra precision is mainly
the underlying cost of computing more digits, not in the way the algorithm
works. This confirms previous observations using <a href="http://www.shoup.net/ntl/" target="_top">NTL
A Library for doing Number Theory</a> high-precision types.
</li>
</ul></div>
<h6>
<a name="math_toolkit.roots.root_comparison.cbrt_comparison.h0"></a>
<span class="phrase"><a name="math_toolkit.roots.root_comparison.cbrt_comparison.program_root_finding_algorithms_"></a></span><a class="link" href="cbrt_comparison.html#math_toolkit.roots.root_comparison.cbrt_comparison.program_root_finding_algorithms_">Program
root_finding_algorithms.cpp, Microsoft Visual C++ version 12.0, Dinkumware
standard library version 610, Win32, x64<br> 1000000 evaluations of each
of 5 root_finding algorithms.</a>
</h6>
<div class="table">
<a name="math_toolkit.roots.root_comparison.cbrt_comparison.cbrt_4"></a><p class="title"><b>Table&#160;12.1.&#160;Cube root(28) for float, double, long double and cpp_bin_float_50</b></p>
<div class="table-contents"><table class="table" summary="Cube root(28) for float, double, long double and cpp_bin_float_50">
<colgroup>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
</colgroup>
<thead><tr>
<th>
</th>
<th>
<p>
float
</p>
</th>
<th>
</th>
<th>
</th>
<th>
</th>
<th>
</th>
<th>
<p>
double
</p>
</th>
<th>
</th>
<th>
</th>
<th>
</th>
<th>
</th>
<th>
<p>
long d
</p>
</th>
<th>
</th>
<th>
</th>
<th>
</th>
<th>
</th>
<th>
<p>
cpp50
</p>
</th>
<th>
</th>
<th>
</th>
<td class="auto-generated">&#160;</td>
<td class="auto-generated">&#160;</td>
</tr></thead>
<tbody>
<tr>
<td>
<p>
Algorithm
</p>
</td>
<td>
<p>
Its
</p>
</td>
<td>
<p>
Times
</p>
</td>
<td>
<p>
Norm
</p>
</td>
<td>
<p>
Dis
</p>
</td>
<td>
</td>
<td>
<p>
Its
</p>
</td>
<td>
<p>
Times
</p>
</td>
<td>
<p>
Norm
</p>
</td>
<td>
<p>
Dis
</p>
</td>
<td>
</td>
<td>
<p>
Its
</p>
</td>
<td>
<p>
Times
</p>
</td>
<td>
<p>
Norm
</p>
</td>
<td>
<p>
Dis
</p>
</td>
<td>
</td>
<td>
<p>
Its
</p>
</td>
<td>
<p>
Times
</p>
</td>
<td>
<p>
Norm
</p>
</td>
<td>
<p>
Dis
</p>
</td>
<td>
</td>
</tr>
<tr>
<td>
<p>
cbrt
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
<p>
46875
</p>
</td>
<td>
<p>
<span class="blue">1.0</span>
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
0
</p>
</td>
<td>
<p>
46875
</p>
</td>
<td>
<p>
<span class="blue">1.0</span>
</p>
</td>
<td>
<p>
1
</p>
</td>
<td>
</td>
<td>
<p>
0
</p>
</td>
<td>
<p>
46875
</p>
</td>
<td>
<p>
<span class="blue">1.0</span>
</p>
</td>
<td>
<p>
1
</p>
</td>
<td>
</td>
<td>
<p>
0
</p>
</td>
<td>
<p>
4906250
</p>
</td>
<td>
<p>
1.1
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
</tr>
<tr>
<td>
<p>
TOMS748
</p>
</td>
<td>
<p>
8
</p>
</td>
<td>
<p>
234375
</p>
</td>
<td>
<p>
<span class="red">5.0</span>
</p>
</td>
<td>
<p>
-1
</p>
</td>
<td>
</td>
<td>
<p>
11
</p>
</td>
<td>
<p>
437500
</p>
</td>
<td>
<p>
<span class="red">9.3</span>
</p>
</td>
<td>
<p>
2
</p>
</td>
<td>
</td>
<td>
<p>
11
</p>
</td>
<td>
<p>
437500
</p>
</td>
<td>
<p>
<span class="red">9.3</span>
</p>
</td>
<td>
<p>
2
</p>
</td>
<td>
</td>
<td>
<p>
7
</p>
</td>
<td>
<p>
66218750
</p>
</td>
<td>
<p>
<span class="red">15.</span>
</p>
</td>
<td>
<p>
-2
</p>
</td>
<td>
</td>
</tr>
<tr>
<td>
<p>
Newton
</p>
</td>
<td>
<p>
5
</p>
</td>
<td>
<p>
109375
</p>
</td>
<td>
<p>
2.3
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
6
</p>
</td>
<td>
<p>
125000
</p>
</td>
<td>
<p>
2.7
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
6
</p>
</td>
<td>
<p>
140625
</p>
</td>
<td>
<p>
3.0
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
2
</p>
</td>
<td>
<p>
4531250
</p>
</td>
<td>
<p>
<span class="blue">1.0</span>
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
</tr>
<tr>
<td>
<p>
Halley
</p>
</td>
<td>
<p>
3
</p>
</td>
<td>
<p>
125000
</p>
</td>
<td>
<p>
2.7
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
4
</p>
</td>
<td>
<p>
156250
</p>
</td>
<td>
<p>
3.3
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
4
</p>
</td>
<td>
<p>
156250
</p>
</td>
<td>
<p>
3.3
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
2
</p>
</td>
<td>
<p>
10625000
</p>
</td>
<td>
<p>
2.3
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
</tr>
<tr>
<td>
<p>
Schr&#246;der
</p>
</td>
<td>
<p>
4
</p>
</td>
<td>
<p>
140625
</p>
</td>
<td>
<p>
3.0
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
5
</p>
</td>
<td>
<p>
187500
</p>
</td>
<td>
<p>
4.0
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
5
</p>
</td>
<td>
<p>
203125
</p>
</td>
<td>
<p>
<span class="red">4.3</span>
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
2
</p>
</td>
<td>
<p>
13109375
</p>
</td>
<td>
<p>
2.9
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
</tr>
</tbody>
</table></div>
</div>
<br class="table-break"><h6>
<a name="math_toolkit.roots.root_comparison.cbrt_comparison.h1"></a>
<span class="phrase"><a name="math_toolkit.roots.root_comparison.cbrt_comparison.program_root_finding_algorithms0"></a></span><a class="link" href="cbrt_comparison.html#math_toolkit.roots.root_comparison.cbrt_comparison.program_root_finding_algorithms0">Program
root_finding_algorithms.cpp, GNU C++ version 4.9.2, GNU libstdc++ version
20141030, Win32, x64<br> 1000000 evaluations of each of 5 root_finding
algorithms.</a>
</h6>
<div class="table">
<a name="math_toolkit.roots.root_comparison.cbrt_comparison.cbrt_4_0"></a><p class="title"><b>Table&#160;12.2.&#160;Cube root(28) for float, double, long double and cpp_bin_float_50</b></p>
<div class="table-contents"><table class="table" summary="Cube root(28) for float, double, long double and cpp_bin_float_50">
<colgroup>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
<col>
</colgroup>
<thead><tr>
<th>
</th>
<th>
<p>
float
</p>
</th>
<th>
</th>
<th>
</th>
<th>
</th>
<th>
</th>
<th>
<p>
double
</p>
</th>
<th>
</th>
<th>
</th>
<th>
</th>
<th>
</th>
<th>
<p>
long d
</p>
</th>
<th>
</th>
<th>
</th>
<th>
</th>
<th>
</th>
<th>
<p>
cpp50
</p>
</th>
<th>
</th>
<th>
</th>
<td class="auto-generated">&#160;</td>
<td class="auto-generated">&#160;</td>
</tr></thead>
<tbody>
<tr>
<td>
<p>
Algorithm
</p>
</td>
<td>
<p>
Its
</p>
</td>
<td>
<p>
Times
</p>
</td>
<td>
<p>
Norm
</p>
</td>
<td>
<p>
Dis
</p>
</td>
<td>
</td>
<td>
<p>
Its
</p>
</td>
<td>
<p>
Times
</p>
</td>
<td>
<p>
Norm
</p>
</td>
<td>
<p>
Dis
</p>
</td>
<td>
</td>
<td>
<p>
Its
</p>
</td>
<td>
<p>
Times
</p>
</td>
<td>
<p>
Norm
</p>
</td>
<td>
<p>
Dis
</p>
</td>
<td>
</td>
<td>
<p>
Its
</p>
</td>
<td>
<p>
Times
</p>
</td>
<td>
<p>
Norm
</p>
</td>
<td>
<p>
Dis
</p>
</td>
<td>
</td>
</tr>
<tr>
<td>
<p>
cbrt
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
<p>
46875
</p>
</td>
<td>
<p>
<span class="blue">1.0</span>
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
0
</p>
</td>
<td>
<p>
46875
</p>
</td>
<td>
<p>
<span class="blue">1.0</span>
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
0
</p>
</td>
<td>
<p>
46875
</p>
</td>
<td>
<p>
<span class="blue">1.0</span>
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
0
</p>
</td>
<td>
<p>
3500000
</p>
</td>
<td>
<p>
1.1
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
</tr>
<tr>
<td>
<p>
TOMS748
</p>
</td>
<td>
<p>
8
</p>
</td>
<td>
<p>
187500
</p>
</td>
<td>
<p>
4.0
</p>
</td>
<td>
<p>
-1
</p>
</td>
<td>
</td>
<td>
<p>
11
</p>
</td>
<td>
<p>
406250
</p>
</td>
<td>
<p>
<span class="red">8.7</span>
</p>
</td>
<td>
<p>
2
</p>
</td>
<td>
</td>
<td>
<p>
10
</p>
</td>
<td>
<p>
609375
</p>
</td>
<td>
<p>
<span class="red">13.</span>
</p>
</td>
<td>
<p>
-1
</p>
</td>
<td>
</td>
<td>
<p>
7
</p>
</td>
<td>
<p>
44531250
</p>
</td>
<td>
<p>
<span class="red">14.</span>
</p>
</td>
<td>
<p>
-2
</p>
</td>
<td>
</td>
</tr>
<tr>
<td>
<p>
Newton
</p>
</td>
<td>
<p>
5
</p>
</td>
<td>
<p>
93750
</p>
</td>
<td>
<p>
2.0
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
6
</p>
</td>
<td>
<p>
109375
</p>
</td>
<td>
<p>
2.3
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
6
</p>
</td>
<td>
<p>
171875
</p>
</td>
<td>
<p>
3.7
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
2
</p>
</td>
<td>
<p>
3140625
</p>
</td>
<td>
<p>
<span class="blue">1.0</span>
</p>
</td>
<td>
<p>
-1
</p>
</td>
<td>
</td>
</tr>
<tr>
<td>
<p>
Halley
</p>
</td>
<td>
<p>
3
</p>
</td>
<td>
<p>
93750
</p>
</td>
<td>
<p>
2.0
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
4
</p>
</td>
<td>
<p>
125000
</p>
</td>
<td>
<p>
2.7
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
4
</p>
</td>
<td>
<p>
218750
</p>
</td>
<td>
<p>
<span class="red">4.7</span>
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
2
</p>
</td>
<td>
<p>
7171875
</p>
</td>
<td>
<p>
2.3
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
</tr>
<tr>
<td>
<p>
Schr&#246;der
</p>
</td>
<td>
<p>
4
</p>
</td>
<td>
<p>
109375
</p>
</td>
<td>
<p>
2.3
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
5
</p>
</td>
<td>
<p>
171875
</p>
</td>
<td>
<p>
3.7
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
5
</p>
</td>
<td>
<p>
281250
</p>
</td>
<td>
<p>
<span class="red">6.0</span>
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
<td>
<p>
2
</p>
</td>
<td>
<p>
8703125
</p>
</td>
<td>
<p>
2.8
</p>
</td>
<td>
<p>
0
</p>
</td>
<td>
</td>
</tr>
</tbody>
</table></div>
</div>
<br class="table-break">
</div>
<table xmlns:rev="http://www.cs.rpi.edu/~gregod/boost/tools/doc/revision" width="100%"><tr>
<td align="left"></td>
<td align="right"><div class="copyright-footer">Copyright &#169; 2006-2010, 2012-2014 Nikhar Agrawal,
Anton Bikineev, Paul A. Bristow, Marco Guazzone, Christopher Kormanyos, Hubert
Holin, Bruno Lalande, John Maddock, Jeremy Murphy, Johan R&#229;de, Gautam Sewani,
Benjamin Sobotta, Thijs van den Berg, Daryle Walker and Xiaogang Zhang<p>
Distributed under the Boost Software License, Version 1.0. (See accompanying
file LICENSE_1_0.txt or copy at <a href="http://www.boost.org/LICENSE_1_0.txt" target="_top">http://www.boost.org/LICENSE_1_0.txt</a>)
</p>
</div></td>
</tr></table>
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