# Rounding Policies

In order to be as general as possible, the library uses a class to compute all the necessary functions rounded upward or downward. This class is the first parameter of `policies`, it is also the type named `rounding` in the policy definition of `interval`.

By default, it is `interval_lib::rounded_math<T>`. The class `interval_lib::rounded_math` is already specialized for the standard floating types (`float` , `double` and `long double`). So if the base type of your intervals is not one of these, a good solution would probably be to provide a specialization of this class. But if the default specialization of `rounded_math<T>` for `float`, `double`, or `long double` is not what you seek, or you do not want to specialize `interval_lib::rounded_math<T>` (say because you prefer to work in your own namespace) you can also define your own rounding policy and pass it directly to `interval_lib::policies`.

## Requirements

Here comes what the class is supposed to provide. The domains are written next to their respective functions (as you can see, the functions do not have to worry about invalid values, but they have to handle infinite arguments).

```/* Rounding requirements */
struct rounding {
// defaut constructor, destructor
rounding();
~rounding();
// mathematical operations
T add_down(T, T); // [-∞;+∞][-∞;+∞]
T add_up  (T, T); // [-∞;+∞][-∞;+∞]
T sub_down(T, T); // [-∞;+∞][-∞;+∞]
T sub_up  (T, T); // [-∞;+∞][-∞;+∞]
T mul_down(T, T); // [-∞;+∞][-∞;+∞]
T mul_up  (T, T); // [-∞;+∞][-∞;+∞]
T div_down(T, T); // [-∞;+∞]([-∞;+∞]-{0})
T div_up  (T, T); // [-∞;+∞]([-∞;+∞]-{0})
T sqrt_down(T);   // ]0;+∞]
T sqrt_up  (T);   // ]0;+∞]
T exp_down(T);    // [-∞;+∞]
T exp_up  (T);    // [-∞;+∞]
T log_down(T);    // ]0;+∞]
T log_up  (T);    // ]0;+∞]
T cos_down(T);    // [0;2π]
T cos_up  (T);    // [0;2π]
T tan_down(T);    // ]-π/2;π/2[
T tan_up  (T);    // ]-π/2;π/2[
T asin_down(T);   // [-1;1]
T asin_up  (T);   // [-1;1]
T acos_down(T);   // [-1;1]
T acos_up  (T);   // [-1;1]
T atan_down(T);   // [-∞;+∞]
T atan_up  (T);   // [-∞;+∞]
T sinh_down(T);   // [-∞;+∞]
T sinh_up  (T);   // [-∞;+∞]
T cosh_down(T);   // [-∞;+∞]
T cosh_up  (T);   // [-∞;+∞]
T tanh_down(T);   // [-∞;+∞]
T tanh_up  (T);   // [-∞;+∞]
T asinh_down(T);  // [-∞;+∞]
T asinh_up  (T);  // [-∞;+∞]
T acosh_down(T);  // [1;+∞]
T acosh_up  (T);  // [1;+∞]
T atanh_down(T);  // [-1;1]
T atanh_up  (T);  // [-1;1]
T median(T, T);   // [-∞;+∞][-∞;+∞]
T int_down(T);    // [-∞;+∞]
T int_up  (T);    // [-∞;+∞]
// unprotected rounding class
typedef ... unprotected_rounding;
};```

The constructor and destructor of the rounding class have a very important semantic requirement: they are responsible for setting and resetting the rounding modes of the computation on T. For instance, if T is a standard floating point type and floating point computation is performed according to the Standard IEEE 754, the constructor can save the current rounding state, each `_up` (resp. `_down`) function will round up (resp. down), and the destructor will restore the saved rounding state. Indeed this is the behavior of the default rounding policy.

The meaning of all the mathematical functions up until `atanh_up` is clear: each function returns number representable in the type `T` which is a lower bound (for` _down`) or upper bound (for `_up`) on the true mathematical result of the corresponding function. The function `median` computes the average of its two arguments rounded to its nearest representable number. The functions `int_down` and `int_up` compute the nearest integer smaller or bigger than their argument.

The type `unprotected_rounding` allows to remove all controls. For reasons why one might to do this, see the protection paragraph below.

## Overview of the provided classes

A lot of classes are provided. The classes are organized by level. At the bottom is the class `rounding_control`. At the next level come `rounded_arith_exact`, `rounded_arith_std` and `rounded_arith_opp`. Then there are `rounded_transc_dummy`, `rounded_transc_exact`, `rounded_transc_std` and `rounded_transc_opp`. And finally are `save_state` and `save_state_nothing`. Each of these classes provide a set of members that are required by the classes of the next level. For example, a `rounded_transc_...` class needs the members of a `rounded_arith_...` class.

When they exist in two versions `_std` and `_opp`, the first one does switch the rounding mode each time, and the second one tries to keep it oriented toward plus infinity. The main purpose of the `_opp` version is to speed up the computations through the use of the "opposite trick" (see the performance notes). This version requires the rounding mode to be upward before entering any computation functions of the class. It guarantees that the rounding mode will still be upward at the exit of the functions.

Please note that it is really a very bad idea to mix the `_opp` version with the `_std` since they do not have compatible properties.

There is a third version named `_exact` which computes the functions without changing the rounding mode. It is an "exact" version because it is intended for a base type that produces exact results.

The last version is the `_dummy` version. It does not do any computations but still produces compatible results.

Please note that it is possible to use the "exact" version for an inexact base type, e.g. `float` or `double`. In that case, the inclusion property is no longer guaranteed, but this can be useful to speed up the computation when the inclusion property is not desired strictly. For instance, in computer graphics, a small error due to floating-point roundoff is acceptable as long as an approximate version of the inclusion property holds.

Here comes what each class defines. Later, when they will be described more thoroughly, these members will not be repeated. Please come back here in order to see them. Inheritance is also used to avoid repetitions.

```template <class T>
struct rounding_control
{
typedef ... rounding_mode;
void set_rounding_mode(rounding_mode);
void get_rounding_mode(rounding_mode&);
void downward ();
void upward   ();
void to_nearest();
T to_int(T);
T force_rounding(T);
};

template <class T, class Rounding>
struct rounded_arith_... : Rounding
{
void init();
T add_up  (T, T);
T sub_down(T, T);
T sub_up  (T, T);
T mul_down(T, T);
T mul_up  (T, T);
T div_down(T, T);
T div_up  (T, T);
T sqrt_down(T);
T sqrt_up  (T);
T median(T, T);
T int_down(T);
T int_up  (T);
};

template <class T, class Rounding>
struct rounded_transc_... : Rounding
{
T exp_down(T);
T exp_up  (T);
T log_down(T);
T log_up  (T);
T cos_down(T);
T cos_up  (T);
T tan_down(T);
T tan_up  (T);
T asin_down(T);
T asin_up  (T);
T acos_down(T);
T acos_up  (T);
T atan_down(T);
T atan_up  (T);
T sinh_down(T);
T sinh_up  (T);
T cosh_down(T);
T cosh_up  (T);
T tanh_down(T);
T tanh_up  (T);
T asinh_down(T);
T asinh_up  (T);
T acosh_down(T);
T acosh_up  (T);
T atanh_down(T);
T atanh_up  (T);
};

template <class Rounding>
struct save_state_... : Rounding
{
save_state_...();
~save_state_...();
typedef ... unprotected_rounding;
};```

## Synopsis.

```namespace boost {
namespace numeric {
namespace interval_lib {

/* basic rounding control */
template <class T>  struct rounding_control;

/* arithmetic functions rounding */
template <class T, class Rounding = rounding_control<T> > struct rounded_arith_exact;
template <class T, class Rounding = rounding_control<T> > struct rounded_arith_std;
template <class T, class Rounding = rounding_control<T> > struct rounded_arith_opp;

/* transcendental functions rounding */
template <class T, class Rounding> struct rounded_transc_dummy;
template <class T, class Rounding = rounded_arith_exact<T> > struct rounded_transc_exact;
template <class T, class Rounding = rounded_arith_std<T> > struct rounded_transc_std;
template <class T, class Rounding = rounded_arith_opp<T> > struct rounded_transc_opp;

/* rounding-state-saving classes */
template <class Rounding> struct save_state;
template <class Rounding> struct save_state_nothing;

/* default policy for type T */
template <class T>  struct rounded_math;
template <>  struct rounded_math<float>;
template <>  struct rounded_math<double>;

/* some metaprogramming to convert a protected to unprotected rounding */
template <class I> struct unprotect;

} // namespace interval_lib
} // namespace numeric
} // namespace boost```

## Description of the provided classes

We now describe each class in the order they appear in the definition of a rounding policy (this outermost-to-innermost order is the reverse order from the synopsis).

### Protection control

Protection refers to the fact that the interval operations will be surrounded by rounding mode controls. Unprotecting a class means to remove all the rounding controls. Each rounding policy provides a type `unprotected_rounding`. The required type `unprotected_rounding` gives another rounding class that enables to work when nested inside rounding. For example, the first three lines below should all produce the same result (because the first operation is the rounding constructor, and the last is its destructor, which take care of setting the rounding modes); and the last line is allowed to have an undefined behavior (since no rounding constructor or destructor is ever called).

```T c; { rounding rnd; c = rnd.add_down(a, b); }
T c; { rounding rnd1; { rounding rnd2; c = rnd2.add_down(a, b); } }
T c; { rounding rnd1; { rounding::unprotected_rounding rnd2; c = rnd2.add_down(a, b); } }
T d; { rounding::unprotected_rounding rnd; d = rnd.add_down(a, b); }```

Naturally `rounding::unprotected_rounding` may simply be `rounding` itself. But it can improve performance if it is a simplified version with empty constructor and destructor. In order to avoid undefined behaviors, in the library, an object of type `rounding::unprotected_rounding` is guaranteed to be created only when an object of type `rounding` is already alive. See the performance notes for some additional details.

The support library defines a metaprogramming class template `unprotect` which takes an interval type `I` and returns an interval type `unprotect<I>::type` where the rounding policy has been unprotected. Some information about the types: ```interval<T, interval_lib::policies<Rounding, _> >::traits_type::rounding``` is the same type as `Rounding`, and ```unprotect<interval<T, interval_lib::policies<Rounding, _> > >::type``` is the same type as ```interval<T, interval_lib::policies<Rounding::unprotected, _> >```.

### State saving

First comes `save_state`. This class is responsible for saving the current rounding mode and calling init in its constructor, and for restoring the saved rounding mode in its destructor. This class also defines the `unprotected_rounding` type.

If the rounding mode does not require any state-saving or initialization, `save_state_nothing` can be used instead of `save_state`.

### Transcendental functions

The classes `rounded_transc_exact`, `rounded_transc_std` and `rounded_transc_opp` expect the std namespace to provide the functions exp log cos tan acos asin atan cosh sinh tanh acosh asinh atanh. For the `_std` and `_opp` versions, all these functions should respect the current rounding mode fixed by a call to downward or upward.

Please note: Unfortunately, the latter is rarely the case. It is the reason why a class `rounded_transc_dummy` is provided which does not depend on the functions from the std namespace. There is no magic, however. The functions of `rounded_transc_dummy` do not compute anything. They only return valid values. For example, `cos_down` always returns -1. In this way, we do verify the inclusion property for the default implementation, even if this has strictly no value for the user. In order to have useful values, another policy should be used explicitely, which will most likely lead to a violation of the inclusion property. In this way, we ensure that the violation is clearly pointed out to the user who then knows what he stands against. This class could have been used as the default transcendental rounding class, but it was decided it would be better for the compilation to fail due to missing declarations rather than succeed thanks to valid but unusable functions.

### Basic arithmetic functions

The classes `rounded_arith_std` and `rounded_arith_opp` expect the operators + - * / and the function `std::sqrt` to respect the current rounding mode.

The class `rounded_arith_exact` requires `std::floor` and `std::ceil` to be defined since it can not rely on `to_int`.

### Rounding control

The functions defined by each of the previous classes did not need any explanation. For example, the behavior of `add_down` is to compute the sum of two numbers rounded downward. For `rounding_control`, the situation is a bit more complex.

The basic function is `force_rounding` which returns its argument correctly rounded accordingly to the current rounding mode if it was not already the case. This function is necessary to handle delayed rounding. Indeed, depending on the way the computations are done, the intermediate results may be internaly stored in a more precise format and it can lead to a wrong rounding. So the function enforces the rounding. Here is an example of what happens when the rounding is not enforced.

The function `get_rounding_mode` returns the current rounding mode, `set_rounding_mode` sets the rounding mode back to a previous value returned by `get_rounding_mode`. `downward`, `upward` and `to_nearest` sets the rounding mode in one of the three directions. This rounding mode should be global to all the functions that use the type `T`. For example, after a call to `downward`, `force_rounding(x+y)` is expected to return the sum rounded toward -∞.

The function `to_int` computes the nearest integer accordingly to the current rounding mode.

The non-specialized version of `rounding_control` does not do anything. The functions for the rounding mode are empty, and `to_int` and `force_rounding` are identity functions. The `pi_` constant functions return suitable integers (for example, `pi_up` returns `T(4)`).

The class template `rounding_control` is specialized for `float`, `double` and `long double` in order to best use the floating point unit of the computer.

## Template class rounded_math

The default policy (aka `rounded_math<T>`) is simply defined as:

`template <class T> struct rounded_math<T> : save_state_nothing<rounded_arith_exact<T> > {};`

and the specializations for `float`, `double` and `long double` use `rounded_arith_opp`, as in:

```template <> struct rounded_math<float>       : save_state<rounded_arith_opp<float> >       {};
template <> struct rounded_math<double>      : save_state<rounded_arith_opp<double> >      {};
template <> struct rounded_math<long double> : save_state<rounded_arith_opp<long double> > {};```

## Performance Issues

This paragraph deals mostly with the performance of the library with intervals using the floating-point unit (FPU) of the computer. Let's consider the sum of [a,b] and [c,d] as an example. The result is [`down`(a+c), `up`(b+d)], where `down` and `up` indicate the rounding mode needed.

### Rounding Mode Switch

If the FPU is able to use a different rounding mode for each operation, there is no problem. For example, it's the case for the Alpha processor: each floating-point instruction can specify a different rounding mode. However, the IEEE-754 Standard does not require such a behavior. So most of the FPUs only provide some instructions to set the rounding mode for all subsequent operations. And generally, these instructions need to flush the pipeline of the FPU.

In this situation, the time needed to sum [a,b] and [c,d] is far worse than the time needed to calculate a+b and c+d since the two additions cannot be parallelized. Consequently, the objective is to diminish the number of rounding mode switches.

If this library is not used to provide exact computations, but only for pair arithmetic, the solution is quite simple: do not use rounding. In that case, doing the sum [a,b] and [c,d] will be as fast as computing a+b and c+d. Everything is perfect.

However, if exact computations are required, such a solution is totally unthinkable. So, are we penniless? No, there is still a trick available. Indeed, down(a+c) = -up(-a-c) if the unary minus is an exact operation. It is now possible to calculate the whole sum with the same rounding mode. Generally, the cost of the mode switching is worse than the cost of the sign changes.

Let's recapitulate. Before, when doing an addition, there were three rounding mode switches (down, up and restore). Now, with this little trick, there are only two switches (up and restore). It is better, but still a bottleneck when many operations are nested. Indeed, the generated code for [a,b] + [c,d] + [e,f] will probably look like:

```up();
t1 = -(-a - c);
t2 = b + d;
restore();
up();
x = -(-t1 - e);
y = t2 + f;
restore();```

If you think it is possible to do much better, you are right. For example, this is better (and probably optimal):

```up();
x = -(-a - c - e);
y = b + d + f;
restore();```

Such a code will be generated by a compiler if the computations are made without initialization and restoration of the rounding mode. However, it would be far too easy if there were no drawback: because the rounding mode is not restored in the meantime, operations on floating-point numbers must be prohibited. This method can only be used if all the operations are operations on intervals (or operations between an interval and a floating point number).

#### Example

Here is an example of the Horner scheme to compute the value of a polynom. The rounding mode switches are disabled for the whole computation.

```// I is an interval class, the polynom is a simple array
template<class I>
I horner(const I& x, const I p[], int n) {

// save and initialize the rounding mode
typename I::traits_type::rounding rnd;

// define the unprotected version of the interval type
typedef typename boost::numeric::interval_lib::unprotect<I>::type R;

const R& a = x;
R y = p[n - 1];
for(int i = n - 2; i >= 0; i--) {
y = y * a + (const R&)(p[i]);
}
return y;

// restore the rounding mode with the destruction of rnd
}```

Please note that a rounding object is especially created in order to compensate for the protection loss. Each interval of type I is converted in an interval of type R before any operations. If this conversion is not done, the result is still correct, but the interest of this whole optimization has disappeared. Whenever possible, it is good to convert to ```const R&``` instead of `R`: indeed, the function could already be called inside an unprotection block so the types `R` and `I` would be the same interval, no need for a conversion.

#### Uninteresting remark

It was said at the beginning that the Alpha processors can use a specific rounding mode for each operation. However, due to the instruction format, the rounding toward plus infinity is not available. Only the rounding toward minus infinity can be used. So the trick using the change of sign becomes essential, but there is no need to save and restore the rounding mode on both sides of an operation.

### Extended Registers

There is another problem besides the cost of the rounding mode switch. Some FPUs use extended registers (for example, float computations will be done with double registers, or double computations with long double registers). Consequently, many problems can arise.

The first one is due to to the extended precision of the mantissa. The rounding is also done on this extended precision. And consequently, we still have down(a+b) = -up(-a-b) in the extended registers. But back to the standard precision, we now have down(a+b) < -up(-a-b) instead of an equality. A solution could be not to use this method. But there still are other problems, with the comparisons between numbers for example.

Naturally, there is also a problem with the extended precision of the exponent. To illustrate this problem, let m be the biggest number before +inf. If we calculate 2*[m,m], the answer should be [m,inf]. But due to the extended registers, the FPU will first store [2m,2m] and then convert it to [inf,inf] at the end of the calculus (when the rounding mode is toward +inf). So the answer is no more accurate.

There is only one solution: to force the FPU to convert the extended values back to standard precision after each operation. Some FPUs provide an instruction able to do this conversion (for example the PowerPC processors). But for the FPUs that do not provide it (the x86 processors), the only solution is to write the values to memory and read them back. Such an operation is obviously very expensive.

## Some Examples

Here come several cases:

• if you need precise computations with the `float` or `double` types, use the default `rounded_math<T>`;
• for fast wide intervals without any rounding nor precision, use `save_state_nothing<rounded_transc_exact<T> >`;
• for an exact type (like int or rational with a little help for infinite and NaN values) without support for transcendental functions, the solution could be ```save_state_nothing<rounded_transc_dummy<T, rounded_arith_exact<T> > >``` or directly `save_state_nothing<rounded_arith_exact<T> >`;
• if it is a more complex case than the previous ones, the best thing is probably to directly define your own policy.

Revised: 2003-01-21
Copyright (c) Guillaume Melquiond, Sylvain Pion, Hervé Brönnimann, 2002.
Polytechnic University.