**Document number**: P0037R4 **Date**: 2017-10-16 **Reply-to**: John McFarlane, [mcfarlane.john+fixed-point@gmail.com](mailto:mcfarlane.john+fixed-point@gmail.com) **Audience**: SG6, SG14, LEWG # Fixed-Point Real Numbers ## I. Introduction This proposal introduces a system for performing binary fixed-point arithmetic using integral types. ## II. Motivation Floating-point types are an exceedingly versatile and widely supported method of expressing real numbers on modern architectures. However, there are certain situations where fixed-point arithmetic is preferable: * Some systems lack native floating-point registers and must emulate them in software; * many others are capable of performing some or all operations more efficiently using integer arithmetic; * certain applications can suffer from the variability in precision which comes from a dynamic radix point [\[pathengine\]](http://www.pathengine.com/Contents/Overview/FundamentalConcepts/WhyIntegerCoordinates/page.php); * in situations where a variable exponent is not desired, it takes valuable space away from the significand and reduces precision and * not all hardware and compilers produce exactly the same results, leading to non-deterministic results. Integer types provide the basis for an efficient representation of binary fixed-point real numbers. However, laborious, error-prone steps are required to normalize the results of certain operations and to convert to and from fixed-point types. A set of tools for defining and manipulating fixed-point types is proposed. These tools are designed to make work easier for those who traditionally use integers to perform low-level, high-performance fixed-point computation. They are composable such that a wide range of trade-offs between speed, accuracy and safety are supported. ## III. Impact On the Standard This proposal is a pure library extension. It does not require changes to any standard classes or functions. It adds several new class and function templates to new header file, ``. ## IV. Design Decisions The design is driven by the following aims in roughly descending order: 1. to automate the task of using integer types to perform low-level binary fixed-point arithmetic; 2. to facilitate a style of code that is intuitive to anyone who is comfortable with integer and floating-point arithmetic; 3. to treat fixed-point as a super-set of integer such that a fixed-point type with an exponent of zero can provide a drop-in replacement for its underlying integer type 4. to avoid incurring expense for unused features - including compilation time. More generally, the aim of this proposal is to contain within a single API all the tools necessary to perform binary fixed-point arithmetic. The design facilitates a wide range of competing compile-time strategies for avoiding overflow and precision loss, but implements only the simplest by default. Similarly, orthogonal concerns such as run-time overflow detection and rounding modes are deferred to the underlying integer types used as storage. ### Class Template Fixed-point numbers are specializations of template class fixed_point; where the template parameters are described as follows. #### `Rep` Type Template Parameter This parameter indicates the integral type used as storage. Fundamental integral types other than `bool` are ideal choices but any suitably integer-like type can be used. Other than scale, the characteristics of `fixed_point` are the characteristics of `Rep` including: * signedness; * number of digits; * behavior or operators and * alignment. #### `Exponent` Non-Type Template Parameter The exponent of a fixed-point type is the equivalent of the exponent field in a floating-point type and shifts the stored value by the requisite number of bits necessary to produce the desired range. The default value of `Exponent` is zero, giving `fixed_point` the same range as `T`. By far the most common use of fixed-point is to store values with fractional digits. Thus, the exponent is typically a negative value. The resolution of a specialization of `fixed_point` is pow(2, Exponent) and the minimum and maximum values are std::numeric_limits::min() * pow(2, Exponent) and std::numeric_limits::max() * pow(2, Exponent) respectively. Any usage that results in values of `Exponent` which lie outside the range, (`INT_MIN / 2`, `INT_MAX / 2`), may result in undefined behavior and/or overflow or underflow. This range of exponent values is far in excess of the largest built-in floating-point type and should be adequate for all intents and purposes. ### Conversion While effort is made to ensure that significant digits are not lost during conversion, no effort is made to avoid rounding errors. Whatever would happen when converting to and from `Rep` largely applies to `fixed_point` objects also. For example: fixed_point{.499}==0 ...equates to `true` and is considered an acceptable rounding error. ### Access to `Rep` Value It is sometimes necessary to read from and write to the `Rep` value contained in a `fixed_point` object. This is supported through numeric traits, `to_rep` and `from_rep` respectively. These traits are described in paper, [\[P0675\]](https://github.com/johnmcfarlane/papers/blob/master/wg21/p0675r0.md). constexpr auto a = from_rep>()(320); static_assert(a == 1.25); constexpr auto b = to_rep>()(a); static_assert(b == 320); // 1.25*(1<<8) ### Class Template Deduction The type of a `fixed_point` object can be deduced by an integer initializer: auto a = fixed_point(0ul); static_assert(is_same_v>); It can also be deduced with an integral constant of type `constant` (described in [\[P0827\]](https://github.com/johnmcfarlane/papers/blob/master/wg21/p0827r0.md)): constexpr auto b = fixed_point(constant<0xFF00000000L>{}); static_assert(is_same_v>); static_assert(to_rep>()(b) == 0xFF); For `Exponent`, the highest value which does not incur data loss is used. This minimizes the required range of the underlying integer value which reduces the likelihood of out-of-range errors during arithmetic operations. For `Rep`, a fundamental integer type of `int` width is preferred unless a wider type is required. ### Operators Any arithmetic, comparison, logic and bitwise operators that might be applied to integer types can also be applied to fixed-point types. A guiding principle of operator overloads is that they perform as little run-time computation as is practically possible. With the exception of shift and comparison operators, binary operators can take any combination of: * one or two fixed-point arguments and * zero or one arguments of any arithmetic type, i.e. a type for which `numeric_limits` is specialized. Assuming a binary operation, `@`, in the form auto R = S @ T; where `S` is of type `fixed_point` and `T` is a numeric type — possibly another `fixed_point` instantiation — then result, `R`, of the operation is determined as follows. 1. If `T` is a floating-point type, `Float`, then `S` is cast to `Float` and a floating-point operation takes place, e.g.: auto a = fixed_point(3) + 4.f; static_assert(is_same_v); 2. If `T` is a `constant` of integer type, `Integer`, then: a. If the operator is bitwise left shift (`<<`), then the result is `fixed_point` with the shift operator applied. b. If the operator is bitwise right shift (`>>`), then the result is `fixed_point` with the shift operator applied. c. Otherwise, `T` is converted to `fixed_point(T{})`, e.g. auto b = fixed_point(200U) - constant<100L>{}; static_assert(is_same_v(200) - fixed_point(100))>); and proceeding rule #4 subsequently applies. 3. If `T` is an integer type, `Integer`, then: a. If the operator is bitwise shift (`<<` or `>>`), then the result is type `S` with the shift operator applied. b. Otherwise, `T` is cast to `fixed_point`, e.g. auto c = fixed_point<>(5) * 6ul; static_assert(is_same_v(5) * fixed_point(6))>); and proceeding rule #4 subsequently applies. 4. If `T` is type, `fixed_point`, then: a. If the operator is multiplication (`*`), then the result is `fixed_point`, e.g.: constexpr auto d = fixed_point{1.25} * fixed_point{8}; static_assert(is_same_v>); static_assert(d == 10); b. If the operator is division (`/`), then the result is `fixed_point`, e.g.: constexpr auto e = fixed_point{1.5} / fixed_point{2.5}; static_assert(is_same_v>); static_assert(e == .5); c. If the operator is modulo (`%`), then the result is `fixed_point`, e.g.: constexpr auto f = fixed_point{1.5} % fixed_point{2.5}; static_assert(is_same_v>); static_assert(f == .25); d. If the operator is addition (`+`) or subtraction (`-`), then the operand with the greater exponent is converted such that its exponent matches the other operands' exponent. Then the result is `fixed_point`, eg.: constexpr auto g = fixed_point{12.5} - fixed_point{8}; static_assert(is_same_v>); static_assert(g == 4.5); e. If the operator is comparison (`==`, `!=`, `<`, `>`, `<=` or `>=`), then the operand with the greater exponent is converted such that its exponent matches the other operands' exponent. Then the result is `decltype(RepS@RepT)`, eg.: constexpr auto h = fixed_point{12.5} <= fixed_point{8}; static_assert(is_same_v); static_assert(h == false); (See section, **Extended Comparison Range**, for additional details.) f. If the operator is bitwise or (`|`) or xor (`^`) then the same rules as addition (`+`) are applied. g. If the operator is bitwise and (`&`) then the same rules as bitwise or (`|`) are applied except that the greater — not less — exponent is preferred. Some details have been left out for brevity. Unary operators are supported. Some minor variations occur when `S` is not `fixed_point` and `T` is `fixed_point`. The complete set of rules may appear to be large and complex. However, this mostly reflects the existing complexity in the behavior of arithmetic types. Relatively few design principles govern these rules: 1. A `fixed_point` should follow the same behavior as `T` to the greatest extend practical, reflecting the facts that: a) all integers are fixed-point — rather than floating-point types and b) integer arithmetic generally provides the best efficiency and performance characteristics. 2. In situations where a trade-off between overflow and underflow must be made, the design guards against underflow. This follows from principle #1. Far more operations can cause overflow and users are generally more wart of it. And detection/handling of overflow is an orthogonal concern which is best implemented using a custom numeric type such as the `safe_integer` and `elastic_integer` types discussed in [\[P0554\]](http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2017/p0554r0.html#componentization). ### Named Arithmetic Functions The following named function templates can be used as alternatives to arithmetic operators, `*` and `/`. template constexpr auto multiply(const Lhs& lhs, const Rhs& rhs); template constexpr auto divide(const Lhs& lhs, const Rhs& rhs); They eschew machine-friendly integer promotion in favor of custom widening rules that place conciseness and correctness before raw performance. Multiplying two 8-bit values does not necessarily produce an int-sized result: auto f = fixed_point{15.9375}; auto p = multiply(f, f); // p === fixed_point{254.00390625} The arithmetic operators shield the user from none of the pitfalls of fixed-point arithmetic. For example, naive use of `*` can easily lead to surprising results. auto f = fixed_point{15.9375}; auto p = f * f; // p === fixed_point{0} In contrast, the `multiply` function returns appropriately widened results. It does a better job at avoiding unnecessary narrowing and catastrophic information loss. auto f = fixed_point{15.9375}; auto p = multiply(f, f); // p === fixed_point{254.00390625} Function, `divide`, performance a similar job. It follows rules laid out in [\[P0106\]](http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2015/p0106r0.html). In doing so, it performs division in a manner which may be less surprising to users who are familiar with floating-point division. constexpr auto n = fixed_point{1}; constexpr auto d = fixed_point{2}; // information appears to be lost by division operator constexpr auto q1 = n / d; static_assert(is_same_v>); static_assert(q1 == 0); // but divide preserves accurate results where practical constexpr auto q2 = divide(n, d); static_assert(is_same_v>); static_assert(q2 == 0.5); ### Alternative Types for `Rep` Using built-in integral types as the default underlying representation minimizes certain costs: * many fixed-point operations are as efficient as their integral equivalents; * compile-time complexity is kept relatively low and * the behavior of fixed-point types should cause few surprises. However, this choice also brings with it many of the deficiencies of built-in types. For example: * the typical rounding behavior is distinct for: * conversion from floating-point types; * right shift and * divide operations; * all of these rounding behaviors cause drift and propagate error; * overflow, underflow and flush are handled silently with wrap-around or undefined behavior; * divide-by-zero similarly results in undefined behavior and * the range of values is limited by the largest type: `long long int`. The effort involved in addressing these deficiencies is non-trivial and on-going (for example [\[P0105\]](http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2015/p0105r0.html)). As solutions are made available, it should become easier to define custom integral types which address concerns surrounding robustness and correctness. How to combine such numeric types is the topic of [\[P0554\]](http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2017/p0554r0.html), **Composition of Arithmetic Types**. #### Required Specializations For a type to be suitable as parameter, `Rep`, of `fixed_point`, it must meet the following requirements: * it must have specialized the following existing standard library types: * `numeric_limits` * `make_signed` and `make_unsigned` * it must have specialized the following proposed standard library types as described in [\[P0675\]](http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2017/p0675r0.html): * `num_digits` and `set_num_digits`, * `to_rep`, `from_rep` and `from_value`. Note that `make_signed` and `make_unsigned` must not be specialized for custom types. Unless this rule can be relaxed, some equivalent mechanism must be introduced in order for custom types to be used with `fixed_point<>`. One possibility is the addition of `numeric_limits<>::signed` and `numeric_limits<>::unsigned` type aliases. ### Example The following function, `magnitude`, calculates the magnitude of a 3-dimensional vector. template constexpr auto magnitude(Fp x, Fp y, Fp z) { return sqrt(x*x+y*y+z*z); } And here is a call to `magnitude`. auto m = magnitude( fixed_point(1), fixed_point(4), fixed_point(9)); // m === fixed_point{9.8994948863983154} ## V. Technical Specification ### Header \ Synopsis namespace std { template class fixed_point; // for each unary arithmetic, comparison, logic and bitwise operator, @ template constexpr auto operator@( const fixed_point & rhs); // for each binary arithmetic, comparison, logic and bitwise operator, @ // (and for named functions, multiply and divide) template constexpr auto operator@( const fixed_point & lhs, const fixed_point & rhs); template ::is_iec559>> constexpr auto operator@( const fixed_point & lhs, const RhsFloat & rhs); template ::is_iec559>> constexpr auto operator@( const LhsFloat & lhs, const fixed_point & rhs); template ::is_integer>> constexpr auto operator@( const fixed_point & lhs, const RhsInteger & rhs); template ::is_integer>> constexpr auto operator@( const LhsInteger & lhs, const fixed_point & rhs); template constexpr auto operator@( const fixed_point & lhs, constant); template constexpr auto operator@( constant, const fixed_point & rhs); // for each arithmetic, comparison, logic and bitwise compound assignment operator, @= template constexpr auto operator@=( fixed_point & lhs, const fixed_point & rhs); template ::is_iec559>> constexpr auto operator@=( fixed_point & lhs, const RhsFloat & rhs); template ::is_iec559>> constexpr auto operator@=( LhsFloat & lhs, const fixed_point & rhs); template ::is_integer>> constexpr auto operator@=( fixed_point & lhs, const RhsInteger & rhs); template ::is_integer>> constexpr auto operator@=( LhsInteger & lhs, const fixed_point & rhs); template constexpr auto operator@=( fixed_point & lhs, constant); } #### `fixed_point<>` Class Template ``` c++ template class fixed_point { public: using rep = Rep; constexpr static int exponent; constexpr fixed_point(); template constexpr fixed_point(fixed_point const&); template constexpr fixed_point(constant); template::is_integer, int> Dummy = 0> constexpr fixed_point(S const&); template::is_iec559, int> Dummy = 0> constexpr fixed_point(S); template::is_integer, int> Dummy = 0> constexpr fixed_point& operator=(S); template::is_iec559, int> Dummy = 0> constexpr fixed_point& operator=(S); template constexpr fixed_point& operator=(fixed_point const&); template::is_integer, int> Dummy = 0> explicit constexpr operator S() const; template::is_iec559, int> Dummy = 0> explicit constexpr operator S() const; }; ``` ## VI. Open Issues ### Library Support Because the aim is to provide an alternative to existing arithmetic types which are supported by the standard library, it is conceivable that a future proposal might specialize existing class templates and overload existing functions. Possible candidates for overloading include the functions defined in \ and a templated specialization of `numeric_limits`. A new type trait, `is_fixed_point`, would also be useful. While `fixed_point` is intended to provide drop-in replacements to existing built-ins, it may be preferable to deviate slightly from the behavior of certain standard functions. For example, overloads of functions from \ will be considerably less concise, efficient and versatile if they obey rules surrounding error cases. In particular, the guarantee of setting `errno` in the case of an error prevents a function from being defined as pure. This highlights a wider issue surrounding the adoption of the functional approach and compile-time computation that is beyond the scope of this document. One suggested addition is a specialization of `std::complex`. This would take the form: template class complex>; This type's arithmetic operators would differ from existing specializations because `fixed_point<>` operators often return results of a different type to their operands. Hence signatures such as ```c+ template complex operator*( const complex& lhs, const complex& rhs); ``` would need to be replaced with: ```c+ template auto operator*( const complex& lhs, const complex& rhs); ``` ### Different Division Strategies Integer and floating-point types solve division in fundamentally different ways. This poses a problem for the unwary user of `fixed_point` who may see the radix point and assume that `fixed_point` division will behave the same as floating-point. For instance, almost 50% of all integer and `fixed_point` division operations contain a numerator greater than the denominator, resulting in a value of zero. And where both operands have the same exponent, the result will have an exponent of zero. The `divide` function answers the needs of users expecting results to contain a number of integer and fractional digits complementing to those of the operands. However, this does not stop the behavior of the division operator (`/`) from being a source of surprise. One reason for not giving the division operator the same behavior as `divide` is that results will vary between different platforms depending on the width of types such as `int` and `long`. This is not a problem for types such as `elastic_integer` ([\[P0554\]](http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2017/p0554r0.html#componentization)) which explicitly represents the number of bits in its type. It is proposed that specialization, `fixed_point, E>`, have its own division operator whose behavior closely resembles that of `divide`. ### Template Parameter Order It is quite possible that the order of the two template parameters of `fixed_point` are the wrong way around and should be: template class fixed_point; While being able to express `fixed_point` reinforces the fact that integers are merely fixed-point types with radix point fixed at zero, the second parameter, `Exponent` is perhaps more important to specify. ### Non-Binary Radixes Interest in decimal fixed-point arithmetic has been observed. It seems plausible that a general-purpose type could support both binary and decimal fixed-point types as follows: template class basic_fixed_point; template using fixed_point = basic_fixed_point; template using decimal_fixed_point = basic_fixed_point; This naming scheme imitates `basic_string` in order to illustrate a similar pattern. Further investigation needs to be conducted in order to ascertain whether this break-down can maintain the same level of efficiency. ### Extended Comparison Range Comparison operations between two `fixed_point` operands require that they both have the same exponent. When they do not, conversion takes place to ensure they do. Unfortunately, if the difference in exponents is too great, the conversion may cause an out-of-bounds condition. However, where two operands have bits whose values are in ranges that do not overlap, it may not be necessary to perform a conversion which results in out-of-range results: a result that ensures they continue to not overlap may be sufficient. For example, static_assert(fixed_point{0} < fixed_point{4.e38}); requires that the right-hand operand be converted to `fixed_point`. This will result in the underlying integer being scaled up by 1000 bits, resulting in undefined behavior and/or a flushed value. But in this case, it only needed to be scaled by 8 bits in order for none of its bit values to overlap with those of the left-hand operand. ### Extensions to Exponent Parameter The possibility of scaling by other than an exponent has been discussed previously [\[future\]](https://groups.google.com/a/isocpp.org/forum/#!search/fixed_point/std-proposals/nK2EsdEf20A/LWmGn-GhAwAJ). It is likely that `fixed_point` is just one example of a more general numeric type, `scaled`: // a numeric type template class scaled; // a member of concept, "scale" template class power; // fixed_point as a numeric type scaled by powers of 2 template using fixed_point = scaled>; This approach separates two concerns currently combined in `fixed_point`: 1. using an existing number type to represent a new number type and 2. applying a scaling factor to the existing number. In this dichotomy, `scaled` holds onto a member variable of type, `Rep`, while `power` is stateless and provides an API which converts to and from the `Rep` type through function parameters. `power` also provides arithmetic support. Alternatives to `power` would include: * existing class, `ratio` (with additional arithmetic support) * units (containing static dimension information) * rounding and overflow-handling facilities * bounded integer * unit scalar (in the range [0, 1] or [-1, 1]) This design is a matter for future experimentation but it has immediate consequences for the API of `fixed_point`. ### Disable Addition/Subtraction if Exponents are Different When `fixed_point` operands of different exponent values are added and subtracted, one of them must first be scaled. This may represent an unexpected performance regression to some users. It might be clearer if the user is force to align the operands explicitly: auto l = fixed_point{0x55}, r = fixed_point{0xAA} // stop this from compiling auto sum = l + r; // force user to pick a common exponent auto sum = l + fixed_point{r}; ### Named Functions Functions, `multiply` and `divide` are of limited utility. They can be implemented by the user using casts. In the other direction, `add` and `subtract` could be useful additions. They could ensure that operations between numbers with vastly different exponents did not result in a flushed value. Q: Are `multiply` and `divide` worthwhile? Q: Should `add` and `subtract` be defined also? ## VII. Prior Art Many examples of fixed-point support in C and C++ exist. While almost all of them aim for low run-time cost and expressive alternatives to raw integer manipulation, they vary greatly in detail and in terms of their interface. One especially interesting dichotomy is between solutions which offer a discrete selection of fixed-point types and libraries which contain a continuous range of exponents through type parameterization. ### N1169 One example of the former is found in proposal N1169 [\[N1169\]](http://www.open-std.org/JTC1/SC22/WG14/www/docs/n1169.pdf), the intent of which is to expose features found in certain embedded hardware. It introduces a succinct set of language-level fixed-point types and impose constraints on the number of integer or fractional digits each can possess. As with all examples of discrete-type fixed-point support, the limited choice of exponents is a considerable restriction on the versatility and expressiveness of the API. Nevertheless, it may be possible to harness performance gains provided by N1169 fixed-point types through explicit template specialization. This is likely to be a valuable proposition to potential users of the library who find themselves targeting platforms which support fixed-point arithmetic at the hardware level. ### P0106 There are many other C++ libraries available which fall into the latter category of continuous-range fixed-point arithmetic [\[mizvekov\]](https://github.com/mizvekov/fp) [\[schregle\]](http://www.codeproject.com/Articles/37636/Fixed-Point-Class) [\[viboes\]](https://github.com/viboes/fixed_point). In particular, an existing library proposal by Lawrence Crowl, P0106 [\[P0106\]](http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2015/p0106r0.html) (formerly N3352), aims to achieve very similar goals through similar means and warrants closer comparison than N1169. P0106 introduces four class templates covering the quadrant of signed versus unsigned and fractional versus integer numeric types. It is intended to replace built-in types in a wide variety of situations and accordingly, is highly compile-time configurable in terms of how rounding and overflow are handled. Parameters to these four class templates include the storage in bits and - for fractional types - the resolution. The `fixed_point` class template could probably - with a few caveats - be generated using the two fractional types, `nonnegative` and `negatable`, replacing the `Rep` parameter with the integer bit count of `Rep`, specifying `fastest` for the rounding mode and specifying `undefined` as the overflow mode. However, `fixed_point` more closely and concisely caters to the needs of users who already use integer types and simply desire a more concise, less error-prone form. It more closely follows the four design aims of the library and - it can be argued - more closely follows the spirit of the standard in its pursuit of zero-cost abstraction. Some aspects of the design of the P0106 API which back up these conclusion are that: * the result of arithmetic operations closely resemble the `trunc_` function templates and are potentially more costly at run-time; * the nature of the range-specifying template parameters - through careful framing in mathematical terms - abstracts away valuable information regarding machine-critical type size information; * the breaking up of duties amongst four separate class templates introduces four new concepts and incurs additional mental load for relatively little gain while further detaching the interface from vital machine-level details and * the absence of the most negative number from signed types reduces the capacity of all types by one. The added versatility that the P0106 API provides regarding rounding and overflow handling are of relatively low priority to users who already bear the scars of battles with raw integer types. Nevertheless, providing them as options to be turned on or off at compile time is an ideal way to leave the choice in the hands of the user. Many high-performance applications - in which fixed-point is of potential value - favor run-time checks during development which are subsequently deactivated in production builds. The P0106 interface is highly conducive to this style of development. The design proposed in this paper aims to achieve similar results by composing fixed-point types from custom integral types. ## VIII. Acknowledgements SG6: Lawrence Crowl SG14: Guy Davidson, Michael Wong Contributors: Ed Ainsley, Billy Baker, Lance Dyson, Marco Foco, Mathias Gaunard, Clément Grégoire, Nicolas Guillemot, Kurt Guntheroth, Matt Kinzelman, Joël Lamotte, Sean Middleditch, Paul Robinson, Patrice Roy, Peter Schregle, Ryhor Spivak ## IX. Revisions This paper revises [P0037R3](http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2016/p0037r3.html): * removed mention of `width` and `set_width` * rewritten description of `Rep` template parameter * added sections, **Access to `Rep` Value** and **Class Template Deduction** * removed `make_fixed` and `make_ufixed` function templates * rewritten **Operator Overloads** section, renamed **Operators** and included `constant` operators * removed sections, **Overflow** and **Underflow** * removed `add` and `subtract` function templates * reversed the roles of `operator/` and `divide` * replaced section on composability with link to [\[P0554\]](http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2017/p0554r0.html) * replaced reference to [\[P0381\]](http://johnmcfarlane.github.io/fixed_point/papers/p0381r1.html) with reference to [\[P0675\]](https://github.com/johnmcfarlane/papers/blob/master/wg21/p0675r0.md) * revised synopsis * renamed section **Future Issues** to **Open Issues** and added sections, * **Different Division Strategies**, **Template Parameter Order**, **Disable Addition/Subtraction if Exponents are Different**, **Named Functions**, **Extended Comparison Range** and remove sections * **Compile-Time Bit-Shift Operations**, **Alternative Return Type Policies**, * removed section, **References**, moving links into document body * rewrote **Appendix 1: Reference Implementation** referencing [\[github\]](https://github.com/johnmcfarlane/cnl) * formatting changes intended to make markdown more readable as plain text ## XI. Appendix 1: Reference Implementation An in-development implementation of the fixed_point class template and its essential supporting functions and types is available [\[github\]](https://github.com/johnmcfarlane/cnl). ## XII. Appendix 2: Performance Despite a focus on usable interface and direct translation from integer-based fixed-point operations, there is an overwhelming expectation that the source code result in minimal instructions and clock cycles. A few preliminary numbers are presented to give a very early idea of how the API might perform. Some notes: * A few test functions were run, ranging from single arithmetic operations to basic geometric functions, performed against integer, floating-point and fixed-point types for comparison. * Figures were taken from a single CPU, OS and compiler, namely: * Debian clang version 3.5.0-10 (tags/RELEASE_350/final) (based on LLVM 3.5.0) * Target: x86_64-pc-linux-gnu * Thread model: posix * Fixed inputs were provided to each function, meaning that branch prediction rarely fails. Results may also not represent the full range of inputs. * Details of the test harness used can be found in the source project mentioned in Appendix 1; * Times are in nanoseconds; * Code has not yet been optimized for performance. ### Types Where applicable various combinations of integer, floating-point and fixed-point types were tested with the following identifiers: * `uint8_t`, `int8_t`, `uint16_t`, `int16_t`, `uint32_t`, `int32_t`, `uint64_t` and `int64_t` built-in integer types; * `float`, `double` and `long double` built-in floating-point types; * s3:4, u4:4, s7:8, u8:8, s15:16, u16:16, s31:32 and u32:32 format fixed-point types. ### Basic Arithmetic Plus, minus, multiplication and division were tested in isolation using a number of different numeric types with the following results: name cpu_time add(float) 1.78011 add(double) 1.73966 add(long double) 3.46011 add(u4_4) 1.87726 add(s3_4) 1.85051 add(u8_8) 1.85417 add(s7_8) 1.82057 add(u16_16) 1.94194 add(s15_16) 1.93463 add(u32_32) 1.94674 add(s31_32) 1.94446 add(int8_t) 2.14857 add(uint8_t) 2.12571 add(int16_t) 1.9936 add(uint16_t) 1.88229 add(int32_t) 1.82126 add(uint32_t) 1.76 add(int64_t) 1.76 add(uint64_t) 1.83223 sub(float) 1.96617 sub(double) 1.98491 sub(long double) 3.55474 sub(u4_4) 1.77006 sub(s3_4) 1.72983 sub(u8_8) 1.72983 sub(s7_8) 1.72983 sub(u16_16) 1.73966 sub(s15_16) 1.85051 sub(u32_32) 1.88229 sub(s31_32) 1.87063 sub(int8_t) 1.76 sub(uint8_t) 1.74994 sub(int16_t) 1.82126 sub(uint16_t) 1.83794 sub(int32_t) 1.89074 sub(uint32_t) 1.85417 sub(int64_t) 1.83703 sub(uint64_t) 2.04914 mul(float) 1.9376 mul(double) 1.93097 mul(long double) 102.446 mul(u4_4) 2.46583 mul(s3_4) 2.09189 mul(u8_8) 2.08 mul(s7_8) 2.18697 mul(u16_16) 2.12571 mul(s15_16) 2.10789 mul(u32_32) 2.10789 mul(s31_32) 2.10789 mul(int8_t) 1.76 mul(uint8_t) 1.78011 mul(int16_t) 1.8432 mul(uint16_t) 1.76914 mul(int32_t) 1.78011 mul(uint32_t) 2.19086 mul(int64_t) 1.7696 mul(uint64_t) 1.79017 div(float) 5.12 div(double) 7.64343 div(long double) 8.304 div(u4_4) 3.82171 div(s3_4) 3.82171 div(u8_8) 3.84 div(s7_8) 3.8 div(u16_16) 9.152 div(s15_16) 11.232 div(u32_32) 30.8434 div(s31_32) 34 div(int8_t) 3.82171 div(uint8_t) 3.82171 div(int16_t) 3.8 div(uint16_t) 3.82171 div(int32_t) 3.82171 div(uint32_t) 3.81806 div(int64_t) 10.2286 div(uint64_t) 8.304 Among the slowest types are `long double`. It is likely that they are emulated in software. The next slowest operations are fixed-point multiply and divide operations - especially with 64-bit types. This is because values need to be promoted temporarily to double-width types. This is a known fixed-point technique which inevitably experiences slowdown where a 128-bit type is required on a 64-bit system. Here is a section of the disassembly of the s15:16 multiply call: 30: mov %r14,%rax mov %r15,%rax movslq -0x28(%rbp),%rax movslq -0x30(%rbp),%rcx imul %rax,%rcx shr $0x10,%rcx mov %ecx,-0x38(%rbp) mov %r12,%rax 4c: movzbl (%rbx),%eax cmp $0x1,%eax ↓ jne 68 54: mov 0x8(%rbx),%rax lea 0x1(%rax),%rcx mov %rcx,0x8(%rbx) cmp 0x38(%rbx),%rax ↑ jb 30 The two 32-bit numbers are multiplied together and the result shifted down - much as it would if raw `int` values were used. The efficiency of this operation varies with the exponent. An exponent of zero should mean no shift at all. ### 3-Dimensional Magnitude Squared A fast `sqrt` implementation has not yet been tested with `fixed_point`. (The naive implementation takes over 300ns.) For this reason, a magnitude-squared function is measured, combining multiply and add operations: template constexpr FP magnitude_squared(const FP & x, const FP & y, const FP & z) { return x * x + y * y + z * z; } Only real number formats are tested: float 2.42606 double 2.08 long double 4.5056 s3_4 2.768 s7_8 2.77577 s15_16 2.752 s31_32 4.10331 Again, the size of the type seems to have the largest impact. ### Circle Intersection A similar operation includes a comparison and branch: template bool circle_intersect_generic(Real x1, Real y1, Real r1, Real x2, Real y2, Real r2) { auto x_diff = x2 - x1; auto y_diff = y2 - y1; auto distance_squared = x_diff * x_diff + y_diff * y_diff; auto touch_distance = r1 + r2; auto touch_distance_squared = touch_distance * touch_distance; return distance_squared <= touch_distance_squared; } float 3.46011 double 3.48 long double 6.4 s3_4 3.88 s7_8 4.5312 s15_16 3.82171 s31_32 5.92 Again, fixed-point and native performance are comparable.