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zircon/system/ulib/ffl/README.md

Fuchsia Fixed-Point Library (FFL)

Introduction

FFL is a C++ template library for fixed-point arithmetic. The library is primarily intended to support the Zircon kernel scheduler however, it is sufficiently general to be useful wherever fixed-point computations are needed.

FFL is motivated by the following requirements:

  • Availability: Fixed-point support is not yet ratified in the standard library. We need a solution today.
  • Dependency: Many alternatives require additional dependencies. We prefer to depend only on the standard library.
  • Rounding: Many alternatives, including the proposal for the standard library, have poor or ill-defined rounding behavior. We need well-defined rounding with reasonable general-purpose stability, such as convergent rounding.

General Usage

The main user-facing type in FFL is the value template type ffl::Fixed<typename Integer, size_t FractionalBits>. This template accepts an integer type for the underlying value and the number of bit to use to represent the fractional component. Naturally, the range of the integer component of the fixed-point value is defined by the difference between the number of bits of the underlying integer type and the number of bits reserved for the fractional part.

ffl::Fixed behaves similarly to plain integers. The type supports most of the same arithmetic operators: addition, subtraction, negation, multiplication, and division, as well as all of the comparison operators.

#include <ffl/fixed.h>

using ffl::Fixed;

Fixed<int32_t, 31> UnitaryRatio(Fixed<int32_t, 0> a, Fixed<int32_t, 0> b) {
    if (a > b)
        return b / a;
    else
        return a / b;
}

Fixed<uint8_t, 0> Blend(Fixed<uint8_t, 0> color0, Fixed<uint8_t, 0> color1, Fixed<uint8_t, 8> alpha) {
    return alpha * color0 + (Fixed<uint8_t, 8>{1} - alpha) * color1;
}

Expressions and Managing Precision

FFL supports arithmetic and comparisons with mixed precisions. These operations may consider both the source and destination precisions at compile time to select an appropriate strategy for intermediate computations.

In order to consider the destination precision, the evaluation of an expression involving ffl::Fixed values is deferred until the expression is assigned to a ffl::Fixed variable. To facilitate this deferred evaluation, the arithmetic operators return instances of the template type ffl::Expression, which captures the arithmetic operation and the arguments involved. The arguments may be instances of ffl::Fixed, plain integers, or other instances of ffl::Expression returned by other operators and utility functions. With this approach, compound expressions result in expression trees that follow the C++ order of operations.

In many cases the use of expression trees is transparent to the user, as in the following example:

#include <ffl/fixed.h>

using ffl::Fixed;

struct Point2d {
    Fixed<int16_t, 0> x;
    Fixed<int16_t, 0> y;
};

Point2d LinearInterpolate(Point2d p0, Point2d p1, Fixed<int32_t, 16> t) {
    return {p0.x + t * (p1.x - p0.x), p0.y + t * (p1.y - p0.y)};
}

In this example the arithmetic expressions and assignments happen together and there is no need to consider the intermediate Expression objects.

In some cases it is useful to be aware of the intermediate Expression objects. The following example uses intermediate expressions to make the overall computation more readable:

#include <ffl/fixed.h>

using ffl::Fixed;

// TODO

Mixed Precision

FFL uses the following rules when performing mixed precision arithmetic:

  • Addition and subtraction convert to the greatest precision and least resolution of the two operands before computing an intermediate result.
  • Multiplication produces an intermediate result with precision and resolution sufficient to hold the sum of both the fractional and integral bit depths of the operands.
  • Division produces an intermediate result with the resolution of the target format.

Comparisons convert to the least resolution of the two operands before performing the comparison. However, when comparing a fixed-point value with a plain integer, the values are converted to an intermediate type with sufficient precision and the resolution of the fixed-point argument.

Intermediate Values and Saturation

Saturation is one important difference between fixed-point arithmetic in FFL and regular integer arithmetic. Regular integer arithmetic over or underflows when the result exceeds the range of the integral type. In contrast, FFL uses intermediate values with sufficient range for the computation. When an intermediate value is finally assigned to a fixed-point variable the value is clamped to precision of the destination type.

Coercing Resolution

Some arithmetic operations take the target resolution into account when computing intermediate values (only division at the time of this writing). The target resolution may be influenced using the ToResolution<FractionalBits>() utility function. This utility functions by inserting a resolution node into the expression tree at the point of invocation; deeper nodes that consider target resolution will consider the resolution given by this node instead of the final resolution.

#include <ffl/fixed.h>

using ffl::Fixed;
using ffl::Round;
using ffl::ToResolution;

constexpr int32_t Divide(int32_t numerator, int32_t denominator) {
    const Fixed<int32_t, 0> fixed_numerator{numerator};
    const Fixed<int32_t, 0> fixed_denominator{denominator};

    // Perform division with 2bit fractional resolution for optimum convergent
    // rounding of the quotient.
    return Round<int32_t>(ToResolution<2>(fixed_numerator / fixed_denominator));
}