# Storing non-negative floating point values

1

Is there an efficient way to store non-negative floating point values using the existing `float32` and `float64` formats?

Imagine the default `float32` behaviour which allows negative/positive:

``````val = bytes.readFloat32();
``````

Is it possible to allow for greater positive values if negative values are not necessary?

``````val = bytes.readFloat32() + 0xFFFFFFFF;
``````

Edit: Essentially when I know I'm storing only positive values, the float format could be modified a bit to allow for greater range or precision for the same amount of bits.

Eg. The `float32` format is defined as 1 bit for sign, 8 bits for exponent, 23 bits for fraction

What if I don't need the sign bit, can we have 8 bits for exponent, 24 bits for fraction to give greater precision for the same 32 bits?

c++
floating-point
unsigned
primitive-types
asked on Stack Overflow Apr 14, 2012 by Robin Rodricks • edited Nov 17, 2020 by phuclv

3

Floating-point numbers (`float32` and `float64`) have an explicit sign bit. The equivalent of unsigned integers doesn't exist for floating-point numbers.

So there is no easy way to double the range of positive floating-point numbers.

answered on Stack Overflow Apr 14, 2012 by Jeffrey Sax
2

You can extend the range/accuracy in many ways using other numeric representations. The intent won't be clear, and the performance will typically be poor if you want the range and accuracy of `float` or `double` using another numeric representation (of equal size).

Just stick with `float` or `double` unless performance/storage is very very important, and you can represent your values well (or better!) using another numeric representation.

answered on Stack Overflow Apr 14, 2012 by justin • edited Apr 14, 2012 by justin
0

There's almost no support for unsigned float in hardware so you won't have such off-the-shelf feature but you can still have quite efficient unsigned float by storing the least significant bit in the sign bit. This way you can utilize hardware available float support instead of writing a software float solution. To do that you can

• manipulate it manually after each operation

This way you need some small correction to the lsb (A.K.A sign bit), for example 1 more long division step, or a 1-bit adder for the addition

• or by doing the math in higher precision if available

For example if the type is `float` you can do operations in `double` then cast back to `float` when storing

Here's a simple PoC implementation:

``````#include <cmath>
#include <cfenv>
#include <bit>
#include <type_traits>

// Does the math in double precision when hardware double is available
#define HAS_NATIVE_DOUBLE

class UFloat
{
public:
// =========== Constructors ===========
UFloat(float rhs = 0.0f) : value(rhs)
{
std::fesetround(FE_TOWARDZERO); // We'll round the value ourselves
#ifdef HAS_NATIVE_DOUBLE
static_assert(sizeof(float) < sizeof(double));
#endif
}
UFloat(double d) : UFloat(0.0f)
{
if (d < 0)
throw std::range_error("Value must be non-negative!");
uint64_t dbits = std::bit_cast<uint64_t>(d);
bool lsb = dbits & lsbMask;
dbits &= ~lsbMask; // turn off the lsb
d = std::bit_cast<double>(dbits);
value = lsb ? -(float)d : (float)d;
}
UFloat(const UFloat &rhs) : UFloat(rhs.value) {}

// =========== Operators ===========
UFloat &operator+=(const UFloat &rhs)
{
#ifdef HAS_NATIVE_DOUBLE
// Calculate in higher precision then round back
setValue((double)value + rhs.value);
#else
// Calculate the least significant bit manually

bool lhsLsb = std::signbit(value);
bool rhsLsb = std::signbit(rhs.value);
// Clear the sign bit to get the higher significant bits then get the sum
value = std::abs(value);
value += std::abs(rhs.value);
if (std::isfinite(value))
{
if (lhsLsb ^ rhsLsb) // Only one of the 2 least significant bits is 1
{
// The sum's least significant bit is 1, so we'll set its sign bit
value = -value;
}
else if (lhsLsb)
{
// Both least significant bits are 1s, so add the carry to the next bit
// The least significant bit of the sum is 0, so we don't change the sign bit
value = std::nextafter(value, INFINITY);
}
}
#endif
return *this;
}

UFloat &operator*=(const UFloat &rhs)
{
#ifdef HAS_NATIVE_DOUBLE
// Calculate in higher precision then round back
setValue((double)value * rhs.value);
#else
// Calculate the least significant bit manually

bool lhsLsb = std::signbit(value);
bool rhsLsb = std::signbit(rhs.value);

// Clear the sign bit to get the higher significant bits then get the product
float lhsMsbs = std::abs(value);
float rhsMsbs = std::abs(rhs.value);

// Suppose we have X.xPm with X: the high significant bits, x: the least significant one
// and m: the exponent. Same to Y.yPn
// X.xPm * Y.yPn = (X + 0.x)*2^m * (Y + 0.y)*2^n
//               = (X + x/2)*2^m * (Y + y/2)*2^n
//               = (X*Y + X*y/2 + Y*x/2 + x*y/4)*2^(m + n)
value = lhsMsbs * rhsMsbs; // X*Y
if (std::isfinite(value))
{
uint32_t rhsMsbsBits = std::bit_cast<uint32_t>(rhsMsb);
value += rhsMsbs*lhsLsb / 2; // X*y/2

uint32_t lhsMsbsBits = std::bit_cast<uint32_t>(lhsMsbs);
value += lhsMsbs*rhsLsb / 2; // Y*x/2

int lsb = (rhsMsbsBits | lhsMsbsBits) & 1; // the product's lsb
lsb += lhsLsb & rhsLsb;
if (lsb & 1)
value = -value; // set the lsb
if (lsb > 1)    // carry to the next bit
value = std::nextafter(value, INFINITY);
}
#endif

return *this;
}

UFloat &operator/=(const UFloat &rhs)
{
#ifdef HAS_NATIVE_DOUBLE
// Calculate in higher precision then round back
setValue((double)value / rhs.value);
#else
// Calculate the least significant bit manually
// Do just one more step of long division, since we only have 1 bit left to divide

throw std::runtime_error("Not Implemented yet!");
#endif

return *this;
}

double getUnsignedValue() const
{
if (!std::signbit(value))
{
return (double)value;
}
else
{
double result = std::abs(value);
uint64_t doubleValue;
memcpy(&doubleValue, &result, sizeof result);
doubleValue |= lsbMask; // turn on the least significant bit
memcpy(&result, &doubleValue, sizeof result);
return result;
}
}

private:
// The unsigned float value, with the least significant bit being stored in the sign bit
float value;

// the first bit after the normal mantissa bits
static const uint64_t lsbMask = 1ULL << (DBL_MANT_DIG - FLT_MANT_DIG - 1);
void setValue(double d)
{
auto bits = std::bit_cast<std::uint64_t>(d); // get the bit pattern of the double value
bool lsb = bits & lsbMask;
bits &= ~lsbMask;                            // turn off the lsb to avoid rounding when converting to float
d = std::bit_cast<double>(bits);
value = (float)d;
if (lsb)
value = -value;
}
}
``````

Some more tuning may be necessary to get the correct lsb

Either way you'll need more operations than normal so this may only be good for big arrays where cache footprint is a concern. In that case I suggest to use this as a storage format only, like how FP16 is treated on most current architectures: there are only load/store instructions for it which expands to `float` or `double` and convert back. All arithmetic operations are done in `float` or `double` only

So the unsigned float should exist in memory only, and will be decoded to the full `double` on load. This way you work on the native `double` type and won't need the correction after each operator

answered on Stack Overflow Nov 17, 2020 by phuclv

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