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Mesh data is usually stored using 32-bit single-precision floats for the vertices, however in some situations it is acceptable to reduce the precision to only 16-bit half-precision, requiring only half the storage at the expense of some precision. Mesh quantization can also be done with 8-bit or 16-bit fixed precision depending on the requirements.
This format uses a binary significand from 0 to 10 p −1. For example, the Decimal32 significand can be up to 10 7 −1 = 9 999 999 = 98967F 16 = 1001 1000100101 1001111111 2. While the encoding can represent larger significands, they are illegal and the standard requires implementations to treat them as 0, if encountered on input.
That is, a 16-bit signed (two's complement) integer, that is implicitly multiplied by the scaling factor 2 −12. In particular, when n is zero, the numbers are just integers. If m is zero, all bits except the sign bit are fraction bits; then the range of the stored number is from −1.0 (inclusive) to +1.0 (exclusive).
For example, decimal 0.1 cannot be represented in binary exactly, only approximated. ... 0 01111111 00000000000000000000001 2 = 3f80 0001 16 = 1 + 2 −23 ≈ 1. ...
This format is a shortened (16-bit) version of the 32-bit IEEE 754 single-precision floating-point format (binary32) with the intent of accelerating machine learning and near-sensor computing. [3] It preserves the approximate dynamic range of 32-bit floating-point numbers by retaining 8 exponent bits , but supports only an 8-bit precision ...
A decimal number with d digits requires 1 / 2 (d+1) bytes of storage space. For example, a 4-byte (32-bit) word can hold seven decimal digits plus a sign and can represent values ranging from ±9,999,999.
Given the hexadecimal representation 3FD5 5555 5555 5555 16, Sign = 0 Exponent = 3FD 16 = 1021 Exponent Bias = 1023 (constant value; see above) Fraction = 5 5555 5555 5555 16 Value = 2 (Exponent − Exponent Bias) × 1.Fraction – Note that Fraction must not be converted to decimal here = 2 −2 × (15 5555 5555 5555 16 × 2 −52) = 2 −54 ...
The value encoded is (−1) s ×10 q ×c. In both formats the range of possible values is identical, but they differ in how the significand c is represented. In the decimal encoding, it is encoded as a series of p decimal digits (using the densely packed decimal (DPD) encoding).