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The advantage over 8-bit or 16-bit integers is that the increased dynamic range allows for more detail to be preserved in highlights and shadows for images, and avoids gamma correction. The advantage over 32-bit single-precision floating point is that it requires half the storage and bandwidth (at the expense of precision and range). [5]
The 16-bit word length thus became more common in the 1960s, especially on minicomputer systems. Early 16-bit computers (c. 1965–70) include the IBM 1130, [3] the HP 2100, [4] the Data General Nova, [5] and the DEC PDP-11. [6] Early 16-bit microprocessors, often modeled on one of the mini platforms, began to appear in the 1970s.
execute opcode, where opcode is either iload, fload, aload, lload, dload, istore, fstore, astore, lstore, dstore, or ret, but assume the index is 16 bit; or execute iinc, where the index is 16 bits and the constant to increment by is a signed 16 bit short (no name) cb-fd these values are currently unassigned for opcodes and are reserved for ...
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 floating-point variable can represent a wider range of numbers than a fixed-point variable of the same bit width at the cost of precision. A signed 32-bit integer variable has a maximum value of 2 31 − 1 = 2,147,483,647, whereas an IEEE 754 32-bit base-2 floating-point variable has a maximum value of (2 − 2 −23) × 2 127 ≈ 3.4028235 ...
In a move or convert operation, zero extension refers to setting the high bits of the destination to zero, rather than setting them to a copy of the most significant bit of the source. If the source of the operation is an unsigned number, then zero extension is usually the correct way to move it to a larger field while preserving its numeric ...
An Adler-32 checksum is obtained by calculating two 16-bit checksums A and B and concatenating their bits into a 32-bit integer. A is the sum of all bytes in the stream plus one, and B is the sum of the individual values of A from each step. At the beginning of an Adler-32 run, A is initialized to 1, B to 0.
When the data word is divided into 16-bit blocks, two 16-bit sums result and are combined into a 32-bit Fletcher checksum. Usually, the second sum will be multiplied by 2 16 and added to the simple checksum, effectively stacking the sums side-by-side in a 32-bit word with the simple checksum at the least significant end. This algorithm is then ...