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2.3434e−6 = 2.3434 × 10 −6 = 2.3434 × 0.000001 = 0.0000023434 The advantage of this scheme is that by using the exponent we can get a much wider range of numbers, even if the number of digits in the significand, or the "numeric precision", is much smaller than the range.
The base determines the fractions that can be represented; for instance, 1/5 cannot be represented exactly as a floating-point number using a binary base, but 1/5 can be represented exactly using a decimal base (0.2, or 2 × 10 −1). However, 1/3 cannot be represented exactly by either binary (0.010101...) or decimal (0.333...), but in base 3 ...
One of the few RISC instruction sets to directly support decimal is IBM's Power ISA, which added support for IEEE 754-2008 decimal floating-point starting with Power ISA 2.05. Decimal integer support had been part of their mainframe line, and as part of the broader effort to merge the iSeries and zSeries decimal arithmetic was added to the ...
The page had already had a merge, but since then I moved it here. Paper.io 2 was the merge by the way. Paper.io is now a series for this article. Paper.io 2's draft I changed to redirect to the draft paper.io, so it goes here. It's messy, so check the revision history for help. I'm the same dude(I didn't make the paper.io 2 draft).
For example, in duodecimal, 1 / 2 = 0.6, 1 / 3 = 0.4, 1 / 4 = 0.3 and 1 / 6 = 0.2 all terminate; 1 / 5 = 0. 2497 repeats with period length 4, in contrast with the equivalent decimal expansion of 0.2; 1 / 7 = 0. 186A35 has period 6 in duodecimal, just as it does in decimal. If b is an integer base ...
By default, 1/3 rounds up, instead of down like double precision, because of the even number of bits in the significand. The bits of 1/3 beyond the rounding point are 1010... which is more than 1/2 of a unit in the last place. Encodings of qNaN and sNaN are not specified in IEEE 754 and implemented differently on different processors.
Thus only 112 bits of the significand appear in the memory format, but the total precision is 113 bits (approximately 34 decimal digits: log 10 (2 113) ≈ 34.016) for normal values; subnormals have gracefully degrading precision down to 1 bit for the smallest non-zero value. The bits are laid out as:
For comparison, the same number in decimal representation: 1.125 × 2 3 (using decimal representation), or 1.125B3 (still using decimal representation). Some calculators use a mixed representation for binary floating point numbers, where the exponent is displayed as decimal number even in binary mode, so the above becomes 1.001 b × 10 b 3 d or ...