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INTLAB was used to develop other MATLAB-based libraries such as VERSOFT [5] and INTSOLVER, [6] and it was used to solve some problems in the Hundred-dollar, Hundred-digit Challenge problems. [ 7 ] INTLAB (Interval Laboratory)
For an ANSI/ISO compliant compiler, the minimum requirements for the specified ranges, that is, −(2 63 −1) [11] to 2 63 −1 for signed and 0 to 2 64 −1 for unsigned, [12] must be fulfilled; however, extending this range is permitted. [17] [18] This can be an issue when exchanging code and data between platforms, or doing direct hardware ...
Integer overflow can be demonstrated through an odometer overflowing, a mechanical version of the phenomenon. All digits are set to the maximum 9 and the next increment of the white digit causes a cascade of carry-over additions setting all digits to 0, but there is no higher digit (1,000,000s digit) to change to a 1, so the counter resets to zero.
In the base −2 representation, a signed number is represented using a number system with base −2. In conventional binary number systems, the base, or radix, is 2; thus the rightmost bit represents 2 0, the next bit represents 2 1, the next bit 2 2, and so on. However, a binary number system with base −2 is also possible.
The floor of x is also called the integral part, integer part, greatest integer, or entier of x, and was historically denoted [x] (among other notations). [2] However, the same term, integer part, is also used for truncation towards zero, which differs from the floor function for negative numbers. For n an integer, ⌊n⌋ = ⌈n⌉ = n.
In computer science, arbitrary-precision arithmetic, also called bignum arithmetic, multiple-precision arithmetic, or sometimes infinite-precision arithmetic, indicates that calculations are performed on numbers whose digits of precision are potentially limited only by the available memory of the host system.
The range of a double-double remains essentially the same as the double-precision format because the exponent has still 11 bits, [4] significantly lower than the 15-bit exponent of IEEE quadruple precision (a range of 1.8 × 10 308 for double-double versus 1.2 × 10 4932 for binary128).
For example, the smallest positive number that can be represented in binary64 is 2 −1074; contributions to the −1074 figure include the emin value −1022 and all but one of the 53 significand bits (2 −1022 − (53 − 1) = 2 −1074). Decimal digits is the precision of the format expressed in terms of an equivalent number of decimal digits.