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  2. Karatsuba algorithm - Wikipedia

    en.wikipedia.org/wiki/Karatsuba_algorithm

    In a computer with a full 32-bit by 32-bit multiplier, for example, one could choose B = 2 31 and store each digit as a separate 32-bit binary word. Then the sums x 1 + x 0 and y 1 + y 0 will not need an extra binary word for storing the carry-over digit (as in carry-save adder), and the Karatsuba recursion can be applied until the numbers to ...

  3. Saturation arithmetic - Wikipedia

    en.wikipedia.org/wiki/Saturation_arithmetic

    Saturation arithmetic for integers has also been implemented in software for a number of programming languages including C, C++, such as the GNU Compiler Collection, [2] LLVM IR, and Eiffel. Support for saturation arithmetic is included as part of the C++26 Standard Library. This helps programmers anticipate and understand the effects of ...

  4. Integer overflow - Wikipedia

    en.wikipedia.org/wiki/Integer_overflow

    In particular, multiplying or adding two integers may result in a value that is unexpectedly small, and subtracting from a small integer may cause a wrap to a large positive value (for example, 8-bit integer addition 255 + 2 results in 1, which is 257 mod 2 8, and similarly subtraction 0 − 1 results in 255, a two's complement representation ...

  5. Multiplication algorithm - Wikipedia

    en.wikipedia.org/wiki/Multiplication_algorithm

    To form the product of two 8-bit integers, for example, the digital device forms the sum and difference, looks both quantities up in a table of squares, takes the difference of the results, and divides by four by shifting two bits to the right. For 8-bit integers the table of quarter squares will have 2 9 −1=511 entries (one entry for the ...

  6. GNU Multiple Precision Arithmetic Library - Wikipedia

    en.wikipedia.org/wiki/GNU_Multiple_Precision...

    GNU Multiple Precision Arithmetic Library (GMP) is a free library for arbitrary-precision arithmetic, operating on signed integers, rational numbers, and floating-point numbers. [3] There are no practical limits to the precision except the ones implied by the available memory (operands may be of up to 2 321 bits on 32-bit machines and 2 37 ...

  7. Computational complexity of mathematical operations - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity...

    Here, complexity refers to the time complexity of performing computations on a multitape Turing machine. [1] See big O notation for an explanation of the notation used. Note: Due to the variety of multiplication algorithms, () below stands in for the complexity of the chosen multiplication algorithm.

  8. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    On a typical computer system, a double-precision (64-bit) binary floating-point number has a coefficient of 53 bits (including 1 implied bit), an exponent of 11 bits, and 1 sign bit. Since 2 10 = 1024, the complete range of the positive normal floating-point numbers in this format is from 2 −1022 ≈ 2 × 10 −308 to approximately 2 1024 ≈ ...

  9. Binary multiplier - Wikipedia

    en.wikipedia.org/wiki/Binary_multiplier

    When the +1 from the two's complement negation for p7 in bit position 0 (LSB) and all the −1's in bit columns 7 through 14 (where each of the MSBs are located) are added together, they can be simplified to the single 1 that "magically" is floating out to the left.