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#### 15.3.2 Lehmer’s algorithm

Lehmer’s improvement of the Euclidean algorithms is based on the observation that the initial part of the quotient sequence depends only on the most significant parts of the inputs. The variant of Lehmer’s algorithm used in GMP splits off the most significant two limbs, as suggested, e.g., in “A Double-Digit Lehmer-Euclid Algorithm” by Jebelean (see References). The quotients of two double-limb inputs are collected as a 2 by 2 matrix with single-limb elements. This is done by the function `mpn_hgcd2`. The resulting matrix is applied to the inputs using `mpn_mul_1` and `mpn_submul_1`. Each iteration usually reduces the inputs by almost one limb. In the rare case of a large quotient, no progress can be made by examining just the most significant two limbs, and the quotient is computed using plain division.

The resulting algorithm is asymptotically O(N^2), just as the Euclidean algorithm and the binary algorithm. The quadratic part of the work are the calls to `mpn_mul_1` and `mpn_submul_1`. For small sizes, the linear work is also significant. There are roughly N calls to the `mpn_hgcd2` function. This function uses a couple of important optimizations:

• It uses the same relaxed notion of correctness as `mpn_hgcd` (see next section). This means that when called with the most significant two limbs of two large numbers, the returned matrix does not always correspond exactly to the initial quotient sequence for the two large numbers; the final quotient may sometimes be one off.
• It takes advantage of the fact the quotients are usually small. The division operator is not used, since the corresponding assembler instruction is very slow on most architectures. (This code could probably be improved further, it uses many branches that are unfriendly to prediction).
• It switches from double-limb calculations to single-limb calculations half-way through, when the input numbers have been reduced in size from two limbs to one and a half.

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