curve25519_dalek::backend::serial::scalar_mul::pippenger

Struct Pippenger

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pub struct Pippenger;
Available on crate feature alloc only.
Expand description

Implements a version of Pippenger’s algorithm.

The algorithm works as follows:

Let n be a number of point-scalar pairs. Let w be a window of bits (6..8, chosen based on n, see cost factor).

  1. Prepare 2^(w-1) - 1 buckets with indices [1..2^(w-1)) initialized with identity points. Bucket 0 is not needed as it would contain points multiplied by 0.
  2. Convert scalars to a radix-2^w representation with signed digits in [-2^w/2, 2^w/2]. Note: only the last digit may equal 2^w/2.
  3. Starting with the last window, for each point i=[0..n) add it to a a bucket indexed by the point’s scalar’s value in the window.
  4. Once all points in a window are sorted into buckets, add buckets by multiplying each by their index. Efficient way of doing it is to start with the last bucket and compute two sums: intermediate sum from the last to the first, and the full sum made of all intermediate sums.
  5. Shift the resulting sum of buckets by w bits by using w doublings.
  6. Add to the return value.
  7. Repeat the loop.

Approximate cost w/o wNAF optimizations (A = addition, D = doubling):

cost = (n*A + 2*(2^w/2)*A + w*D + A)*256/w
         |          |       |     |   |
         |          |       |     |   looping over 256/w windows
         |          |       |     adding to the result
   sorting points   |       shifting the sum by w bits (to the next window, starting from last window)
   one by one       |
   into buckets     adding/subtracting all buckets
                    multiplied by their indexes
                    using a sum of intermediate sums

For large n, dominant factor is (n*256/w) additions. However, if w is too big and n is not too big, then (2^w/2)*A could dominate. Therefore, the optimal choice of w grows slowly as n grows.

This algorithm is adapted from section 4 of https://eprint.iacr.org/2012/549.pdf.

Trait Implementations§

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impl VartimeMultiscalarMul for Pippenger

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type Point = EdwardsPoint

The type of point being multiplied, e.g., RistrettoPoint.
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fn optional_multiscalar_mul<I, J>(scalars: I, points: J) -> Option<EdwardsPoint>

Given an iterator of public scalars and an iterator of Options of points, compute either Some(Q), where $$ Q = c_1 P_1 + \cdots + c_n P_n, $$ if all points were Some(P_i), or else return None. Read more
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fn vartime_multiscalar_mul<I, J>(scalars: I, points: J) -> Self::Point
where I: IntoIterator, I::Item: Borrow<Scalar>, J: IntoIterator, J::Item: Borrow<Self::Point>, Self::Point: Clone,

Given an iterator of public scalars and an iterator of public points, compute $$ Q = c_1 P_1 + \cdots + c_n P_n, $$ using variable-time operations. Read more

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