Fast, Vectorizable method of taking floating point number modulus of special primes?

Is there a fast method for taking the modulus of a floating point number?

With integers, there are tricks for Mersenne primes, so that its possible to calculate y = x MOD 2^31-1 without needing division. integer trick

Can any similar tricks be applied for floating point numbers?

Preferably, in a way that can be converted into vector/SIMD operations, or moved into GPGPU code. This rules out using integer calculations on the floating point data.

The primes I'm interested in would be 2^7-1 and 2^31-1, although if there are more efficient ones开发者_运维技巧 for floating point numbers, those would be welcome.

One intended use of this algorithm would be to calculate a running "checksum" of input floating point numbers as they are being read into an algorithm. To avoid taking up too much of the calculation capability, I'd like to keep this lightweight.

Apparently a similar technique is used for larger numbers, particularly 2^127 - 1. Unfortunately, the math in the paper is beyond me, and I haven't been able to figure out how to convert it to smaller primes.

Example of floating point MOD 2^127 - 1 - HASH127

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I looked at djb's paper, and you have it easier, since 31 bits fits comfortably into the 53-bit precision double significand. Assuming that your checksum consists of some ring operations over Z/(2**31 - 1), it will be easier (and faster) to solve the relaxed problem of computing a small representative of x mod Z/(2**31 - 1); at the end, you can use integer arithmetic to find a canonical one, which is slow but shouldn't happen too often.

The basic reduction step is to replace an integer x = y + 2**31 * z with y + z. The trick that djb uses is to compute w = (x + L) - L, where L is a large integer carefully chosen to provoke roundoff in such a way that z = 2**-31 * w. Then compute y = x - w and output y + z, which will have magnitude at most 2**32. (I apologize if this operation isn't quite enough; if so, please post your checksum algorithm.)

The choice of L involves knowing how precise the significand is. For the modulus 2**31 - 1, we want the unit of least precision (ulp) to be 2**31. For doubles in the range [1.0, 2.0), the ulp is 2**-52, so L should be 2**52 * 2**31. If you were doing this with the modulus 2**7 - 1, then you'd take L = 2**52 * 2**7. As djb notes, this trick depends crucially on intermediate results not being computed in higher precision.