11,964 research outputs found
Faster polynomial multiplication over finite fields
Let p be a prime, and let M_p(n) denote the bit complexity of multiplying two
polynomials in F_p[X] of degree less than n. For n large compared to p, we
establish the bound M_p(n) = O(n log n 8^(log^* n) log p), where log^* is the
iterated logarithm. This is the first known F\"urer-type complexity bound for
F_p[X], and improves on the previously best known bound M_p(n) = O(n log n log
log n log p)
Faster 64-bit universal hashing using carry-less multiplications
Intel and AMD support the Carry-less Multiplication (CLMUL) instruction set
in their x64 processors. We use CLMUL to implement an almost universal 64-bit
hash family (CLHASH). We compare this new family with what might be the fastest
almost universal family on x64 processors (VHASH). We find that CLHASH is at
least 60% faster. We also compare CLHASH with a popular hash function designed
for speed (Google's CityHash). We find that CLHASH is 40% faster than CityHash
on inputs larger than 64 bytes and just as fast otherwise
Faster truncated integer multiplication
We present new algorithms for computing the low n bits or the high n bits of
the product of two n-bit integers. We show that these problems may be solved in
asymptotically 75% of the time required to compute the full 2n-bit product,
assuming that the underlying integer multiplication algorithm relies on
computing cyclic convolutions of real sequences.Comment: 28 page
Chunky and Equal-Spaced Polynomial Multiplication
Finding the product of two polynomials is an essential and basic problem in
computer algebra. While most previous results have focused on the worst-case
complexity, we instead employ the technique of adaptive analysis to give an
improvement in many "easy" cases. We present two adaptive measures and methods
for polynomial multiplication, and also show how to effectively combine them to
gain both advantages. One useful feature of these algorithms is that they
essentially provide a gradient between existing "sparse" and "dense" methods.
We prove that these approaches provide significant improvements in many cases
but in the worst case are still comparable to the fastest existing algorithms.Comment: 23 Pages, pdflatex, accepted to Journal of Symbolic Computation (JSC
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