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* Update MPFR to 3.1.0 - http://trac.sagemath.org/sage_trac/ticket/11666 (Mike Hansen) * People: Bill H., Mike H., Fredrik J., Andy N., Sebastian P. * Update MPFI to 1.5.0 - http://trac.sagemath.org/sage_trac/ticket/12171 (Mike Hansen) |
Projects
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Contents
Put flint2 into Sage
Update MPFR to 3.1.0 - http://trac.sagemath.org/sage_trac/ticket/11666
- (Mike Hansen)
- People: Bill H., Mike H., Fredrik J., Andy N., Sebastian P.
Update MPFI to 1.5.0 - http://trac.sagemath.org/sage_trac/ticket/12171
- (Mike Hansen)
Switch some of the mwrank code to use flint2
Help the Singular developers make better use of flint2
Linear algebra mod p, for log_2 p = 64
Flint2 has an implementation for asymptotically fast linear algebra mod p for p up to 2^64. I (malb) am curious whether it can be improved using ideas inspired by M4RIE, i.e., replace multiplications by additions using pre-computation tables. Whether this is beneficial will depend on how much slower multiplication is than additions.
Update (2011-12-15 10:57): It seems the difference between scalar multiplication and addition is too small for these tricks to make sense.
#include <flint.h> #include <nmod_mat.h> #include <profiler.h> #include <stdio.h> #include "cpucycles-20060326/cpucycles.h" int main(int argc, char *argv[]) { nmod_mat_t A,B,C; flint_rand_t state; unsigned long long cc0 = 0, cc1 = 0; unsigned long i,j; unsigned long long p = 4294967311ULL; flint_randinit(state); nmod_mat_init(A, 2000, 2000, p); nmod_mat_init(C, 2000, 2000, p); nmod_mat_randfull(A, state); cc0 = cpucycles(); nmod_mat_scalar_mul(C, A, 14234); cc0 = cpucycles() - cc0; printf("scalar multiplication: %llu\n",cc0); cc1 = cpucycles(); for (i = 0; i < A->r; i++) { for (j = 0; j < A->c; j++) { C->rows[i][j] = A->rows[i][j] + A->rows[i][j]; } } cc1 = cpucycles() - cc1; printf("addition: %llu\n",cc1); printf("ratio: %lf\n",((double)cc0)/(double)cc1); nmod_mat_clear(A); nmod_mat_clear(C); flint_randclear(state); return 0; }
Gives a ratio of about 4.5.
Linear algebra mod p^n, for log_2 p small-ish
Linear algebra over GF(pk) can be reduced to linear algebra over GF(p) and for GF(2k) the performance is very nice. Hence, it would be a good project to develop some somewhat generic infrastructure for dense matrices over GF(p^k), or even *any* extension field? The natural place to put this would be LinBox but perhaps we can start stand-alone and then integrate it with LinBox if LinBox is too scary to start with.
BKZ 2.0
At AsiaCrypt 2011 Chen and Nguyen presented their new BKZ implementation which is much much more efficient than that in NTL. As far as I understand, the main improvements are due to "extreme pruning" as presented in a paper at EuroCrypt 2010 and perhaps careful parameter choice. As far as I understand, they do not plan to make their code available. I don't know how much work it would be, but perhaps it would be a nice idea to patch NTL's BKZ to include extreme prunning and/or to port it to Flint2?
Improve polynomial factoring mod p in flint2
The Cantor-Zassenhaus implementation in the flint2 nmod_poly module could be optimized:
- Make exponentiation faster by precomputing a Newton inverse of the modulus
- Use sliding window exponentiation
- Use the von zur Gathen / Shoup algorithm (adapt the fast power series composition code for modular composition)