#13358: package for fast polynomial evaluation
--------------------------------+-------------------------------------------
Reporter: gmoroz | Owner: AlexGhitza
Type: enhancement | Status: new
Priority: major | Milestone: sage-5.3
Component: basic arithmetic | Keywords: polynomials
Work issues: | Report Upstream: N/A
Reviewers: | Authors:
Merged in: | Dependencies: boost::interval (optional)
Stopgaps: |
--------------------------------+-------------------------------------------
The attached package provides conversion of univariate and multivariate
polynomials into object that are optimized for fast evaluation on python
object or low-levels c++ classes (see examples at the end).
It could enhanced the fast_callable function for several types, and also
enhances in general the evaluation of polynomials on polynomials.
To test it, you can install it with: ./setup.py install
This will install the package in $SAGE_ROOT/local/lib/python2.7/site-
packages/
Main features:
* handles univariate and multivariate polynomials
* specialized for several low-level types (mpfi, mpz, mpq,
boost::interval)
* different evaluation layouts (horner, estrin, expanded, ...)
* easily extensible:
- add new types (see fast_polynomial/interfaces/README)
- add new layouts (see docstring of fast_polynomial.method)
* handles generic python/sage objects
* can be multi-threaded
Main limitations:
* only handles polynomial (no evaluation of trigonometric functions,...)
* polynomial needs to be converted to a fast callable object before
evaluation
(there is room for speed up on conversion time)
Examples and benchmarks:
{{{
from fast_polynomial import *
R.<x> = ZZ[x]
p = R.random_element(500,-100,100)
# evaluation of polynomials
q = python_polynomial(p, mode='horner')
r = python_polynomial(p, mode='estrin')
%timeit p(x+1) #5 loops, best of 3: 40.3 ms per loop
%timeit q(x+1) #5 loops, best of 3: 40.3 ms per loop
%timeit r(x+1) #125 loops, best of 3: 2.26 ms per loop
%timeit python_polynomial(p)(x+1) #125 loops, best of 3: 3.2 ms per loop
# evaluation of long integers
q = mpz_polynomial(p, num_threads=1)
r = mpz_polynomial(p, num_threads=2)
%timeit p(100) #625 loops, best of 3: 50.4 µs per loop
%timeit q(100) #625 loops, best of 3: 48.1 µs per loop
%timeit r(100) #625 loops, best of 3: 34.9 µs per loop
# evaluation of mpfi interval with precision 1000
q = mpfi_polynomial(p, 1000)
e = RealIntervalField(1000)(2^500, 2^500+1)
cmp(p(e),q(e)) #0
%timeit p(e) #125 loops, best of 3: 2.71 ms per loop
%timeit q(e) #625 loops, best of 3: 513 µs per loop
%timeit mpfi_polynomial(p)(e) #125 loops, best of 3: 1.15 ms per loop
# evaluation of boost interval (précision 53)
q = boost_polynomial(p, mode='horner')
r = boost_polynomial(p, mode='balanced', num_threads=2)
f = fast_callable(p, domain=float)
e = RIF(0.01)
%timeit p(e) #125 loops, best of 3: 2.14 ms per loop
%timeit f(0.01) #625 loops, best of 3: 9.54 µs per loop
%timeit q(e) #625 loops, best of 3: 13.4 µs per loop
%timeit r(e) #625 loops, best of 3: 11.7 µs per loop
# Note that boost_polynomial evaluation offers more guarantees than raw
float evaluation
# multivariate polynomials
R20 = PolynomialRing(QQ, 20,'x')
p = R20.random_element(5,100)
q = mpq_polynomial(p)
%timeit p((2/3,)*20) #125 loops, best of 3: 2.06 ms per loop
%timeit q((2/3,)*20) #625 loops, best of 3: 178 µs per loop
%timeit mpq_polynomial(p) #125 loops, best of 3: 1.91 ms per loop
}}}
--
Ticket URL: <http://trac.sagemath.org/sage_trac/ticket/13358>
Sage <http://www.sagemath.org>
Sage: Creating a Viable Open Source Alternative to Magma, Maple, Mathematica,
and MATLAB
--
You received this message because you are subscribed to the Google Groups
"sage-trac" group.
To post to this group, send email to [email protected].
To unsubscribe from this group, send email to
[email protected].
For more options, visit this group at
http://groups.google.com/group/sage-trac?hl=en.