#4260: use LinBox as native matrix representation for dense matrices over GF(p)
-----------------------------------------------------------+----------------
    Reporter:  malb                                        |         Owner:  
cpernet                                   
        Type:  enhancement                                 |        Status:  
needs_review                              
    Priority:  major                                       |     Milestone:  
sage-4.8                                  
   Component:  linear algebra                              |    Resolution:     
                                       
    Keywords:  linbox, linear algebra, sd32, sd34          |   Work_issues:     
                                       
    Upstream:  N/A                                         |      Reviewer:  
Burcin Erocal, Simon King, Martin Albrecht
      Author:  Burcin Erocal, Martin Albrecht, Rob Beezer  |        Merged:     
                                       
Dependencies:                                              |  
-----------------------------------------------------------+----------------
Changes (by malb):

  * status:  needs_work => needs_review


Old description:

> Copying to and from LinBox uses up precious RAM and the point of fast
> linear algebra is to deal with large matrices. We should consider
> switching to LinBox as the native representation of matrices over GF(p)
>
> '''Without Patch'''
>
> {{{
> #!python
> sage: A = random_matrix(GF(97),2000,2000)
> sage: %time A*A
> CPU times: user 9.66 s, sys: 0.12 s, total: 9.77 s
> Wall time: 9.82 s
> }}}
>
> '''With Patch'''
> {{{
> #!python
> sage: A = random_matrix(GF(97),2000,2000)
> sage: %time A*A
> CPU times: user 1.32 s, sys: 0.00 s, total: 1.32 s
> Wall time: 1.35 s
> }}}
>
> '''Magma'''
>
> {{{
> > A:=RandomMatrix(GF(97),2000,2000);
> > time C:=A*A;
> Time: 1.560
> }}}
>
>  * '''Install'''
> http://sage.math.washington.edu/home/malb/spkgs/linbox-1.1.6.p5.spkg
>  * '''Apply''' [attachment:trac_4260-linbox_default.patch]
>  * '''Apply''' [attachment:trac_4260-dense_ctypes_template.patch]
>  * '''Apply''' [attachment:trac_4260-matrix-modn-docs.patch]
>  * '''Apply''' [attachment:trac_4260_more_doctests.patch]
>  * '''Apply''' [attachment:trac_4260_echelonformdomain.patch]
>  * '''Apply''' [attachment:trac_4260-minor_fixes.patch]

New description:

 Copying to and from LinBox uses up precious RAM and the point of fast
 linear algebra is to deal with large matrices. We should consider
 switching to LinBox as the native representation of matrices over GF(p)

 '''Without Patch'''

 {{{
 #!python
 sage: A = random_matrix(GF(97),2000,2000)
 sage: %time A*A
 CPU times: user 9.66 s, sys: 0.12 s, total: 9.77 s
 Wall time: 9.82 s
 }}}

 '''With Patch'''
 {{{
 #!python
 sage: A = random_matrix(GF(97),2000,2000)
 sage: %time A*A
 CPU times: user 1.32 s, sys: 0.00 s, total: 1.32 s
 Wall time: 1.35 s
 }}}

 '''Magma'''

 {{{
 > A:=RandomMatrix(GF(97),2000,2000);
 > time C:=A*A;
 Time: 1.560
 }}}

  * '''Install'''
 http://sage.math.washington.edu/home/malb/spkgs/linbox-1.1.6.p5.spkg
  * '''Apply''' [attachment:trac_4260-linbox_default.patch]
  * '''Apply''' [attachment:trac_4260-dense_ctypes_template.patch]
  * '''Apply''' [attachment:trac_4260-matrix-modn-docs.patch]
  * '''Apply''' [attachment:trac_4260_more_doctests.patch]
  * '''Apply''' [attachment:trac_4260_echelonformdomain.patch]
  * '''Apply''' [attachment:trac_4260-minor_fixes.patch]
  * '''Apply''' [attachment:trac_4260_bugfix.patch]

--

Comment:

 The attached patch fixes the issue on the machine in question. We forgot
 to deal with 32-bit systems in setting elements while we did it for
 getting elements.

-- 
Ticket URL: <http://trac.sagemath.org/sage_trac/ticket/4260#comment:40>
Sage <http://www.sagemath.org>
Sage: Creating a Viable Open Source Alternative to Magma, Maple, Mathematica, 
and MATLAB

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