Re: [eigen] Matrix decompositions

[Sameer Agarwal <sameeragarwal@xxxxxxxxxx>]

On Thu, Feb 28, 2013 at 1:24 PM, Gael Guennebaud <gael.guennebaud@xxxxxxxxx> wrote:

On Thu, Feb 28, 2013 at 10:00 PM, Sameer Agarwal
<sameeragarwal@xxxxxxxxxx> wrote:
> So why is SIMD/vectorization disabled on unaligned matrices? and by turn on
> Map objects.

SIMD is disabled only for fixed size matrices which are supposed to be
small, and so not worth trying to adapt to the actual alignement at
run-time. For dynamic size matrices, everything is vectorized.

Two questions here.

1. So I can take an arbitrary block of memory, make a Map object out of it and all operations on it are vectorized?  

2. What are the performance implications of using an Aligned versus unaligned matrix then?  Because in the automatic differentiation code in Ceres, where we use unaligned eigen matrices, declaring them aligned makes a 2x difference in performance. And we thought this was because vectorization was getting disabled.

Sameer