Newton solver CUDA compatibility with Eigen

[pramodk]

• mark newton solver routines with EIGEN_DEVICE_FUNC
  so that the solver can be used from cpu or gpu kernels
• usable with latest master of eigen
• update eigen submodule to latest master

Resolves #41

[lkeegan]

LGTM!

By the way did you find some documentation for EIGEN_DEVICE_FUNC? All I could find was this forum post:
https://eigen.tuxfamily.narkive.com/zeJ54QCx/when-to-mark-eigen-device-func
but based on this it seems that since we use fixed size matrices and therefore don't have any dynamic memory allocations it should work fine on gpus.

Also would it be beneficial to define EIGEN_DEFAULT_DENSE_INDEX_TYPE to int, to use a 32bit int for array indexing instead of the default 64bit? as suggested here:
https://eigen.tuxfamily.org/dox/TopicCUDA.html

[lkeegan]

Also by default Eigen will use openMP if enabled in the compiler.
If openMP is already used in coreneuron we should probably set
EIGEN_DONT_PARALLELIZE
to prevent eigen from creating more threads.
see https://eigen.tuxfamily.org/dox/TopicMultiThreading.html

[pramodk]

By the way did you find some documentation for EIGEN_DEVICE_FUNC? All I could find was this forum

I was just grepping through the code :) ...it gets expand to cuda device/host kernel annotation (__host__ __device__) if code is being compiled with NVCC otherwise its empty (see here)

Also would it be beneficial to define EIGEN_DEFAULT_DENSE_INDEX_TYPE to int, to use a 32bit int for array indexing instead of the default 64bit? as suggested here:
https://eigen.tuxfamily.org/dox/TopicCUDA.html

Also by default Eigen will use openMP if enabled in the compiler. If openMP is already used in coreneuron we should probably set EIGEN_DONT_PARALLELIZE

Yeah, good points! We don't want threads from Eigen as simulator already uses OpenMP. If I am not mistaken, those macros should go into somewhere in global header. I created #47.