Re: Parallelization

2016-07-18 Thread Eliot Moss
On 7/18/2016 1:38 AM, Tony Kelman wrote: Eliot Moss cs.umass.edu> writes: True ... it also made me think of Python, which is designed to use parallelized numpy (etc.) libraries, optimized for your platform. Can use all the hardware threads on your machine, as well as make good use of vector ex

Re: Parallelization

2016-07-17 Thread Tony Kelman
Eliot Moss cs.umass.edu> writes: > True ... it also made me think of Python, which is designed to use > parallelized numpy (etc.) libraries, optimized for your platform. > Can use all the hardware threads on your machine, as well as make > good use of vector extensions such as AVX. A 64-bit (x86

Re: Parallelization

2016-07-17 Thread Eliot Moss
On 7/17/2016 7:56 AM, Tony Kelman wrote: Thomas Koenig netcologne.de> writes: This is more of a general numerical ODE or Sundials usage question rather than a cygwin specific one, but I would try openmp or mpi on your function evaluations first, if that's taking most of the time. Do you know

Re: Parallelization

2016-07-17 Thread Tony Kelman
achine. > > So, the question: Is there a way to parallelize the calculation for > this? The references in the Sundials docs that I have seen only refer > to parallelization of solving linear equations, which I do not need > to do. > > Regards > > Thomas >

Parallelization

2016-07-17 Thread Thomas Koenig
the Sundials docs that I have seen only refer to parallelization of solving linear equations, which I do not need to do. Regards Thomas -- Problem reports: http://cygwin.com/problems.html FAQ: http://cygwin.com/faq/ Documentation: http://cygwin.com/docs.html