Commit Graph

9 Commits (master)

Author SHA1 Message Date
Sébastien Villemot 39f47dc957
local_state_space_iteration_k MEX now uses the Fortran code (instead of the C++ code)
Closes: #1802
2022-02-04 11:49:46 +01:00
NormannR 5f828e241f Parallelizes local_state_space_iteration_fortran 2022-01-31 18:44:48 +01:00
Sébastien Villemot 2ab919ebf1
Testsuite: use default number of particles when comparing performance of the various state space iteration MEX 2021-10-21 16:34:22 +02:00
Sébastien Villemot e66a1a63f8
local_state_space_iteration_2 MEX: enable parallelization by default 2021-10-20 15:33:04 +02:00
Sébastien Villemot fbba0bf2fc
Testsuite: fix display of relative timings of local_state_space_iteration_{k,fortran} 2021-10-20 15:32:26 +02:00
NormannR cab65dabb5 Implements `local_state_space_iteration_fortran`, the Fortran replacement of `local_state_space_iteration_k` (Ref #1802)
- Creates the library `libkordersim` with all the relevant Fortran routines to `folded_to_unfolded_dr` and `local_state_space_iteration_fortran`
   - Implements `folded_to_unfolded_dr`, which converts folded decision rule matrices to their unfolded counterparts
2021-09-22 16:28:46 +02:00
Sébastien Villemot c9eb6920c9
local_state_space_iteration_k MEX: fix bug in output
In its output, the MEX was returning values for all endogenous variables, but
it was used in a context where only the variables from oo_.dr.restrict_var_list
were expected (as is done with local_state_space_iteration_2 MEX).

This commit fixes this discrepancy, and also fixes the test that was checking
that both MEX are returning the same output.

Closes: #1768
2021-03-10 13:45:29 +01:00
Stéphane Adjemian (Odysseus) 58da5e7120 Added timing for comparing the mex iterating on the nonlinear reduced form model.
local_state_space_iteration_k is significantly slower than old local_state_space_iteration_2...
2019-12-20 11:31:56 +01:00
Sébastien Villemot 996bdd6c64 New local_state_space_iteration_k MEX, for nonlinear filters at k-order
It applies the approximated policy function to a set of particles, using
Dynare++ routines.

There is support for parallelization, using Dynare++ multithreading
model (itself based on C++11 threads; we don’t use OpenMP because it is
incompatible with MKL). For the time being, default to a single thread. This
should be later refined through empirical testing.
2019-12-20 11:31:56 +01:00