local_state_space_iteration_k MEX now uses the Fortran code (instead of the C++ code)
Closes: #1802trustregion
Sébastien Villemot
parent
10a4ec53e9
commit
39f47dc957
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@ -26,7 +26,7 @@ function [fval,info,exit_flag,DLIK,Hess,ys,trend_coeff,Model,DynareOptions,Bayes
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% - BayesInfo [struct] See INPUTS section.
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% - DynareResults [struct] Updated DynareResults structure described in INPUTS section.
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% Copyright (C) 2010-2021 Dynare Team
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% Copyright (C) 2010-2022 Dynare Team
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%
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% This file is part of Dynare.
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%
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@ -127,6 +127,7 @@ ReducedForm.mf1 = mf1;
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if DynareOptions.k_order_solver && ~(DynareOptions.particle.pruning && DynareOptions.order==2)
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ReducedForm.use_k_order_solver = true;
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ReducedForm.dr = dr;
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ReducedForm.udr = folded_to_unfolded_dr(dr, Model, DynareOptions);
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else
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ReducedForm.use_k_order_solver = false;
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ReducedForm.ghx = dr.ghx(restrict_variables_idx,:);
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@ -1 +1 @@
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Subproject commit 2e18ca8ff584d1ab47658f329ab73ab1c27cdf6f
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Subproject commit d20be2c271b442d91bd36aea300e4837a066ae2d
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@ -1,14 +0,0 @@
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mex_PROGRAMS = local_state_space_iteration_fortran
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local_state_space_iteration_fortran_FCFLAGS = $(AM_FCFLAGS) -I../libkordersim -pthread
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nodist_local_state_space_iteration_fortran_SOURCES = \
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mexFunction.f08
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local_state_space_iteration_fortran_LDADD = ../libkordersim/libkordersim.a
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BUILT_SOURCES = $(nodist_local_state_space_iteration_fortran_SOURCES)
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CLEANFILES = $(nodist_local_state_space_iteration_fortran_SOURCES)
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%.f08: $(top_srcdir)/../../sources/local_state_space_iteration_fortran/%.f08
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$(LN_S) -f $< $@
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@ -1,14 +1,13 @@
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mex_PROGRAMS = local_state_space_iteration_2 local_state_space_iteration_k
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nodist_local_state_space_iteration_2_SOURCES = local_state_space_iteration_2.cc
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nodist_local_state_space_iteration_k_SOURCES = local_state_space_iteration_k.cc
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nodist_local_state_space_iteration_k_SOURCES = local_state_space_iteration_k.f08
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local_state_space_iteration_2_CXXFLAGS = $(AM_CXXFLAGS) -fopenmp
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local_state_space_iteration_2_LDFLAGS = $(AM_LDFLAGS) $(OPENMP_LDFLAGS)
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local_state_space_iteration_k_CPPFLAGS = $(AM_CPPFLAGS) -I$(top_srcdir)/../../../dynare++/sylv/cc -I$(top_srcdir)/../../../dynare++/tl/cc -I$(top_srcdir)/../../../dynare++/kord -I$(top_srcdir)/../../../dynare++/utils/cc $(CPPFLAGS_MATIO)
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local_state_space_iteration_k_LDFLAGS = $(AM_LDFLAGS) $(LDFLAGS_MATIO)
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local_state_space_iteration_k_LDADD = ../libdynare++/libdynare++.a $(LIBADD_MATIO)
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local_state_space_iteration_k_FCFLAGS = $(AM_FCFLAGS) -I../libkordersim -pthread
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local_state_space_iteration_k_LDADD = ../libkordersim/libkordersim.a
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BUILT_SOURCES = $(nodist_local_state_space_iteration_2_SOURCES) \
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$(nodist_local_state_space_iteration_k_SOURCES)
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@ -17,3 +16,6 @@ CLEANFILES = $(nodist_local_state_space_iteration_2_SOURCES) \
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%.cc: $(top_srcdir)/../../sources/local_state_space_iterations/%.cc
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$(LN_S) -f $< $@
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%.f08: $(top_srcdir)/../../sources/local_state_space_iterations/%.f08
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$(LN_S) -f $< $@
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@ -1,10 +1,10 @@
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ACLOCAL_AMFLAGS = -I ../../../m4
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SUBDIRS = mjdgges kronecker bytecode block_kalman_filter sobol perfect_foresight_problem num_procs block_trust_region disclyap_fast
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SUBDIRS = mjdgges kronecker bytecode block_kalman_filter sobol perfect_foresight_problem num_procs block_trust_region disclyap_fast libkordersim local_state_space_iterations folded_to_unfolded_dr k_order_simul k_order_mean
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# libdynare++ must come before gensylv and k_order_perturbation
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if ENABLE_MEX_DYNAREPLUSPLUS
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SUBDIRS += libdynare++ gensylv libkorder k_order_perturbation k_order_welfare local_state_space_iterations libkordersim folded_to_unfolded_dr local_state_space_iteration_fortran k_order_simul k_order_mean
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SUBDIRS += libdynare++ gensylv libkorder k_order_perturbation k_order_welfare
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endif
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if ENABLE_MEX_MS_SBVAR
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@ -1,6 +1,6 @@
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dnl Process this file with autoconf to produce a configure script.
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dnl Copyright © 2009-2021 Dynare Team
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dnl Copyright © 2009-2022 Dynare Team
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dnl
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dnl This file is part of Dynare.
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dnl
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@ -165,7 +165,6 @@ AC_CONFIG_FILES([Makefile
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local_state_space_iterations/Makefile
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libkordersim/Makefile
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folded_to_unfolded_dr/Makefile
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local_state_space_iteration_fortran/Makefile
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k_order_simul/Makefile
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k_order_mean/Makefile
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perfect_foresight_problem/Makefile
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@ -1,2 +0,0 @@
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include ../mex.am
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include ../../local_state_space_iteration_fortran.am
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@ -1,10 +1,10 @@
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ACLOCAL_AMFLAGS = -I ../../../m4
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SUBDIRS = mjdgges kronecker bytecode block_kalman_filter sobol perfect_foresight_problem num_procs block_trust_region disclyap_fast
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SUBDIRS = mjdgges kronecker bytecode block_kalman_filter sobol perfect_foresight_problem num_procs block_trust_region disclyap_fast libkordersim local_state_space_iterations folded_to_unfolded_dr k_order_simul k_order_mean
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# libdynare++ must come before gensylv and k_order_perturbation
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if ENABLE_MEX_DYNAREPLUSPLUS
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SUBDIRS += libdynare++ gensylv libkorder k_order_perturbation k_order_welfare local_state_space_iterations libkordersim folded_to_unfolded_dr local_state_space_iteration_fortran k_order_simul k_order_mean
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SUBDIRS += libdynare++ gensylv libkorder k_order_perturbation k_order_welfare
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endif
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if ENABLE_MEX_MS_SBVAR
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@ -1,6 +1,6 @@
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dnl Process this file with autoconf to produce a configure script.
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dnl Copyright © 2009-2021 Dynare Team
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dnl Copyright © 2009-2022 Dynare Team
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dnl
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dnl This file is part of Dynare.
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dnl
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@ -166,7 +166,6 @@ AC_CONFIG_FILES([Makefile
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local_state_space_iterations/Makefile
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libkordersim/Makefile
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folded_to_unfolded_dr/Makefile
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local_state_space_iteration_fortran/Makefile
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k_order_simul/Makefile
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k_order_mean/Makefile
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perfect_foresight_problem/Makefile
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@ -1,3 +0,0 @@
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EXEEXT = .mex
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include ../mex.am
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include ../../local_state_space_iteration_fortran.am
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@ -18,7 +18,6 @@ EXTRA_DIST = \
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local_state_space_iterations \
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libkordersim \
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folded_to_unfolded_dr \
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local_state_space_iteration_fortran \
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k_order_simul \
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k_order_mean \
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gensylv \
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@ -1,4 +1,4 @@
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! Copyright © 2021 Dynare Team
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! Copyright © 2021-2022 Dynare Team
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!
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! This file is part of Dynare.
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!
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@ -15,7 +15,7 @@
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! You should have received a copy of the GNU General Public License
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! along with Dynare. If not, see <https://www.gnu.org/licenses/>.
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! Routines and data structures for multithreading over particles in local_state_space_iteration_fortran
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! Routines and data structures for multithreading over particles in local_state_space_iteration_k
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module pparticle
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use iso_c_binding
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use simulation
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@ -75,4 +75,4 @@ contains
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end subroutine thread_eval
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end module pparticle
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end module pparticle
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@ -1,191 +0,0 @@
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/*
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* Copyright © 2019-2021 Dynare Team
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*
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* This file is part of Dynare.
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*
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* Dynare is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* Dynare is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with Dynare. If not, see <https://www.gnu.org/licenses/>.
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*/
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#include <memory>
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#include <string>
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#include <utility>
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#include <dynmex.h>
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#include "tl_static.hh"
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#include "decision_rule.hh"
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#include "sthread.hh"
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/* The class that does the real job. It computes the next iteration for a given
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range of particles. There will be as many instances as there are parallel
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threads.
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Note that we can’t use OpenMP since it is incompatible with MKL, which is
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used internally by Dynare++ routines under MATLAB. Hence we fall back to
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the Dynare++ multithreading abstraction. */
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struct ParticleWorker : public sthread::detach_thread
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{
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const int npred_both, exo_nbr;
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const std::pair<size_t, size_t> particle_range;
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const ConstGeneralMatrix &yhat, ε
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const Vector &ys_reordered;
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const UnfoldDecisionRule &dr;
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const ConstVector &restrict_var_list;
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GeneralMatrix &ynext;
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ParticleWorker(int npred_both_arg, int exo_nbr_arg, std::pair<size_t, size_t> particle_range_arg,
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const ConstGeneralMatrix &yhat_arg, const ConstGeneralMatrix &epsilon_arg,
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const Vector &ys_reordered_arg, const UnfoldDecisionRule &dr_arg,
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const ConstVector &restrict_var_list_arg, GeneralMatrix &ynext_arg)
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: npred_both{npred_both_arg}, exo_nbr{exo_nbr_arg}, particle_range{std::move(particle_range_arg)},
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yhat{yhat_arg}, epsilon{epsilon_arg}, ys_reordered{ys_reordered_arg}, dr{dr_arg},
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restrict_var_list{restrict_var_list_arg}, ynext{ynext_arg}
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{
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}
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void
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operator()(std::mutex &mut) override
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{
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Vector dyu(npred_both+exo_nbr);
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Vector dy(dyu, 0, npred_both);
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Vector u(dyu, npred_both, exo_nbr);
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Vector ynext_col_allvars(ys_reordered.length());
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for (size_t i = particle_range.first; i < particle_range.second; i++)
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{
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dy = yhat.getCol(i);
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u = epsilon.getCol(i);
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dr.eval(DecisionRule::emethod::horner, ynext_col_allvars, dyu);
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ynext_col_allvars.add(1.0, ys_reordered);
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/* Select only the variables in restrict_var_list, and copy back to the
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result matrix */
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Vector ynext_col{ynext.getCol(i)};
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for (int j = 0; j < restrict_var_list.length(); j++)
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ynext_col[j] = ynext_col_allvars[restrict_var_list[j]-1];
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}
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}
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};
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void
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mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
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{
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if (nrhs != 5 || nlhs != 1)
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mexErrMsgTxt("Must have 5 input arguments and 1 output argument");
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// Give explicit names to input arguments
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const mxArray *yhat_mx = prhs[0];
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const mxArray *epsilon_mx = prhs[1];
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const mxArray *dr_mx = prhs[2];
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const mxArray *M_mx = prhs[3];
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const mxArray *options_mx = prhs[4];
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auto get_int_field = [](const mxArray *struct_mx, const std::string &fieldname)
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{
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mxArray *field_mx = mxGetField(struct_mx, 0, fieldname.c_str());
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if (!(field_mx && mxIsScalar(field_mx) && mxIsNumeric(field_mx)))
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mexErrMsgTxt(("Field `" + fieldname + "' should be a numeric scalar").c_str());
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return static_cast<int>(mxGetScalar(field_mx));
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};
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int nstatic = get_int_field(M_mx, "nstatic");
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int npred = get_int_field(M_mx, "npred");
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int nboth = get_int_field(M_mx, "nboth");
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int nfwrd = get_int_field(M_mx, "nfwrd");
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int endo_nbr = nstatic + npred + nboth + nfwrd;
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int exo_nbr = get_int_field(M_mx, "exo_nbr");
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int order = get_int_field(options_mx, "order");
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const mxArray *order_var_mx = mxGetField(dr_mx, 0, "order_var");
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if (!(order_var_mx && mxIsDouble(order_var_mx) && mxGetNumberOfElements(order_var_mx) == static_cast<size_t>(endo_nbr)))
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mexErrMsgTxt("Field dr.order_var should be a double precision vector with endo_nbr elements");
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const mxArray *ys_mx = mxGetField(dr_mx, 0, "ys");
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if (!ys_mx || !mxIsDouble(ys_mx) || mxGetNumberOfElements(ys_mx) != static_cast<size_t>(endo_nbr))
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mexErrMsgTxt("Field dr.ys should be a double precision vector with endo_nbr elements");
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const mxArray *restrict_var_list_mx = mxGetField(dr_mx, 0, "restrict_var_list");
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if (!(restrict_var_list_mx && mxIsDouble(restrict_var_list_mx)))
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mexErrMsgTxt("Field dr.restrict_var_list should be a double precision vector");
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size_t nparticles = mxGetN(yhat_mx);
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if (mxGetN(epsilon_mx) != nparticles)
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mexErrMsgTxt("epsilon and yhat don't have the same number of columns");
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if (!(mxIsDouble(yhat_mx) && mxGetM(yhat_mx) == static_cast<size_t>(npred + nboth)))
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mexErrMsgTxt("yhat should be a double precision matrix with npred+nboth rows");
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if (!(mxIsDouble(epsilon_mx) && mxGetM(epsilon_mx) == static_cast<size_t>(exo_nbr)))
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mexErrMsgTxt("epsilon should be a double precision matrix with exo_nbr rows");
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const mxArray *threads_mx = mxGetField(options_mx, 0, "threads");
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if (!threads_mx)
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mexErrMsgTxt("Can't find field `threads' in options_");
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int num_threads = get_int_field(threads_mx, "local_state_space_iteration_k");
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ConstGeneralMatrix yhat{yhat_mx};
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ConstGeneralMatrix epsilon{epsilon_mx};
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ConstVector ys{ys_mx};
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const double *order_var = mxGetPr(order_var_mx);
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ConstVector restrict_var_list{restrict_var_list_mx};
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try
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{
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TLStatic::init(order, npred+nboth+exo_nbr);
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}
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catch (TLException &e)
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{
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mexErrMsgTxt(("Dynare++ error: " + e.message).c_str());
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}
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// Form the polynomial (copied from dynare_simul_.cc)
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UTensorPolynomial pol(endo_nbr, npred+nboth+exo_nbr);
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for (int dim = 0; dim <= order; dim++)
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{
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const mxArray *gk_m = mxGetField(dr_mx, 0, ("g_" + std::to_string(dim)).c_str());
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if (!gk_m)
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mexErrMsgTxt(("Can't find field `g_" + std::to_string(dim) + "' in dr structure").c_str());
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ConstTwoDMatrix gk{gk_m};
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FFSTensor ft{endo_nbr, npred+nboth+exo_nbr, dim};
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if (ft.ncols() != gk.ncols())
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mexErrMsgTxt(("Wrong number of columns for folded tensor: got " + std::to_string(gk.ncols()) + " but i want " + std::to_string(ft.ncols()) + '\n').c_str());
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if (ft.nrows() != gk.nrows())
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mexErrMsgTxt(("Wrong number of rows for folded tensor: got " + std::to_string(gk.nrows()) + " but i want " + std::to_string(ft.nrows()) + '\n').c_str());
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ft.zeros();
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ft.add(1.0, gk);
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pol.insert(std::make_unique<UFSTensor>(ft));
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}
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// Construct the reordered steady state (dr.ys(dr.order_var))
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Vector ys_reordered(endo_nbr);
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for (int i = 0; i < endo_nbr; i++)
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ys_reordered[i] = ys[static_cast<int>(order_var[i])-1];
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// Form the decision rule
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UnfoldDecisionRule dr(pol, PartitionY(nstatic, npred, nboth, nfwrd),
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exo_nbr, ys_reordered);
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// Create the result matrix
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plhs[0] = mxCreateDoubleMatrix(restrict_var_list.length(), nparticles, mxREAL);
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GeneralMatrix ynext{plhs[0]};
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// Run the real job in parallel
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sthread::detach_thread_group::max_parallel_threads = num_threads;
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sthread::detach_thread_group group;
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// The following is equivalent to ceil(nparticles/num_threads), but with integer arithmetic
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int part_by_thread = nparticles / num_threads + (nparticles % num_threads > 0);
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for (size_t i = 0; i < nparticles; i += part_by_thread)
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group.insert(std::make_unique<ParticleWorker>(npred+nboth, exo_nbr,
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std::make_pair(i, std::min(i+part_by_thread, nparticles)),
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yhat, epsilon, ys_reordered, dr, restrict_var_list,
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ynext));
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group.run();
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}
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@ -1,4 +1,4 @@
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! Copyright © 2021 Dynare Team
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! Copyright © 2021-2022 Dynare Team
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!
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! This file is part of Dynare.
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!
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@ -118,7 +118,7 @@ subroutine mexFunction(nlhs, plhs, nrhs, prhs) bind(c, name='mexFunction')
|
|||
if (.not. c_associated(thread_mx)) then
|
||||
call mexErrMsgTxt("Cannot find `threads' in options_")
|
||||
end if
|
||||
nm = get_int_field(thread_mx, "local_state_space_iteration_fortran")
|
||||
nm = get_int_field(thread_mx, "local_state_space_iteration_k")
|
||||
end associate
|
||||
|
||||
nparticles = int(mxGetN(yhat_mx));
|
||||
|
|
@ -618,8 +618,7 @@ PARTICLEFILES = \
|
|||
particle/dsge_base2.mod \
|
||||
particle/first_spec.mod \
|
||||
particle/first_spec_MCMC.mod \
|
||||
particle/local_state_space_iteration_k_test.mod \
|
||||
particle/local_it_k_test_parallel.mod
|
||||
particle/local_state_space_iteration_k_test.mod
|
||||
|
||||
|
||||
XFAIL_MODFILES = ramst_xfail.mod \
|
||||
|
|
|
|||
|
|
@ -1,58 +0,0 @@
|
|||
/*
|
||||
Tests that the parallelized version of local_state_space_iteration_k and local_state_space_iteration_fortran
|
||||
(for k=3) return the same results.
|
||||
|
||||
This file must be run after first_spec.mod (both are based on the same model).
|
||||
*/
|
||||
|
||||
@#include "first_spec_common.inc"
|
||||
|
||||
varobs q ca;
|
||||
|
||||
shocks;
|
||||
var eeps = 0.04^2;
|
||||
var nnu = 0.03^2;
|
||||
var q = 0.01^2;
|
||||
var ca = 0.01^2;
|
||||
end;
|
||||
|
||||
// Initialize various structures
|
||||
estimation(datafile='my_data.mat',order=2,mode_compute=0,mh_replic=0,filter_algorithm=sis,nonlinear_filter_initialization=2
|
||||
,cova_compute=0 %tell program that no covariance matrix was computed
|
||||
);
|
||||
|
||||
stoch_simul(order=2, periods=200, irf=0, k_order_solver);
|
||||
|
||||
// Really perform the test
|
||||
|
||||
nparticles = options_.particle.number_of_particles;
|
||||
nsims = 1e6/nparticles;
|
||||
|
||||
/* We generate particles using realistic distributions (though this is not
|
||||
strictly needed) */
|
||||
state_idx = oo_.dr.order_var((M_.nstatic+1):(M_.nstatic+M_.npred+M_.nboth));
|
||||
yhat = chol(oo_.var(state_idx,state_idx))*randn(M_.npred+M_.nboth, nparticles);
|
||||
epsilon = chol(M_.Sigma_e)*randn(M_.exo_nbr, nparticles);
|
||||
|
||||
stoch_simul(order=3, periods=200, irf=0, k_order_solver);
|
||||
|
||||
options_.threads.local_state_space_iteration_k = 2;
|
||||
options_.threads.local_state_space_iteration_fortran = 2;
|
||||
|
||||
tStart1 = tic; for i=1:nsims, ynext1 = local_state_space_iteration_k(yhat, epsilon, oo_.dr, M_, options_); end, tElapsed1 = toc(tStart1);
|
||||
|
||||
tStart2 = tic; [udr] = folded_to_unfolded_dr(oo_.dr, M_, options_); for i=1:nsims, ynext2 = local_state_space_iteration_fortran(yhat, epsilon, oo_.dr, M_, options_, udr); end, tElapsed2 = toc(tStart2);
|
||||
|
||||
if max(max(abs(ynext1-ynext2))) > 1e-14
|
||||
error('Inconsistency between local_state_space_iteration_k and local_state_space_iteration_fortran')
|
||||
end
|
||||
|
||||
if tElapsed2<tElapsed1
|
||||
skipline()
|
||||
dprintf('local_state_space_iteration_fortran is %5.2f times faster than local_state_space_iteration_k', tElapsed1/tElapsed2)
|
||||
skipline()
|
||||
else
|
||||
skipline()
|
||||
dprintf('local_state_space_iteration_fortran is %5.2f times slower than local_state_space_iteration_k', tElapsed2/tElapsed1)
|
||||
skipline()
|
||||
end
|
||||
|
|
@ -1,8 +1,5 @@
|
|||
/*
|
||||
Tests that :
|
||||
(i) local_state_space_iteration_2, local_state_space_iteration_k and local_state_space_iteration_fortran
|
||||
(for k=2) return the same results
|
||||
(ii) local_state_space_iteration_k and local_state_space_iteration_fortran return the same results for k=3 without parallelization.
|
||||
Tests that local_state_space_iteration_2 and local_state_space_iteration_k (for k=2) return the same results
|
||||
|
||||
This file must be run after first_spec.mod (both are based on the same model).
|
||||
*/
|
||||
|
|
@ -37,8 +34,6 @@ yhat = chol(oo_.var(state_idx,state_idx))*randn(M_.npred+M_.nboth, nparticles);
|
|||
epsilon = chol(M_.Sigma_e)*randn(M_.exo_nbr, nparticles);
|
||||
|
||||
dr = oo_.dr;
|
||||
options_.threads.local_state_space_iteration_fortran = 1;
|
||||
options_.threads.local_state_space_iteration_k = 1;
|
||||
|
||||
|
||||
// “rf” stands for “Reduced Form”
|
||||
|
|
@ -52,17 +47,11 @@ rf_ghxu = dr.ghxu(dr.restrict_var_list, :);
|
|||
|
||||
tStart1 = tic; for i=1:nsims, ynext1 = local_state_space_iteration_2(yhat, epsilon, rf_ghx, rf_ghu, rf_constant, rf_ghxx, rf_ghuu, rf_ghxu, options_.threads.local_state_space_iteration_2); end, tElapsed1 = toc(tStart1);
|
||||
|
||||
tStart2 = tic; for i=1:nsims, ynext2 = local_state_space_iteration_k(yhat, epsilon, dr, M_, options_); end, tElapsed2 = toc(tStart2);
|
||||
|
||||
|
||||
tStart3 = tic; [udr] = folded_to_unfolded_dr(dr, M_, options_); for i=1:nsims, ynext3 = local_state_space_iteration_fortran(yhat, epsilon, dr, M_, options_, udr); end, tElapsed3 = toc(tStart3);
|
||||
tStart2 = tic; [udr] = folded_to_unfolded_dr(dr, M_, options_); for i=1:nsims, ynext2 = local_state_space_iteration_k(yhat, epsilon, dr, M_, options_, udr); end, tElapsed2 = toc(tStart2);
|
||||
|
||||
if max(max(abs(ynext1-ynext2))) > 1e-14
|
||||
error('Inconsistency between local_state_space_iteration_2 and local_state_space_iteration_k')
|
||||
end
|
||||
if max(max(abs(ynext1-ynext3))) > 1e-14
|
||||
error('Inconsistency between local_state_space_iteration_2 and local_state_space_iteration_fortran')
|
||||
end
|
||||
|
||||
if tElapsed1<tElapsed2
|
||||
skipline()
|
||||
|
|
@ -73,33 +62,3 @@ else
|
|||
dprintf('local_state_space_iteration_2 is %5.2f times slower than local_state_space_iteration_k', tElapsed1/tElapsed2)
|
||||
skipline()
|
||||
end
|
||||
|
||||
if tElapsed1<tElapsed3
|
||||
skipline()
|
||||
dprintf('local_state_space_iteration_2 is %5.2f times faster than local_state_space_iteration_fortran', tElapsed3/tElapsed1)
|
||||
skipline()
|
||||
else
|
||||
skipline()
|
||||
dprintf('local_state_space_iteration_2 is %5.2f times slower than local_state_space_iteration_fortran', tElapsed1/tElapsed3)
|
||||
skipline()
|
||||
end
|
||||
|
||||
stoch_simul(order=3, periods=200, irf=0, k_order_solver);
|
||||
|
||||
tStart31 = tic; for i=1:nsims, ynext31 = local_state_space_iteration_k(yhat, epsilon, oo_.dr, M_, options_); end, tElapsed31 = toc(tStart31);
|
||||
|
||||
tStart32 = tic; [udr] = folded_to_unfolded_dr(oo_.dr, M_, options_); for i=1:nsims, ynext32 = local_state_space_iteration_fortran(yhat, epsilon, oo_.dr, M_, options_, udr); end, tElapsed32 = toc(tStart32);
|
||||
|
||||
if max(max(abs(ynext31-ynext32))) > 1e-14
|
||||
error('Inconsistency between local_state_space_iteration_k and local_state_space_iteration_fortran')
|
||||
end
|
||||
|
||||
if tElapsed32<tElapsed31
|
||||
skipline()
|
||||
dprintf('local_state_space_iteration_fortran is %5.2f times faster than local_state_space_iteration_k', tElapsed31/tElapsed32)
|
||||
skipline()
|
||||
else
|
||||
skipline()
|
||||
dprintf('local_state_space_iteration_fortran is %5.2f times slower than local_state_space_iteration_k', tElapsed32/tElapsed31)
|
||||
skipline()
|
||||
end
|
||||
|
|
|
|||
Loading…
Reference in New Issue