Merge pull request #176 from BerkeleyLab/julienne-2.0.0

Switch to Julienne 2.0.0 and Assert 2.1.0

Author: rouson

.github/workflows/deploy-docs.yml

@@ -2,14 +2,9 @@ name: Build and Deploy Documentation
 
 on: [push, pull_request]
 
-
 jobs:
   Build:
-    runs-on: ubuntu-latest
-
-    env:
-      FC: gfortran
-      GCC_V: 14
+    runs-on: ubuntu-22.04
 
     steps:
     - name: Checkout code
@@ -18,17 +13,13 @@ jobs:
     - name: Install Dependencies Ubuntu
       run: |
         sudo apt-get update
-        sudo apt install -y gfortran-${GCC_V} python3-dev python3 build-essential numdiff graphviz
-        sudo pip install ford markdown
-        echo "---------"
-        gfortran --version
-        echo "---------"
+        sudo apt install -y python3-dev python3 build-essential graphviz
+        sudo python3 -m pip install ford
+
     - name: Build Developer Documenation
       run: |
-        # Turn warnings into errors
-        ford ford.md > ford_output.txt
-        cat ford_output.txt; if grep -q -i Warning ford_output.txt; then exit 1; fi
-        cp ./README.md ./doc/html
+        ford ford.md
+
     - name: Upload Documentation
       uses: actions/upload-artifact@v4
       with:

fpm.toml

@@ -6,5 +6,5 @@ maintainer = "rouson@lbl.gov"
 
 [dependencies]
 assert = {git = "https://github.com/berkeleylab/assert", tag = "2.1.0"}
-julienne = {git = "https://github.com/BerkeleyLab/julienne", tag = "1.8.4"}
+julienne = {git = "https://github.com/BerkeleyLab/julienne", tag = "2.0.0"}
 sourcery = {git = "https://github.com/sourceryinstitute/sourcery", tag = "4.5.1"}

include/language-support.F90

@@ -0,0 +1,23 @@
+! Copyright (c), The Regents of the University of California
+! Terms of use are as specified in LICENSE.txt
+
+#ifndef HAVE_PROCEDURE_ACTUAL_FOR_POINTER_DUMMY
+  ! Define whether the compiler supports associating a procedure pointer dummy argument with an
+  ! actual argument that is a valid target for the pointer dummy in a procedure assignment, a
+  ! feature introduced in Fortran 2008 and described in Fortran 2023 clause 15.5.2.10 paragraph 5.
+#if defined(_CRAYFTN) || defined(__INTEL_COMPILER) || defined(NAGFOR) || defined(__flang__)
+#define HAVE_PROCEDURE_ACTUAL_FOR_POINTER_DUMMY 1
+#else
+#define HAVE_PROCEDURE_ACTUAL_FOR_POINTER_DUMMY 0
+#endif
+#endif
+
+#ifndef HAVE_MULTI_IMAGE_SUPPORT
+  ! Define whether the compiler supports the statements and intrinsic procedures that support
+  ! multi-image execution, e.g., this_image(), sync all, etc.
+#if defined(_CRAYFTN) || defined(__INTEL_COMPILER) || defined(NAGFOR) || defined(__GFORTRAN__)
+#define HAVE_MULTI_IMAGE_SUPPORT 1
+#else
+#define HAVE_MULTI_IMAGE_SUPPORT 0
+#endif
+#endif

src/matcha/distribution_s.F90

@@ -1,9 +1,11 @@
 ! Copyright (c), The Regents of the University of California
 ! Terms of use are as specified in LICENSE.tx
+
+#include "assert_macros.h"
+
 submodule(distribution_m) distribution_s
+  use assert_m
   use intrinsic_array_m, only : intrinsic_array_t
-  use do_concurrent_m, only : do_concurrent_sampled_speeds, do_concurrent_my_velocities
-  use assert_m, only : assert
   implicit none
 
 contains
@@ -18,54 +20,57 @@ pure function monotonically_increasing(f) result(monotonic)
   module procedure construct
     integer i
 
-    call assert(all(sample_distribution(:,2)>=0.D0), "distribution_t%construct: sample_distribution>=0.", &
-      intrinsic_array_t(sample_distribution))
+    call_assert_diagnose(all(sample_distribution(:,2)>=0.D0), "distribution_t%construct: sample_distribution>=0.", intrinsic_array_t(sample_distribution))
 
     associate(nintervals => size(sample_distribution,1))      
       distribution%vel_ = [(sample_distribution(i,1), i =1, nintervals)]  ! Assign speeds to each distribution bin         
       distribution%cumulative_distribution_ = [0.D0, [(sum(sample_distribution(1:i,2)), i=1, nintervals)]]
-
-      call assert(monotonically_increasing(distribution%cumulative_distribution_), &
-        "distribution_t: monotonically_increasing(distribution%cumulative_distribution_)", &
-        intrinsic_array_t(distribution%cumulative_distribution_))
     end associate
 
+    call_assert_diagnose(monotonically_increasing(distribution%cumulative_distribution_), "distribution_t: monotonically increasing cumulative distribution", intrinsic_array_t(distribution%cumulative_distribution_))
+
   end procedure construct
 
   module procedure cumulative_distribution
-    call assert(allocated(self%cumulative_distribution_), &
-      "distribution_t%cumulative_distribution: allocated(cumulative_distribution_)")
+    call_assert(allocated(self%cumulative_distribution_))
     my_cumulative_distribution = self%cumulative_distribution_
   end procedure 
 
   module procedure velocities
 
     double precision, allocatable :: sampled_speeds(:,:),  dir(:,:,:)
-    integer step
+    integer cell, step, k
 
-    call assert(allocated(self%cumulative_distribution_), &
-      "distribution_t%cumulative_distribution: allocated(cumulative_distribution_)")
-    call assert(allocated(self%vel_), "distribution_t%cumulative_distribution: allocated(vel_)")
+    call_assert(allocated(self%cumulative_distribution_)) 
+    call_assert(allocated(self%vel_))
 
-     ! Sample from the distribution
-     call do_concurrent_sampled_speeds(speeds, self%vel_, self%cumulative_distribution(), sampled_speeds)
-     
-     associate(nsteps => size(speeds,2))
+    ! Sample from the distribution
+    associate(ncells => size(speeds,1), nsteps => size(speeds,2))
+      allocate(sampled_speeds(ncells,nsteps))
+      do concurrent(cell = 1:ncells, step = 1:nsteps)
+        k = findloc(speeds(cell,step) >= self%cumulative_distribution(), value=.false., dim=1)-1
+        sampled_speeds(cell,step) = self%vel_(k)
+      end do
+      
+      ! Create unit vectors
+      dir = directions(:,1:nsteps,:)
 
-       ! Create unit vectors
-       dir = directions(:,1:nsteps,:)
+      associate(dir_mag => sqrt(dir(:,:,1)**2 +dir(:,:,2)**2 + dir(:,:,3)**2))
+        associate(dir_mag_ => merge(dir_mag, epsilon(dir_mag), dir_mag/=0.))
+          dir(:,:,1) = dir(:,:,1)/dir_mag_
+          dir(:,:,2) = dir(:,:,2)/dir_mag_
+          dir(:,:,3) = dir(:,:,3)/dir_mag_
+        end associate
+      end associate
 
-       associate(dir_mag => sqrt(dir(:,:,1)**2 +dir(:,:,2)**2 + dir(:,:,3)**2))
-         associate(dir_mag_ => merge(dir_mag, epsilon(dir_mag), dir_mag/=0.))
-           dir(:,:,1) = dir(:,:,1)/dir_mag_
-           dir(:,:,2) = dir(:,:,2)/dir_mag_
-           dir(:,:,3) = dir(:,:,3)/dir_mag_
-         end associate
-       end associate
-       
-       call do_concurrent_my_velocities(nsteps, dir, sampled_speeds, my_velocities)
-       
-     end associate
+      allocate(my_velocities, mold=dir)
+      
+      do concurrent(step=1:nsteps)
+        my_velocities(:,step,1) = sampled_speeds(:,step)*dir(:,step,1)
+        my_velocities(:,step,2) = sampled_speeds(:,step)*dir(:,step,2)
+        my_velocities(:,step,3) = sampled_speeds(:,step)*dir(:,step,3)
+      end do
+    end associate
 
   end procedure
 

src/matcha/do_concurrent_m.f90

@@ -33,7 +33,7 @@ pure module function construct(input, history) result(output)
 
   interface
 
-    module function simulated_distribution(self) result(output_distribution)
+    pure module function simulated_distribution(self) result(output_distribution)
       !! The result is a histogram calculated from the simulation output
       implicit none
       class(output_t), intent(in) :: self