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Merged
davytorres merged 4 commits into from
Sep 15, 2022
Merged

Improve memory management #114

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11d567e
refac(matcha_s): allocate entire history at start
rouson Sep 6, 2022
a7911af
feat(input_m): increase problem size to 6k x 6k
rouson Sep 6, 2022
ecfae24
doc(t_cell_collection_m): clarify comment
rouson Sep 9, 2022
f470ba8
refac(matcha_s): match history size to # of steps
rouson Sep 9, 2022
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2 changes: 1 addition & 1 deletion src/matcha/input_m.f90
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Expand Up @@ -8,7 +8,7 @@ module input_m

type input_t
private
integer :: num_cells_ = 1000, num_positions_ = 1000, num_dimensions_ = 3, num_intervals_ = 4
integer :: num_cells_ = 6000, num_positions_ = 6000, num_dimensions_ = 3, num_intervals_ = 4
double precision :: time_step_ = 0.1D0
!double precision, allocatable :: sample_distribution_(:,:)
!allocate(sample_distribution_(num_intervals_,2))
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2 changes: 1 addition & 1 deletion src/matcha/t_cell_collection_m.f90
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Expand Up @@ -21,7 +21,7 @@ module t_cell_collection_m
interface t_cell_collection_t

pure module function construct(positions, time) result(t_cell_collection)
!! Return a t_cell_collection_t object rescaled position vectors and the provided time stamp
!! Return a t_cell_collection_t object with rescaled position vectors and the provided time stamp
implicit none
double precision, intent(in) :: positions(:,:), time
type(t_cell_collection_t) t_cell_collection
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9 changes: 5 additions & 4 deletions src/matcha_s.F90
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Expand Up @@ -49,10 +49,11 @@

associate(random_speeds => random_4vectors(:,:,1), random_directions => random_4vectors(:,:,2:4))
associate(v => distribution%velocities(random_speeds, random_directions))
history = [t_cell_collection_t(scale*random_positions, time=0.D0)]
do step = 1, nsteps
associate(x => history(step)%positions(), t => history(step)%time())
history = [history, t_cell_collection_t(x + v(:,step,:)*dt, t + dt)]
allocate(history(nsteps))
history(1) = t_cell_collection_t(scale*random_positions, time=0.D0)
do step = 2, nsteps
associate(x => history(step-1)%positions(), t => history(step-1)%time())
history(step) = t_cell_collection_t(x + v(:,step-1,:)*dt, t + dt)
end associate
end do
end associate
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