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milan@dhcp-10-29-133-232 output % julia -p 2 ensembles.jl
Weather is speedy: run 0001 100%|█████████| Time: 0:00:07 (322.97 years/day)
Weather is speedy: run 0006 100%|█████████| Time: 0:00:07 (326.40 years/day)
Weather is speedy: run 0002 100%|█████████| Time: 0:00:05 (439.79 years/day)
Weather is speedy: run 0007 100%|█████████| Time: 0:00:05 (441.00 years/day)
Weather is speedy: run 0003 100%|█████████| Time: 0:00:05 (411.43 years/day)
Weather is speedy: run 0008 100%|█████████| Time: 0:00:05 (403.73 years/day)
Weather is speedy: run 0004 100%|█████████| Time: 0:00:05 (420.51 years/day)
Weather is speedy: run 0009 100%|█████████| Time: 0:00:05 (417.16 years/day)
Weather is speedy: run 0005 100%|█████████| Time: 0:00:05 (414.74 years/day)
Weather is speedy: run 0010 100%|█████████| Time: 0:00:05 (422.55 years/day)
So worker 1 took run 0001, worker 2 run 0006, then worker 1 again run 0002, etc. Every sample takes somewhat longer than the 5-7 seconds here as it excludes the initialization, which is currently redone for simplicity.
The text was updated successfully, but these errors were encountered:
One of the problems above is that a given process actually reinitializes the whole model including all memory allocation. We're missing a fill!(::PrognosticVariables,0) function or similar. Maybe a general set!(::PrognosticVariables,...) like Oceananigans does it. Here's an example ensembles script that tries to avoid reallocation
@ningliu-iga With the following code you can run ensemble simulations in parallel, save as
ensembles.jl
and execute withwhere
N
is the number of processors you want to use.which prints
So worker 1 took run 0001, worker 2 run 0006, then worker 1 again run 0002, etc. Every sample takes somewhat longer than the 5-7 seconds here as it excludes the initialization, which is currently redone for simplicity.
The text was updated successfully, but these errors were encountered: