Merge pull request #2892 from CliMA/ck/scaling_plot_utils

Rm code dup, rm some prints, tabulate scaling

Author: charleskawczynski

.buildkite/gpu_pipeline/pipeline.yml

@@ -161,7 +161,7 @@ steps:
           - mkdir -p gpu_aquaplanet_dyamond_ss
           - >
             julia --color=yes --project=examples post_processing/plot_gpu_strong_scaling.jl gpu_aquaplanet_dyamond_ss
-        artifact_paths: "gpu_aquaplanet_dyamond_ss/output_active/*"
+        artifact_paths: "gpu_aquaplanet_dyamond_ss/*"
         agents:
           slurm_cpus_per_task: 1
           slurm_ntasks: 1
@@ -225,7 +225,7 @@ steps:
           - mkdir -p gpu_aquaplanet_dyamond_ws
           - >
             julia --color=yes --project=examples post_processing/plot_gpu_weak_scaling.jl gpu_aquaplanet_dyamond_ws
-        artifact_paths: "gpu_aquaplanet_dyamond_ws/output_active/*"
+        artifact_paths: "gpu_aquaplanet_dyamond_ws/*"
         agents:
           slurm_cpus_per_task: 1
           slurm_ntasks: 1

post_processing/plot_gpu_scaling_utils.jl

@@ -1,5 +1,10 @@
 using JLD2
-function get_jld2data(output_dir, job_id, s)
+import PrettyTables as PT
+
+function get_jld2data(output_dir, job_id, t_int_days, s)
+    secs_per_day = 60 * 60 * 24
+    secs_per_hour = 60 * 60
+    days_per_year = 8760 / 24
     FT = Float64
     nprocs_clima_atmos = Int[]
     ncols_per_process = Int[]
@@ -22,16 +27,46 @@ function get_jld2data(output_dir, job_id, s)
             push!(nprocs_clima_atmos, Int(dict["nprocs"]))
             push!(ncols_per_process, Int(dict["ncols_per_process"]))
             push!(walltime_clima_atmos, FT(dict["walltime"]))
-        else
-            @show occursin(job_id, foldername)
-            @show occursin(s, foldername)
+            found = true
         end
     end
     if !found
         @show readdir(output_dir)
+        for foldername in readdir(output_dir)
+            @show occursin(job_id, foldername)
+            @show occursin(s, foldername)
+        end
     end
-    @show nprocs_clima_atmos
-    @show ncols_per_process
-    @show walltime_clima_atmos
-    return (; nprocs_clima_atmos, ncols_per_process, walltime_clima_atmos)
+    order = sortperm(nprocs_clima_atmos)
+    nprocs_clima_atmos, ncols_per_process, walltime_clima_atmos =
+        nprocs_clima_atmos[order],
+        ncols_per_process[order],
+        walltime_clima_atmos[order]
+
+    # simulated years per day
+    sypd_clima_atmos =
+        (secs_per_day ./ walltime_clima_atmos) * t_int_days ./ days_per_year
+
+    # GPU hours
+    gpu_hours_clima_atmos =
+        nprocs_clima_atmos .* walltime_clima_atmos / secs_per_hour
+
+    data = hcat(
+        nprocs_clima_atmos,
+        ncols_per_process,
+        walltime_clima_atmos,
+        sypd_clima_atmos,
+    )
+    PT.pretty_table(
+        data;
+        header = ["N procs", "Ncols per process", "walltime (seconds)", "SYPD"],
+        alignment = :l,
+    )
+    return (;
+        nprocs_clima_atmos,
+        ncols_per_process,
+        walltime_clima_atmos,
+        sypd_clima_atmos,
+        gpu_hours_clima_atmos,
+    )
 end

post_processing/plot_gpu_strong_scaling.jl

@@ -6,10 +6,6 @@ include("plot_gpu_scaling_utils.jl")
 job_id = "gpu_aquaplanet_dyamond_ss"
 output_dir = "./"
 
-secs_per_hour = 60 * 60
-secs_per_day = 60 * 60 * 24
-days_per_year = 8760 / 24
-
 t_int_days = 12 / 24 # simulation integration time in days
 h_elem = 30
 z_elem = 63
@@ -18,21 +14,14 @@ nlevels = z_elem + 1
 t_int = string(t_int_days) * " days"
 
 # read ClimaAtmos scaling data
-(; nprocs_clima_atmos, ncols_per_process, walltime_clima_atmos) =
-    get_jld2data(output_dir, job_id, "_ss_")
-
-order = sortperm(nprocs_clima_atmos)
-nprocs_clima_atmos, ncols_per_process, walltime_clima_atmos =
-    nprocs_clima_atmos[order],
-    ncols_per_process[order],
-    walltime_clima_atmos[order]
+(;
+    nprocs_clima_atmos,
+    ncols_per_process,
+    walltime_clima_atmos,
+    sypd_clima_atmos,
+    gpu_hours_clima_atmos,
+) = get_jld2data(output_dir, job_id, t_int_days, "_ss_")
 
-# simulated years per day
-sypd_clima_atmos =
-    (secs_per_day ./ walltime_clima_atmos) * t_int_days ./ days_per_year
-# GPU hours
-gpu_hours_clima_atmos =
-    nprocs_clima_atmos .* walltime_clima_atmos / secs_per_hour
 # scaling efficiency
 single_proc_time_clima_atmos = walltime_clima_atmos[1] * nprocs_clima_atmos[1]
 scaling_efficiency_clima_atmos =

post_processing/plot_gpu_weak_scaling.jl

@@ -6,10 +6,6 @@ include("plot_gpu_scaling_utils.jl")
 job_id = "gpu_aquaplanet_dyamond_ws"
 output_dir = "./"
 
-secs_per_hour = 60 * 60
-secs_per_day = 60 * 60 * 24
-days_per_year = 8760 / 24
-
 t_int_days = 12 / 24 # simulation integration time in days
 h_elem = [30, 42, 60]
 z_elem = 63
@@ -18,21 +14,14 @@ nlevels = z_elem + 1
 t_int = string(t_int_days) * " days"
 
 # read ClimaAtmos scaling data
-(; nprocs_clima_atmos, ncols_per_process, walltime_clima_atmos) =
-    get_jld2data(output_dir, job_id, "_ws_")
-
-order = sortperm(nprocs_clima_atmos)
-nprocs_clima_atmos, ncols_per_process, walltime_clima_atmos =
-    nprocs_clima_atmos[order],
-    ncols_per_process[order],
-    walltime_clima_atmos[order]
+(;
+    nprocs_clima_atmos,
+    ncols_per_process,
+    walltime_clima_atmos,
+    sypd_clima_atmos,
+    gpu_hours_clima_atmos,
+) = get_jld2data(output_dir, job_id, t_int_days, "_ws_")
 
-# simulated years per day
-sypd_clima_atmos =
-    (secs_per_day ./ walltime_clima_atmos) * t_int_days ./ days_per_year
-# GPU hours
-gpu_hours_clima_atmos =
-    nprocs_clima_atmos .* walltime_clima_atmos / secs_per_hour
 # weak scaling efficiency
 single_proc_time_clima_atmos = walltime_clima_atmos[1] * nprocs_clima_atmos[1]
 weak_scaling_efficiency_clima_atmos =