updated figs

experiments_SNFROM/advect_fourier2D/snf.jl

@@ -32,7 +32,7 @@ grid = (128, 128,)
 
 solvestats = (;)
 
-for dt_mult in [1, 2, 5] # time-step
+for dt_mult in [1, 2, 5, 10] # time-step
     for iskip in [1, 2, 4, 8, 16] # indices
         # hyper-indices
         ids = zeros(Bool, grid...)

experiments_SNFROM/burgers_fourier2D/snf.jl

@@ -34,78 +34,81 @@ grid = (512, 512,)
 # # modeldir/results
 # postprocess_SNF(prob, datafile, modelfile; rng, device)
 
-ids = zeros(Bool, grid...)
-kk = 32
-@views ids[1:kk:end, 1:kk:end] .= true
-hyper_indices = findall(isone, vec(ids))
-
-# # modeldir/hyper
-# outdir = joinpath(modeldir, "hyper")
-# hyper_reduction_path = joinpath(modeldir, "hyper.jld2")
-# evolve_kw = (; hyper_reduction_path, hyper_indices, verbose = false,)
-# postprocess_SNF(prob, datafile, modelfile; rng, evolve_kw, outdir, device)
-
-# # modeldir/hyperDT
-# outdir = joinpath(modeldir, "hyperDT")
-# hyper_reduction_path = joinpath(modeldir, "hyperDT.jld2")
-#
-# It = LinRange(1, 500, 500) .|> Base.Fix1(round, Int)
-# data_kws = (; Ix = :, It)
-# evolve_kw = (; Δt = 10f0, data_kws, hyper_reduction_path, hyper_indices, verbose = false,)
-# postprocess_SNF(prob, datafile, modelfile; rng, evolve_kw, outdir, device)
-
-# modeldir/hyperGreedy
-outdir = joinpath(modeldir, "hyperGreedy")
-hyper_reduction_path = joinpath(modeldir, "hyperGreedy.jld2")
-
-It = LinRange(1, 500, 500) .|> Base.Fix1(round, Int)
-data_kws = (; Ix = :, It)
-evolve_kw = (; Δt = 10f0, data_kws, hyper_reduction_path, verbose = false,)
-postprocess_SNF(prob, datafile, modelfile; rng, evolve_kw, outdir, device)
+solvestats = (;)
+
+for dt_mult in [1, 2, 5, 10] # time-step
+    for iskip in [4, 8, 16, 32, 64] # indices
+        # hyper-indices
+        ids = zeros(Bool, grid...)
+        @views ids[1:iskip:end, 1:iskip:end] .= true
+        hyper_indices = findall(isone, vec(ids))
+        hyper_reduction_path = joinpath(modeldir, "hyper.jld2")
+
+        # time-step
+        It = LinRange(1, 500, 500 ÷ dt_mult) .|> Base.Fix1(round, Int)
+        data_kws = (; Ix = :, It)
+        evolve_kw = (; Δt = 10f0, data_kws, hyper_reduction_path, hyper_indices, verbose = false,)
+
+        # directory
+        N = length(hyper_indices)
+        casename = "N$(N)_dt$(dt_mult)"
+        outdir = joinpath(modeldir, "hyper_$(casename)")
+
+        # run
+        _, stats = evolve_SNF(prob, datafile, modelfile, 1; rng, outdir, evolve_kw..., device)
+
+        global solvestats = (; solvestats..., Symbol(casename) => stats)
+    end
+end
+
+statsfile = joinpath(modeldir, "hyperstats.jld2")
+jldsave(statsfile; solvestats)
+hyper_plots(datafile, modeldir, 1)
+
 #======================================================#
 
-# timing plots
-
-tme_FOM = 15.779027 # s
-mem_FOM = 163.760   # GiB
-
-Ngrid = 512 * 512
-skips = 4 .^ Array(1:6) # indices: 2, 4, 8, 16, 32, 64
-
-Nps = Ngrid ./ skips
-DTs = [1, 2, 5, 10]
-
-# s
-tme_02 = [ 44.472603 22.082768 8.903516 4.608044 ]
-tme_04 = [ 11.086413 5.557169 2.298053 1.317982 ]
-tme_08 = [ 3.148577 1.633576 0.714816 0.565096 ]
-tme_16 = [ 1.438282 0.800424 0.375744 0.152445 ]
-tme_32 = [ 0.879129 0.505148 0.203869 0.134057 ]
-tme_64 = [ 0.886587 0.453801 0.155870 0.090066 ]
-
-# GiB
-mem_02 = [ 2.132 * 1024 1.067 * 1024 437.687 219.508 ]
-mem_04 = [ 546.079 273.206 109.482 54.907 ]
-mem_08 = [ 136.819 68.451 27.431 13.757 ]
-mem_16 = [ 34.503 17.263 6.918 3.470 ]
-mem_32 = [ 8.925 4.465 1.790 919/1024 ]
-mem_64 = [ 2.530 1.266 520.059/1024 261.227/1024 ]
-
-# rel-MSE-error %
-err_02 = [ 0.057878006 0.129677 0.35801634 0.74683654 ]
-err_04 = [ 0.05751661 0.13067256 0.35610333 0.734099 ]
-err_08 = [ 0.03925267 0.105229855 0.3400021 0.69685143 ]
-err_16 = [ 0.050767798 0.11261147 0.33057037 0.7003481 ]
-err_32 = [ 0.0455603 0.103269145 0.32034075 0.7164427 ]
-err_64 = [ 0.09922275 0.05392034 0.23775052 0.5678324 ]
-
-tmes = vcat(tme_02, tme_04, tme_08, tme_16, tme_32, tme_64)
-mems = vcat(mem_02, mem_04, mem_08, mem_16, mem_32, mem_64)
-errs = vcat(err_02, err_04, err_08, err_16, err_32, err_64)
-
-# speedup
-speedups = tme_FOM ./ tmes
-memorys  = mem_FOM ./ mems
+# # timing plots
+#
+# tme_FOM = 15.779027 # s
+# mem_FOM = 163.760   # GiB
+#
+# Ngrid = 512 * 512
+# skips = 4 .^ Array(1:6) # indices: 2, 4, 8, 16, 32, 64
+#
+# Nps = Ngrid ./ skips
+# DTs = [1, 2, 5, 10]
+#
+# # s
+# tme_02 = [ 44.472603 22.082768 8.903516 4.608044 ]
+# tme_04 = [ 11.086413 5.557169 2.298053 1.317982 ]
+# tme_08 = [ 3.148577 1.633576 0.714816 0.565096 ]
+# tme_16 = [ 1.438282 0.800424 0.375744 0.152445 ]
+# tme_32 = [ 0.879129 0.505148 0.203869 0.134057 ]
+# tme_64 = [ 0.886587 0.453801 0.155870 0.090066 ]
+#
+# # GiB
+# mem_02 = [ 2.132 * 1024 1.067 * 1024 437.687 219.508 ]
+# mem_04 = [ 546.079 273.206 109.482 54.907 ]
+# mem_08 = [ 136.819 68.451 27.431 13.757 ]
+# mem_16 = [ 34.503 17.263 6.918 3.470 ]
+# mem_32 = [ 8.925 4.465 1.790 919/1024 ]
+# mem_64 = [ 2.530 1.266 520.059/1024 261.227/1024 ]
+#
+# # rel-MSE-error %
+# err_02 = [ 0.057878006 0.129677 0.35801634 0.74683654 ]
+# err_04 = [ 0.05751661 0.13067256 0.35610333 0.734099 ]
+# err_08 = [ 0.03925267 0.105229855 0.3400021 0.69685143 ]
+# err_16 = [ 0.050767798 0.11261147 0.33057037 0.7003481 ]
+# err_32 = [ 0.0455603 0.103269145 0.32034075 0.7164427 ]
+# err_64 = [ 0.09922275 0.05392034 0.23775052 0.5678324 ]
+#
+# tmes = vcat(tme_02, tme_04, tme_08, tme_16, tme_32, tme_64)
+# mems = vcat(mem_02, mem_04, mem_08, mem_16, mem_32, mem_64)
+# errs = vcat(err_02, err_04, err_08, err_16, err_32, err_64)
+#
+# # speedup
+# speedups = tme_FOM ./ tmes
+# memorys  = mem_FOM ./ mems
 
 #======================================================#
 nothing

experiments_SNFROM/compare.jl

@@ -318,10 +318,8 @@ function hyper_plots(
     mems = (;) # GPU memory
     uprs = (;) # at final time-step
 
-    data = jldopen(datafile)
-    xdata = data["x"]
-    udata = data["u"][:, :, end]
-    close(data)
+    xdata, _, _, udata, _ = loaddata(datafile)
+    udata = udata[:, :, casenum, end]
 
     for case in cases
         evolvefile = joinpath(modeldir, "hyper_" * String(case), "evolve$(casenum).jld2")