data/evaluate_reduce_bench.jl

@@ -0,0 +1,119 @@
+using Plots
+using StatsPlots
+using CSV
+using DataFrames
+using LaTeXStrings
+
+
+if (length(ARGS) < 2)
+    println("Please use with \"input_file.csv\" \"input_file_gpu.csv\"")
+end
+
+
+function proc_to_n(str::AbstractString)
+    parts = split(str, "'")
+    parts = split(parts[2], "->")
+    k_count = count(c -> c == 'k', parts[2])
+    return k_count
+end
+
+function beautify_title(str::AbstractString)
+    parts = split(str, "->")
+
+    prefix = parts[1]
+    suffix = parts[2]
+
+    k_count = count(c -> c == 'k', suffix)
+    B_count = count(c -> c == 'B', suffix)
+
+    if k_count == 1 || B_count == 1
+        new_suffix = suffix
+    elseif k_count >= 1
+        new_suffix = replace(suffix, r"k+" => "k^$k_count")
+    elseif B_count >= 1
+        new_suffix = replace(suffix, r"B+" => "B^$B_count")
+    end
+
+    return L"%$prefix \rightarrow %$new_suffix"
+end
+
+processes =
+    ["ke->ke", "ke->kke", "ke->kkke", "ke->kkkke", "ke->kkkkke", "AB->AB", "AB->ABBB", "AB->ABBBBB", "AB->ABBBBBBB"]
+
+input_file = ARGS[1]
+input_file_gpu = ARGS[2]
+df = CSV.read(input_file, DataFrame)
+df_gpu = CSV.read(input_file_gpu, DataFrame)
+n_inputs = 50_000
+
+
+for process in processes
+    df_filt = filter(:process => x -> x == process, df)
+    df_filt_gpu = filter(:process => x -> x == process, df_gpu)
+
+    cpu = !isempty(df_filt)
+    gpu = !isempty(df_filt_gpu)
+
+    ymax = 0.0
+
+    if cpu
+        @df df_filt scatter(
+            :operations,
+            :cumulative_optimization_time,
+            label = "Cumulative Optimization Time (s)",
+            markersize = 7,
+        )
+        ymax = max(df_filt[!, :cpu_st_t]..., df_filt[!, :cumulative_optimization_time]...) * 1.1
+        @df df_filt scatter!(
+            :operations,
+            :cpu_st_t,
+            label = "Single-Threaded Execution (s)",
+            markersize = 7,
+            markershape = :square,
+        )
+    end
+
+    if gpu
+        if !cpu
+            @df df_filt_gpu scatter(
+                :operations,
+                :cumulative_optimization_time,
+                label = "Cumulative Optimization Time (s)",
+                markersize = 7,
+            )
+            ymax = max(df_filt_gpu[!, :gpu_t]..., df_filt_gpu[!, :cumulative_optimization_time]...) * 1.1
+        end
+
+        @df df_filt_gpu scatter!(
+            :operations,
+            :gpu_t,
+            label = "GPU Execution (s)",
+            markersize = 7,
+            markershape = :diamond,
+        )
+    end
+
+    if cpu || gpu
+        plot!(
+            title = ("$(beautify_title(process)) Reduction Progression ($(n_inputs) Inputs)"),
+            xscale = :linear,
+            yscale = :linear,
+            ylim = (0, ymax),
+            legend = :outerbottom,
+            minorgrid = true,
+            xticks = :process_size,
+            #yticks = [1e-3, 1e-1, 1e1, 1e3],
+            xgrid = false,
+            xminorticks = false,
+            legendcolumns = 1,
+            legend_font_pointsize = 12,
+            fontsize = 12,
+            size = (800, 600),
+            xlabel = "optimizer steps (#)",
+            ylabel = "time (s)",
+        )
+
+        savefig("$(String(process))_reduction_bench.pdf")
+    end
+end
+