415 lines
12 KiB
Julia
415 lines
12 KiB
Julia
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using CSV
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using Plots
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pgfplotsx()
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function myfill(element, dimensions)
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res = fill(element, dimensions)
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res = map(x -> deepcopy(x), res)
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res
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end
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# Generals TODO : Fix the ticks, add legends
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#eaps = [12,13]
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eaps = [14,15]
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#eaps = [0,12,13,14,15]
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len_eaps = length(eaps)
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#types = ["S","U"]
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types = ["S"]
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#functions_identifier = ["A", "B", "C", "D", "E"]
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functions_identifier = ["F"]
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function A_index(k, x, y, z)
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if (x + k) % 64 != y
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print(string("Argh, k = ", k, ", x = ", x, ", y = ", y, ", z = ", z))
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@assert false
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end
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(x,z)
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end
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function B_index(k, x, y, z)
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@assert (x - k + 64) % 64 == y
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(x,z)
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end
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function C_index(k, x, y, z)
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@assert (y + k) % 64 == z
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(x,y)
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end
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function D_index(k, x, y, z)
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@assert (y - k + 64) % 64 == z
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(x,y)
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end
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function E_index(k, x, y, z)
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@assert (y - x + 64) % 64 == (z - y + 64) % 64
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(x, (y - x + 64) % 64)
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end
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function F_index(k, x1, x2, x3, x4)
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@assert (x1 + k + 64) % 64 == x2
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@assert (x2 + k + 64) % 64 == x4
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(x1, x3)
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end
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#functions_index = [A_index, B_index, C_index, D_index, E_index]
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functions_index = [F_index]
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#types = ["S"]
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ks = [[1, 2, 3, 4, 8],
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[1, 2, 3, 4, 8],
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[1, 2, 3, 4, 8],
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[1, 2, 3, 4, 8],
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[2, 3, 4]
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]
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ks = [[4, 3, 2, 1, -1, -2, -3, -4]]
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#ks = [[1]]
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methods = ["SF", "SR", "FF"]
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plot_lock = ReentrantLock()
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slices_offset_0 = [0, 1, 2, 8, 14, 15, 30, 31, 32, 55, 56, 61, 62, 63]
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#slices_offset_0 = []
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#diff_slices_offset_0 = [0, 1, 2, 61, 62, 63]
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function make_name(eap, type, f, k)
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string("bonusap/bonusap-with-", eap, "-prefetcher.", type, f, k, ".csv")
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end
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all_file_names = myfill((0,0,0,[]), (length(eaps), length(types), length(functions_index)))
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for x in 1:len_eaps
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for (y,type) in enumerate(types)
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for (z,f) in enumerate(functions_identifier)
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all_file_names[x,y,z] = (x,y,z,[])
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for (i,k) in enumerate(ks[z])
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# change me : insert file names into list
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push!(all_file_names[x,y,z][4] , (x, y, z, k, make_name(eaps[x], type, f, k) ) )
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end
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end
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end
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end
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print(all_file_names)
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#files = Matrix(CSV, length(eaps), length(types), length(levels))
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files = Array{
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Union{
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Nothing,
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Tuple{Int64, Int64, Int64, Vector{
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Tuple{ Int64, Int64, Int64, Int64, CSV.File }
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}}
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},3
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}(nothing, length(eaps), length(types), length(functions_identifier))
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Threads.@threads for f in all_file_names
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x = f[1]
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y = f[2]
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z = f[3]
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files[x,y,z] = (x,y,z,[])
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for (x,y,z,k,name) in f[4]
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push!(files[x,y,z][4], (x,y,z,k, CSV.File(name)))
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end
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end
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# TODO :
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#
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# - Split this function in a load data into square / cube structure and a plot function
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# - Refactor the code below to compute the various squares / cubes and then do the plots.
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# - Refactor the Slicing function too
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# - Create a custom diagonal slice function ?
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preamble_printed = false
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push!(PGFPlotsX.CUSTOM_PREAMBLE,raw"\newcommand{\gdfigurewidth}{150mm}")
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push!(PGFPlotsX.CUSTOM_PREAMBLE,raw"\newcommand{\gdfigureheight}{100mm}")
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function graph2d(name, matrix, xlabel, ylabel)
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x = range(0, 63)
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y = range(0, 63)
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function hmp2d(x, y)
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matrix[x + 1, y + 1]
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end
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lock(plot_lock) do
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graph = heatmap(x, y, hmp2d, minorgrid=true, height = raw"{\gdfigureheight}}, width = {{\gdfigurewidth}", xlabel = xlabel, ylabel = ylabel, c = :blues, extra_kwargs =:subplot)
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if !preamble_printed
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global preamble_printed = true
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print(Plots.pgfx_preamble(graph))
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end
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savefig(graph, string(name, ".tikz"))
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savefig(graph, string(name, ".pdf"))
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end
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end
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function graph2dclims(name, matrix, clims, xlabel, ylabel)
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x = range(0, 63)
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y = range(0, 63)
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function hmp2d(x, y)
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matrix[x + 1, y + 1]
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end
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lock(plot_lock) do
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graph = heatmap(x, y, hmp2d, clims = clims, minorgrid=true, height = raw"{\gdfigureheight}}, width = {{\gdfigurewidth}", xlabel = xlabel, ylabel = ylabel, extra_kwargs =:subplot)
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savefig(graph, string(name, ".tikz"))
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savefig(graph, string(name, ".pdf"))
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end
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end
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function cube_flatten_z(cubes)
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len = length(cubes)
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res = myfill(myfill(0.0,(64,64)), len)
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for k in range(1,64)
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Threads.@threads for i in range(1,64)
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for j in range(1,64)
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for l in range(1,len)
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res[l][i,j] += cubes[l][i,j,k]
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end
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end
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end
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end
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res
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end
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function slice_extract_x(cubes, slices)
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slice_length = length(slices)
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cube_length = length(cubes)
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res = myfill(myfill(myfill(0.0, (64, 64)), slice_length), cube_length)
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for i in range(1,64)
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for j in range(1,64)
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for (k,slice) in enumerate(slices)
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for l in range(1, cube_length)
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res[l][k][i, j] = cubes[l][slice+1, i, j]
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end
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end
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end
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end
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res
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end
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function graph_2(basename, csv, k, index_function)
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result = fill(-1.0, (3, 64,64,64))
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# Fill in the 3D cube, then create the various slices and flattenings
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# Flattened Cube with x = first addr, y = second addr, compute the sum of prefetches ?
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# Grab a few random first adresses and look at them with x = second addr, y = probe addr
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# 0,1, 62,63 14, 15 plus one other depending on what appears
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for row in csv
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probe = row.ProbeAddr
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offset_0 = Int64(row.Offset_0)
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offset_1 = Int64(row.Offset_1)
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offset_2 = Int64(row.Offset_2)
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offset_3 = Int64(row.Offset_3)
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index = index_function(k, offset_0, offset_1, offset_2, offset_3)
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i = index[1] + 1
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j = index[2] + 1
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@assert result[:, i, j, probe + 1] == [-1.0,-1.0,-1.0]
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result[1, i, j, probe + 1] = row.Probe_SF_HR
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result[2, i, j, probe + 1] = row.Probe_SR_HR
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result[3, i, j, probe + 1] = row.Probe_FF_HR
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end
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allprobes = cube_flatten_z([result[1,:,:,:], result[2,:,:,:], result[3,:,:,:]])
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sf_probe_heatmap_allprobes = allprobes[1]
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sr_probe_heatmap_allprobes = allprobes[2]
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ff_probe_heatmap_allprobes = allprobes[3]
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all_slices = slice_extract_x([result[1,:,:,:], result[2,:,:,:], result[3,:,:,:]], slices_offset_0)
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sf_probe_slices_heatmaps = all_slices[1]
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sr_probe_slices_heatmaps = all_slices[2]
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ff_probe_slices_heatmaps = all_slices[3]
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graph2d(string(basename, "_SF_AllProbes"), sf_probe_heatmap_allprobes, "i", "j")
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graph2d(string(basename, "_SR_AllProbes"), sr_probe_heatmap_allprobes, "i", "j")
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graph2d(string(basename, "_FF_AllProbes"), ff_probe_heatmap_allprobes, "i", "j")
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for (i, offset_0) in enumerate(slices_offset_0)
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print(offset_0)
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data = sf_probe_slices_heatmaps[i]
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graph2dclims(string(basename, "_SF_Slice_", offset_0),sf_probe_slices_heatmaps[i],(0,1), "j", "probe")
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graph2dclims(string(basename, "_SR_Slice_", offset_0),sr_probe_slices_heatmaps[i],(0,1), "j", "probe")
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graph2dclims(string(basename, "_FF_Slice_", offset_0),ff_probe_slices_heatmaps[i],(0,1), "j", "probe")
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end
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result
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end
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cubes = myfill([], (length(eaps), length(types), length(functions_identifier)))
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# need to push (k, cube)
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Threads.@threads for experiment in files
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for (eap, type, f, k, file) in experiment[4]
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name = string(eaps[eap], "/julia_eap_", eaps[eap], "_", types[type], functions_identifier[f], k)
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print(string(name,"\n"))
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cube_3 = graph_2(name, file, k, functions_index[f])
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push!(cubes[eap, type, f], cube_3)
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end
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end
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if false
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print("Computing 14 union 13...")
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function cube_max(cubes_1, cubes_2)
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@assert size(cubes_1) == size(cubes_2)
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sizes = size(cubes_1)
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@assert length(sizes) == 5
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res = fill(0.0, sizes)
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for i in range(1,sizes[1])
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for j in range(1,sizes[2])
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Threads.@threads for k in range(1,64)
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for l in range(1, 64)
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for m in range(1, 64)
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res[i,j,k,l,m] = max(cubes_1[i,j,k,l,m], cubes_2[i,j,k,l,m])
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end
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end
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end
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end
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end
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res
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end
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index_0 = findfirst(isequal(0), eaps)
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index_12 = findfirst(isequal(12), eaps)
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index_13 = findfirst(isequal(13), eaps)
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index_14 = findfirst(isequal(14), eaps)
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cube_max_13_14 = cube_max(cubes[index_13,:,:,:,:,:], cubes[index_14,:,:,:,:,:])
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function do_cubes(name, cubes)
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cube_list = []
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index_list = []
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for type in range(1,length(types))
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for method in range(1,3)
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push!(cube_list, cubes[type,method,:,:,:])
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push!(index_list, (type, method))
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end
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end
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allgraphs = cube_flatten_z(cube_list)
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for (i,(type,method)) in enumerate(index_list)
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graph2d(string(name, "_", types[type], "2_", methods[method], "_AllProbes"), allgraphs[i], "i", "j")
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for slice in diff_slices_offset_0
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graph2d(string(name,"_", types[type], "2_", methods[method], "_Slice_", slice), cubes[type, method, slice+1,:,:], "j", "probe")
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end
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end
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end
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graph_13_14 = @task begin
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do_cubes("julia_max_13_14", cube_max_13_14)
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#cube_list = []
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#index_list = []
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#for type in range(1,length(types))
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# for method in range(1,3)
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# push!(cube_list, cube_max_13_14[type,method,:,:,:])
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# push!(index_list, (type, method))
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# end
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#end
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#allgraphs = cube_flatten_z(cube_list)
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#for (i,(type,method)) in enumerate(index_list)
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# graph2d(string("julia_max_13_14_", types[type], "2_", methods[method], "_AllProbes"), allgraphs[i], "i", "j")
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#end
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end
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schedule(graph_13_14)
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print(" OK\n")
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print("Computing Any difference between 0 and 12...")
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function cube_differences(cubes_1, cubes_2)
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@assert size(cubes_1) == size(cubes_2)
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sizes = size(cubes_1)
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@assert length(sizes) == 5
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res = fill(0.0, sizes)
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for i in range(1,sizes[1])
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for j in range(1,sizes[2])
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Threads.@threads for k in range(1,64)
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||
|
|
for l in range(1, 64)
|
||
|
|
for m in range(1, 64)
|
||
|
|
res[i,j,k,l,m] = abs(cubes_1[i,j,k,l,m] - cubes_2[i,j,k,l,m])
|
||
|
|
end
|
||
|
|
end
|
||
|
|
end
|
||
|
|
end
|
||
|
|
end
|
||
|
|
res
|
||
|
|
end
|
||
|
|
|
||
|
|
cube_diff_0_12 = cube_differences(cubes[index_0,:,:,:,:,:], cubes[index_12,:,:,:,:,:])
|
||
|
|
|
||
|
|
graph_0_12 = @task begin
|
||
|
|
do_cubes("julia_diff_0_12", cube_diff_0_12)
|
||
|
|
#cube_list = []
|
||
|
|
#index_list = []
|
||
|
|
#for type in range(1,length(types))
|
||
|
|
# for method in range(1,3)
|
||
|
|
# push!(cube_list, cube_diff_0_12[type,method,:,:,:])
|
||
|
|
# push!(index_list, (type, method))
|
||
|
|
# end
|
||
|
|
#end
|
||
|
|
#allgraphs = cube_flatten_z(cube_list)
|
||
|
|
#for (i,(type,method)) in enumerate(index_list)
|
||
|
|
# graph2d(string("julia_diff_0_12_", types[type], "2_", methods[method], "_AllProbes"), allgraphs[i], "i", "j")
|
||
|
|
#end
|
||
|
|
end
|
||
|
|
schedule(graph_0_12)
|
||
|
|
|
||
|
|
print(" OK\n")
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
print("Computing Differences between 12 and (13 union 14)...")
|
||
|
|
|
||
|
|
cube_diff_12_1314 = cube_differences(cubes[index_0,:,:,:,:,:], cube_max_13_14)
|
||
|
|
|
||
|
|
graph_12_1314 = @task begin
|
||
|
|
do_cubes("julia_diff_12_1314", cube_diff_12_1314)
|
||
|
|
#cube_list = []
|
||
|
|
#index_list = []
|
||
|
|
#for type in range(1,length(types))
|
||
|
|
# for method in range(1,3)
|
||
|
|
# push!(cube_list, cube_diff_12_1314[type,method,:,:,:])
|
||
|
|
# push!(index_list, (type, method))
|
||
|
|
# end
|
||
|
|
#end
|
||
|
|
#allgraphs = cube_flatten_z(cube_list)
|
||
|
|
#for (i,(type,method)) in enumerate(index_list)
|
||
|
|
# graph2d(string("julia_diff_12_1314", types[type], "2_", methods[method], "_AllProbes"), allgraphs[i], "i", "j")
|
||
|
|
# for slice in diff_slices_offset_0
|
||
|
|
#
|
||
|
|
# end
|
||
|
|
#end
|
||
|
|
end
|
||
|
|
schedule(graph_12_1314)
|
||
|
|
|
||
|
|
wait(graph_13_14)
|
||
|
|
wait(graph_0_12)
|
||
|
|
wait(graph_12_1314)
|
||
|
|
print("done\n")
|
||
|
|
|
||
|
|
end
|