Add analysis scripts, format and fix spelling of prefetcher_reverse/Readme.md
Squash of 4 cherry-picked commits: 569f3aaf26469c6f37ecf338f32fd8d6222575fb 1b93a2a951a9a6eea123806b1d557634e9333665 6e5b5c5807a83758ba321e405901377a532734c1 25ccd3248fa0a87e454363698d2ad2bba0588e37
This commit is contained in:
Guillaume DIDIER
parent
0765552240
commit
bc684eca89
7
analysis/change_colour_map.sh
Executable file
7
analysis/change_colour_map.sh
Executable file
@ -0,0 +1,7 @@
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#!/bin/sh
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sed -i.old 's/plots1/squarecolourmap/g' */_/1/*{FF,SF,SR}.tikz
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sed -i.old 's/plots1/cubecolourmap/g' */*/*/*AllProbes.tikz
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sed -i.old 's/plots1/slicecolourmap/g' */*/*/*Slice_*.tikz
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sed -i.old 's/plots1/maxcolourmap/g' max_*/*.tikz
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sed -i.old 's/plots1/diffcolourmap/g' diff_*/*.tikz
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128
analysis/extract_analysis_csv.sh
Executable file
128
analysis/extract_analysis_csv.sh
Executable file
@ -0,0 +1,128 @@
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#!/bin/sh
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grep '^SingleIP0:' "$1.log" | cut -b 11- > "$1.S0.csv"
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grep '^UniqueIPs0:' "$1.log" | cut -b 12- > "$1.U0.csv"
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grep '^SingleIP1:' "$1.log" | cut -b 11- > "$1.S1.csv"
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grep '^UniqueIPs1:' "$1.log" | cut -b 12- > "$1.U1.csv"
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grep '^SingleIP2:' "$1.log" | cut -b 11- > "$1.S2.csv"
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grep '^UniqueIPs2:' "$1.log" | cut -b 12- > "$1.U2.csv"
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grep '^SingleIPA1:' "$1.log" | cut -b 12- > "$1.SA1.csv"
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grep '^UniqueIPsA1:' "$1.log" | cut -b 13- > "$1.UA1.csv"
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grep '^SingleIPA2:' "$1.log" | cut -b 12- > "$1.SA2.csv"
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grep '^UniqueIPsA2:' "$1.log" | cut -b 13- > "$1.UA2.csv"
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grep '^SingleIPA3:' "$1.log" | cut -b 12- > "$1.SA3.csv"
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grep '^UniqueIPsA3:' "$1.log" | cut -b 13- > "$1.UA3.csv"
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grep '^SingleIPA4:' "$1.log" | cut -b 12- > "$1.SA4.csv"
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grep '^UniqueIPsA4:' "$1.log" | cut -b 13- > "$1.UA4.csv"
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grep '^SingleIPA8:' "$1.log" | cut -b 12- > "$1.SA8.csv"
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grep '^UniqueIPsA8:' "$1.log" | cut -b 13- > "$1.UA8.csv"
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grep '^SingleIPB1:' "$1.log" | cut -b 12- > "$1.SB1.csv"
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grep '^UniqueIPsB1:' "$1.log" | cut -b 13- > "$1.UB1.csv"
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grep '^SingleIPB2:' "$1.log" | cut -b 12- > "$1.SB2.csv"
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grep '^UniqueIPsB2:' "$1.log" | cut -b 13- > "$1.UB2.csv"
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grep '^SingleIPB3:' "$1.log" | cut -b 12- > "$1.SB3.csv"
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grep '^UniqueIPsB3:' "$1.log" | cut -b 13- > "$1.UB3.csv"
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grep '^SingleIPB4:' "$1.log" | cut -b 12- > "$1.SB4.csv"
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grep '^UniqueIPsB4:' "$1.log" | cut -b 13- > "$1.UB4.csv"
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grep '^SingleIPB8:' "$1.log" | cut -b 12- > "$1.SB8.csv"
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grep '^UniqueIPsB8:' "$1.log" | cut -b 13- > "$1.UB8.csv"
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grep '^SingleIPC1:' "$1.log" | cut -b 12- > "$1.SC1.csv"
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grep '^UniqueIPsC1:' "$1.log" | cut -b 13- > "$1.UC1.csv"
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grep '^SingleIPC2:' "$1.log" | cut -b 12- > "$1.SC2.csv"
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grep '^UniqueIPsC2:' "$1.log" | cut -b 13- > "$1.UC2.csv"
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grep '^SingleIPC3:' "$1.log" | cut -b 12- > "$1.SC3.csv"
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grep '^UniqueIPsC3:' "$1.log" | cut -b 13- > "$1.UC3.csv"
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grep '^SingleIPC4:' "$1.log" | cut -b 12- > "$1.SC4.csv"
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grep '^UniqueIPsC4:' "$1.log" | cut -b 13- > "$1.UC4.csv"
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grep '^SingleIPC8:' "$1.log" | cut -b 12- > "$1.SC8.csv"
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grep '^UniqueIPsC8:' "$1.log" | cut -b 13- > "$1.UC8.csv"
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grep '^SingleIPD1:' "$1.log" | cut -b 12- > "$1.SD1.csv"
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grep '^UniqueIPsD1:' "$1.log" | cut -b 13- > "$1.UD1.csv"
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grep '^SingleIPD2:' "$1.log" | cut -b 12- > "$1.SD2.csv"
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grep '^UniqueIPsD2:' "$1.log" | cut -b 13- > "$1.UD2.csv"
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grep '^SingleIPD3:' "$1.log" | cut -b 12- > "$1.SD3.csv"
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grep '^UniqueIPsD3:' "$1.log" | cut -b 13- > "$1.UD3.csv"
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grep '^SingleIPD4:' "$1.log" | cut -b 12- > "$1.SD4.csv"
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grep '^UniqueIPsD4:' "$1.log" | cut -b 13- > "$1.UD4.csv"
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grep '^SingleIPD8:' "$1.log" | cut -b 12- > "$1.SD8.csv"
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grep '^UniqueIPsD8:' "$1.log" | cut -b 13- > "$1.UD8.csv"
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grep '^SingleIPE2:' "$1.log" | cut -b 12- > "$1.SE2.csv"
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grep '^UniqueIPsE2:' "$1.log" | cut -b 13- > "$1.UE2.csv"
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grep '^SingleIPE3:' "$1.log" | cut -b 12- > "$1.SE3.csv"
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grep '^UniqueIPsE3:' "$1.log" | cut -b 13- > "$1.UE3.csv"
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grep '^SingleIPE4:' "$1.log" | cut -b 12- > "$1.SE4.csv"
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grep '^UniqueIPsE4:' "$1.log" | cut -b 13- > "$1.UE4.csv"
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grep '^SingleIPF1:' "$1.log" | cut -b 12- > "$1.SF1.csv"
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grep '^SingleIPF-1:' "$1.log" | cut -b 13- > "$1.SF-1.csv"
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grep '^SingleIPF2:' "$1.log" | cut -b 12- > "$1.SF2.csv"
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grep '^SingleIPF-2:' "$1.log" | cut -b 13- > "$1.SF-2.csv"
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grep '^SingleIPF3:' "$1.log" | cut -b 12- > "$1.SF3.csv"
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grep '^SingleIPF-3:' "$1.log" | cut -b 13- > "$1.SF-3.csv"
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grep '^SingleIPF4:' "$1.log" | cut -b 12- > "$1.SF4.csv"
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grep '^SingleIPF-4:' "$1.log" | cut -b 13- > "$1.SF-4.csv"
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grep '^UniqueIPsF1:' "$1.log" | cut -b 13- > "$1.UF1.csv"
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grep '^UniqueIPsF-1:' "$1.log" | cut -b 14- > "$1.UF-1.csv"
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grep '^UniqueIPsF2:' "$1.log" | cut -b 13- > "$1.UF2.csv"
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grep '^UniqueIPsF-2:' "$1.log" | cut -b 14- > "$1.UF-2.csv"
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grep '^UniqueIPsF3:' "$1.log" | cut -b 13- > "$1.UF3.csv"
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grep '^UniqueIPsF-3:' "$1.log" | cut -b 14- > "$1.UF-3.csv"
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grep '^UniqueIPsF4:' "$1.log" | cut -b 13- > "$1.UF4.csv"
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grep '^UniqueIPsF-4:' "$1.log" | cut -b 14- > "$1.UF-4.csv"
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#SingleIPA1Functions:i,Addr
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#UniqueIPsA1Functions:i,Addr
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#SingleIPA2Functions:i,Addr
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#UniqueIPsA2Functions:i,Addr
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#SingleIPA3Functions:i,Addr
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#UniqueIPsA3Functions:i,Addr
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#SingleIPA4Functions:i,Addr
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#UniqueIPsA4Functions:i,Addr
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#SingleIPA8Functions:i,Addr
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#UniqueIPsA8Functions:i,Addr
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#SingleIPB1Functions:i,Addr
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#UniqueIPsB1Functions:i,Addr
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#SingleIPB2Functions:i,Addr
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#UniqueIPsB2Functions:i,Addr
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#SingleIPB3Functions:i,Addr
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#UniqueIPsB3Functions:i,Addr
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#SingleIPB4Functions:i,Addr
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#UniqueIPsB4Functions:i,Addr
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#SingleIPB8Functions:i,Addr
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#UniqueIPsB8Functions:i,Addr
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#SingleIPC1Functions:i,Addr
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#UniqueIPsC1Functions:i,Addr
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#SingleIPC2Functions:i,Addr
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#UniqueIPsC2Functions:i,Addr
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#SingleIPC3Functions:i,Addr
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#UniqueIPsC3Functions:i,Addr
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#SingleIPC4Functions:i,Addr
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#UniqueIPsC4Functions:i,Addr
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#SingleIPC8Functions:i,Addr
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#UniqueIPsC8Functions:i,Addr
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#SingleIPD1Functions:i,Addr
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#UniqueIPsD1Functions:i,Addr
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#SingleIPD2Functions:i,Addr
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#UniqueIPsD2Functions:i,Addr
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#SingleIPD3Functions:i,Addr
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#UniqueIPsD3Functions:i,Addr
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#SingleIPD4Functions:i,Addr
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#UniqueIPsD4Functions:i,Addr
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#SingleIPD8Functions:i,Addr
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#UniqueIPsD8Functions:i,Addr
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#SingleIPE2Functions:i,Addr
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#UniqueIPsE2Functions:i,Addr
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#SingleIPE3Functions:i,Addr
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#UniqueIPsE3Functions:i,Addr
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#SingleIPE4Functions:i,Addr
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#UniqueIPsE4Functions:i,Addr
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#grep '^SingleIP0:' "$1.log" | cut -b 11- > "$1.S0.csv"
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#grep '^UniqueIPs0:' "$1.log" | cut -b 12- > "$1.U0.csv"
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#grep '^SingleIP1:' "$1.log" | cut -b 11- > "$1.S1.csv"
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#grep '^UniqueIPs1:' "$1.log" | cut -b 12- > "$1.U1.csv"
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#grep '^SingleIP2:' "$1.log" | cut -b 11- > "$1.S2.csv"
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#grep '^UniqueIPs2:' "$1.log" | cut -b 12- > "$1.U2.csv"
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414
analysis/makeplots-bonus.jl
Normal file
414
analysis/makeplots-bonus.jl
Normal file
@ -0,0 +1,414 @@
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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]
|
||||
result[1, i, j, probe + 1] = row.Probe_SF_HR
|
||||
result[2, i, j, probe + 1] = row.Probe_SR_HR
|
||||
result[3, i, j, probe + 1] = row.Probe_FF_HR
|
||||
|
||||
end
|
||||
|
||||
allprobes = cube_flatten_z([result[1,:,:,:], result[2,:,:,:], result[3,:,:,:]])
|
||||
sf_probe_heatmap_allprobes = allprobes[1]
|
||||
sr_probe_heatmap_allprobes = allprobes[2]
|
||||
ff_probe_heatmap_allprobes = allprobes[3]
|
||||
|
||||
|
||||
|
||||
all_slices = slice_extract_x([result[1,:,:,:], result[2,:,:,:], result[3,:,:,:]], slices_offset_0)
|
||||
sf_probe_slices_heatmaps = all_slices[1]
|
||||
sr_probe_slices_heatmaps = all_slices[2]
|
||||
ff_probe_slices_heatmaps = all_slices[3]
|
||||
|
||||
|
||||
|
||||
graph2d(string(basename, "_SF_AllProbes"), sf_probe_heatmap_allprobes, "i", "j")
|
||||
graph2d(string(basename, "_SR_AllProbes"), sr_probe_heatmap_allprobes, "i", "j")
|
||||
graph2d(string(basename, "_FF_AllProbes"), ff_probe_heatmap_allprobes, "i", "j")
|
||||
|
||||
|
||||
for (i, offset_0) in enumerate(slices_offset_0)
|
||||
print(offset_0)
|
||||
data = sf_probe_slices_heatmaps[i]
|
||||
graph2dclims(string(basename, "_SF_Slice_", offset_0),sf_probe_slices_heatmaps[i],(0,1), "j", "probe")
|
||||
graph2dclims(string(basename, "_SR_Slice_", offset_0),sr_probe_slices_heatmaps[i],(0,1), "j", "probe")
|
||||
graph2dclims(string(basename, "_FF_Slice_", offset_0),ff_probe_slices_heatmaps[i],(0,1), "j", "probe")
|
||||
end
|
||||
|
||||
result
|
||||
end
|
||||
|
||||
|
||||
cubes = myfill([], (length(eaps), length(types), length(functions_identifier)))
|
||||
|
||||
# need to push (k, cube)
|
||||
|
||||
Threads.@threads for experiment in files
|
||||
for (eap, type, f, k, file) in experiment[4]
|
||||
name = string(eaps[eap], "/julia_eap_", eaps[eap], "_", types[type], functions_identifier[f], k)
|
||||
print(string(name,"\n"))
|
||||
cube_3 = graph_2(name, file, k, functions_index[f])
|
||||
push!(cubes[eap, type, f], cube_3)
|
||||
end
|
||||
end
|
||||
|
||||
|
||||
if false
|
||||
|
||||
print("Computing 14 union 13...")
|
||||
|
||||
function cube_max(cubes_1, cubes_2)
|
||||
@assert size(cubes_1) == size(cubes_2)
|
||||
sizes = size(cubes_1)
|
||||
@assert length(sizes) == 5
|
||||
res = fill(0.0, sizes)
|
||||
for i in range(1,sizes[1])
|
||||
for j in range(1,sizes[2])
|
||||
Threads.@threads for k in range(1,64)
|
||||
for l in range(1, 64)
|
||||
for m in range(1, 64)
|
||||
res[i,j,k,l,m] = max(cubes_1[i,j,k,l,m], cubes_2[i,j,k,l,m])
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
res
|
||||
end
|
||||
|
||||
index_0 = findfirst(isequal(0), eaps)
|
||||
index_12 = findfirst(isequal(12), eaps)
|
||||
index_13 = findfirst(isequal(13), eaps)
|
||||
index_14 = findfirst(isequal(14), eaps)
|
||||
|
||||
cube_max_13_14 = cube_max(cubes[index_13,:,:,:,:,:], cubes[index_14,:,:,:,:,:])
|
||||
|
||||
function do_cubes(name, cubes)
|
||||
cube_list = []
|
||||
index_list = []
|
||||
for type in range(1,length(types))
|
||||
for method in range(1,3)
|
||||
push!(cube_list, cubes[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(name, "_", types[type], "2_", methods[method], "_AllProbes"), allgraphs[i], "i", "j")
|
||||
for slice in diff_slices_offset_0
|
||||
graph2d(string(name,"_", types[type], "2_", methods[method], "_Slice_", slice), cubes[type, method, slice+1,:,:], "j", "probe")
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
graph_13_14 = @task begin
|
||||
do_cubes("julia_max_13_14", cube_max_13_14)
|
||||
#cube_list = []
|
||||
#index_list = []
|
||||
#for type in range(1,length(types))
|
||||
# for method in range(1,3)
|
||||
# push!(cube_list, cube_max_13_14[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_max_13_14_", types[type], "2_", methods[method], "_AllProbes"), allgraphs[i], "i", "j")
|
||||
#end
|
||||
end
|
||||
schedule(graph_13_14)
|
||||
|
||||
|
||||
print(" OK\n")
|
||||
|
||||
print("Computing Any difference between 0 and 12...")
|
||||
|
||||
function cube_differences(cubes_1, cubes_2)
|
||||
@assert size(cubes_1) == size(cubes_2)
|
||||
sizes = size(cubes_1)
|
||||
@assert length(sizes) == 5
|
||||
res = fill(0.0, sizes)
|
||||
for i in range(1,sizes[1])
|
||||
for j in range(1,sizes[2])
|
||||
Threads.@threads for k in range(1,64)
|
||||
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
|
||||
403
analysis/makeplots-extra.jl
Normal file
403
analysis/makeplots-extra.jl
Normal file
@ -0,0 +1,403 @@
|
||||
using CSV
|
||||
using Plots
|
||||
pgfplotsx()
|
||||
|
||||
function myfill(element, dimensions)
|
||||
res = fill(element, dimensions)
|
||||
res = map(x -> deepcopy(x), res)
|
||||
res
|
||||
end
|
||||
|
||||
# Generals TODO : Fix the ticks, add legends
|
||||
#eaps = [12,13]
|
||||
#eaps = [0,14,15]
|
||||
eaps = [0,12,13,14,15]
|
||||
len_eaps = length(eaps)
|
||||
types = ["S","U"]
|
||||
functions_identifier = ["A", "B", "C", "D", "E"]
|
||||
#functions_identifier = ["B"]
|
||||
|
||||
function A_index(k, x, y, z)
|
||||
if (x + k) % 64 != y
|
||||
print(string("Argh, k = ", k, ", x = ", x, ", y = ", y, ", z = ", z))
|
||||
@assert false
|
||||
end
|
||||
(x,z)
|
||||
end
|
||||
|
||||
function B_index(k, x, y, z)
|
||||
@assert (x - k + 64) % 64 == y
|
||||
(x,z)
|
||||
end
|
||||
|
||||
function C_index(k, x, y, z)
|
||||
@assert (y + k) % 64 == z
|
||||
(x,y)
|
||||
end
|
||||
|
||||
function D_index(k, x, y, z)
|
||||
@assert (y - k + 64) % 64 == z
|
||||
(x,y)
|
||||
end
|
||||
|
||||
function E_index(k, x, y, z)
|
||||
@assert (y - x + 64) % 64 == (z - y + 64) % 64
|
||||
(x, (y - x + 64) % 64)
|
||||
end
|
||||
|
||||
functions_index = [A_index, B_index, C_index, D_index, E_index]
|
||||
#functions_index = [B_index]
|
||||
#types = ["S"]
|
||||
ks = [[1, 2, 3, 4, 8],
|
||||
[1, 2, 3, 4, 8],
|
||||
[1, 2, 3, 4, 8],
|
||||
[1, 2, 3, 4, 8],
|
||||
[2, 3, 4]
|
||||
]
|
||||
|
||||
#ks = [[8]]
|
||||
|
||||
|
||||
methods = ["SF", "SR", "FF"]
|
||||
|
||||
|
||||
|
||||
plot_lock = ReentrantLock()
|
||||
|
||||
slices_offset_0 = [0, 1, 2, 8, 14, 15, 30, 31, 32, 55, 56, 61, 62, 63]
|
||||
#slices_offset_0 = []
|
||||
|
||||
diff_slices_offset_0 = [0, 1, 2, 61, 62, 63]
|
||||
|
||||
|
||||
|
||||
function make_name(eap, type, f, k)
|
||||
string("extrap/extrap-with-", eap, "-prefetcher.", type, f, k, ".csv")
|
||||
end
|
||||
|
||||
all_file_names = myfill((0,0,0,[]), (length(eaps), length(types), length(functions_index)))
|
||||
|
||||
|
||||
|
||||
for x in 1:len_eaps
|
||||
for (y,type) in enumerate(types)
|
||||
for (z,f) in enumerate(functions_identifier)
|
||||
all_file_names[x,y,z] = (x,y,z,[])
|
||||
for (i,k) in enumerate(ks[z])
|
||||
# change me : insert file names into list
|
||||
push!(all_file_names[x,y,z][4] , (x, y, z, k, make_name(eaps[x], type, f, k) ) )
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
print(all_file_names)
|
||||
|
||||
|
||||
|
||||
#files = Matrix(CSV, length(eaps), length(types), length(levels))
|
||||
files = Array{
|
||||
Union{
|
||||
Nothing,
|
||||
Tuple{Int64, Int64, Int64, Vector{
|
||||
Tuple{ Int64, Int64, Int64, Int64, CSV.File }
|
||||
}}
|
||||
},3
|
||||
}(nothing, length(eaps), length(types), length(functions_identifier))
|
||||
|
||||
|
||||
|
||||
Threads.@threads for f in all_file_names
|
||||
x = f[1]
|
||||
y = f[2]
|
||||
z = f[3]
|
||||
files[x,y,z] = (x,y,z,[])
|
||||
for (x,y,z,k,name) in f[4]
|
||||
push!(files[x,y,z][4], (x,y,z,k, CSV.File(name)))
|
||||
end
|
||||
end
|
||||
|
||||
|
||||
|
||||
# TODO :
|
||||
#
|
||||
# - Split this function in a load data into square / cube structure and a plot function
|
||||
# - Refactor the code below to compute the various squares / cubes and then do the plots.
|
||||
# - Refactor the Slicing function too
|
||||
# - Create a custom diagonal slice function ?
|
||||
|
||||
|
||||
preamble_printed = false
|
||||
|
||||
push!(PGFPlotsX.CUSTOM_PREAMBLE,raw"\newcommand{\gdfigurewidth}{150mm}")
|
||||
push!(PGFPlotsX.CUSTOM_PREAMBLE,raw"\newcommand{\gdfigureheight}{100mm}")
|
||||
|
||||
function graph2d(name, matrix, xlabel, ylabel)
|
||||
x = range(0, 63)
|
||||
y = range(0, 63)
|
||||
function hmp2d(x, y)
|
||||
matrix[x + 1, y + 1]
|
||||
end
|
||||
lock(plot_lock) do
|
||||
graph = heatmap(x, y, hmp2d, minorgrid=true, height = raw"{\gdfigureheight}}, width = {{\gdfigurewidth}", xlabel = xlabel, ylabel = ylabel, c = :blues, extra_kwargs =:subplot)
|
||||
if !preamble_printed
|
||||
global preamble_printed = true
|
||||
print(Plots.pgfx_preamble(graph))
|
||||
end
|
||||
savefig(graph, string(name, ".tikz"))
|
||||
savefig(graph, string(name, ".pdf"))
|
||||
end
|
||||
end
|
||||
|
||||
function graph2dclims(name, matrix, clims, xlabel, ylabel)
|
||||
x = range(0, 63)
|
||||
y = range(0, 63)
|
||||
function hmp2d(x, y)
|
||||
matrix[x + 1, y + 1]
|
||||
end
|
||||
lock(plot_lock) do
|
||||
graph = heatmap(x, y, hmp2d, clims = clims, minorgrid=true, height = raw"{\gdfigureheight}}, width = {{\gdfigurewidth}", xlabel = xlabel, ylabel = ylabel, extra_kwargs =:subplot)
|
||||
savefig(graph, string(name, ".tikz"))
|
||||
savefig(graph, string(name, ".pdf"))
|
||||
end
|
||||
end
|
||||
|
||||
|
||||
function cube_flatten_z(cubes)
|
||||
len = length(cubes)
|
||||
res = myfill(myfill(0.0,(64,64)), len)
|
||||
for k in range(1,64)
|
||||
Threads.@threads for i in range(1,64)
|
||||
for j in range(1,64)
|
||||
for l in range(1,len)
|
||||
res[l][i,j] += cubes[l][i,j,k]
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
res
|
||||
end
|
||||
|
||||
function slice_extract_x(cubes, slices)
|
||||
slice_length = length(slices)
|
||||
cube_length = length(cubes)
|
||||
res = myfill(myfill(myfill(0.0, (64, 64)), slice_length), cube_length)
|
||||
for i in range(1,64)
|
||||
for j in range(1,64)
|
||||
for (k,slice) in enumerate(slices)
|
||||
for l in range(1, cube_length)
|
||||
res[l][k][i, j] = cubes[l][slice+1, i, j]
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
res
|
||||
end
|
||||
|
||||
function graph_2(basename, csv, k, index_function)
|
||||
|
||||
result = fill(-1.0, (3, 64,64,64))
|
||||
|
||||
|
||||
# Fill in the 3D cube, then create the various slices and flattenings
|
||||
# Flattened Cube with x = first addr, y = second addr, compute the sum of prefetches ?
|
||||
# Grab a few random first adresses and look at them with x = second addr, y = probe addr
|
||||
# 0,1, 62,63 14, 15 plus one other depending on what appears
|
||||
|
||||
for row in csv
|
||||
probe = row.ProbeAddr
|
||||
offset_0 = row.Offset_0
|
||||
offset_1 = row.Offset_1
|
||||
offset_2 = row.Offset_2
|
||||
|
||||
index = index_function(k, offset_0, offset_1, offset_2)
|
||||
i = index[1] + 1
|
||||
j = index[2] + 1
|
||||
@assert result[:, i, j, probe + 1] == [-1.0,-1.0,-1.0]
|
||||
result[1, i, j, probe + 1] = row.Probe_SF_HR
|
||||
result[2, i, j, probe + 1] = row.Probe_SR_HR
|
||||
result[3, i, j, probe + 1] = row.Probe_FF_HR
|
||||
|
||||
end
|
||||
|
||||
allprobes = cube_flatten_z([result[1,:,:,:], result[2,:,:,:], result[3,:,:,:]])
|
||||
sf_probe_heatmap_allprobes = allprobes[1]
|
||||
sr_probe_heatmap_allprobes = allprobes[2]
|
||||
ff_probe_heatmap_allprobes = allprobes[3]
|
||||
|
||||
|
||||
|
||||
all_slices = slice_extract_x([result[1,:,:,:], result[2,:,:,:], result[3,:,:,:]], slices_offset_0)
|
||||
sf_probe_slices_heatmaps = all_slices[1]
|
||||
sr_probe_slices_heatmaps = all_slices[2]
|
||||
ff_probe_slices_heatmaps = all_slices[3]
|
||||
|
||||
|
||||
|
||||
graph2d(string(basename, "_SF_AllProbes"), sf_probe_heatmap_allprobes, "i", "j")
|
||||
graph2d(string(basename, "_SR_AllProbes"), sr_probe_heatmap_allprobes, "i", "j")
|
||||
graph2d(string(basename, "_FF_AllProbes"), ff_probe_heatmap_allprobes, "i", "j")
|
||||
|
||||
|
||||
for (i, offset_0) in enumerate(slices_offset_0)
|
||||
print(offset_0)
|
||||
data = sf_probe_slices_heatmaps[i]
|
||||
graph2dclims(string(basename, "_SF_Slice_", offset_0),sf_probe_slices_heatmaps[i],(0,1), "j", "probe")
|
||||
graph2dclims(string(basename, "_SR_Slice_", offset_0),sr_probe_slices_heatmaps[i],(0,1), "j", "probe")
|
||||
graph2dclims(string(basename, "_FF_Slice_", offset_0),ff_probe_slices_heatmaps[i],(0,1), "j", "probe")
|
||||
end
|
||||
|
||||
result
|
||||
end
|
||||
|
||||
|
||||
cubes = myfill([], (length(eaps), length(types), length(functions_identifier)))
|
||||
|
||||
# need to push (k, cube)
|
||||
|
||||
Threads.@threads for experiment in files
|
||||
for (eap, type, f, k, file) in experiment[4]
|
||||
name = string(eaps[eap], "/julia_eap_", eaps[eap], "_", types[type], functions_identifier[f], k)
|
||||
print(string(name,"\n"))
|
||||
cube_3 = graph_2(name, file, k, functions_index[f])
|
||||
push!(cubes[eap, type, f], cube_3)
|
||||
end
|
||||
end
|
||||
|
||||
print("Computing 14 union 13...")
|
||||
|
||||
function cube_max(cubes_1, cubes_2)
|
||||
@assert size(cubes_1) == size(cubes_2)
|
||||
sizes = size(cubes_1)
|
||||
@assert length(sizes) == 5
|
||||
res = fill(0.0, sizes)
|
||||
for i in range(1,sizes[1])
|
||||
for j in range(1,sizes[2])
|
||||
Threads.@threads for k in range(1,64)
|
||||
for l in range(1, 64)
|
||||
for m in range(1, 64)
|
||||
res[i,j,k,l,m] = max(cubes_1[i,j,k,l,m], cubes_2[i,j,k,l,m])
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
res
|
||||
end
|
||||
|
||||
index_0 = findfirst(isequal(0), eaps)
|
||||
index_12 = findfirst(isequal(12), eaps)
|
||||
index_13 = findfirst(isequal(13), eaps)
|
||||
index_14 = findfirst(isequal(14), eaps)
|
||||
|
||||
cube_max_13_14 = cube_max(cubes[index_13,:,:,:,:,:], cubes[index_14,:,:,:,:,:])
|
||||
|
||||
function do_cubes(name, cubes)
|
||||
cube_list = []
|
||||
index_list = []
|
||||
for type in range(1,length(types))
|
||||
for method in range(1,3)
|
||||
push!(cube_list, cubes[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(name, "_", types[type], "2_", methods[method], "_AllProbes"), allgraphs[i], "i", "j")
|
||||
for slice in diff_slices_offset_0
|
||||
graph2d(string(name,"_", types[type], "2_", methods[method], "_Slice_", slice), cubes[type, method, slice+1,:,:], "j", "probe"))
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
graph_13_14 = @task begin
|
||||
do_cubes("julia_max_13_14", cube_max_13_14)
|
||||
cube_list = []
|
||||
index_list = []
|
||||
for type in range(1,length(types))
|
||||
for method in range(1,3)
|
||||
push!(cube_list, cube_max_13_14[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_max_13_14_", types[type], "2_", methods[method], "_AllProbes"), allgraphs[i], "i", "j")
|
||||
end
|
||||
end
|
||||
schedule(graph_13_14)
|
||||
|
||||
|
||||
print(" OK\n")
|
||||
|
||||
print("Computing Any difference between 0 and 12...")
|
||||
|
||||
function cube_differences(cubes_1, cubes_2)
|
||||
@assert size(cubes_1) == size(cubes_2)
|
||||
sizes = size(cubes_1)
|
||||
@assert length(sizes) == 5
|
||||
res = fill(0.0, sizes)
|
||||
for i in range(1,sizes[1])
|
||||
for j in range(1,sizes[2])
|
||||
Threads.@threads for k in range(1,64)
|
||||
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")
|
||||
419
analysis/makeplots.jl
Normal file
419
analysis/makeplots.jl
Normal file
@ -0,0 +1,419 @@
|
||||
using CSV
|
||||
using Plots
|
||||
pgfplotsx()
|
||||
|
||||
# Generals TODO : Fix the ticks, add legends
|
||||
#eaps = [0,12,13,14]
|
||||
eaps = [0,12,13,14,15]
|
||||
len_eaps = length(eaps)
|
||||
types = ["S","U"]
|
||||
#types = ["S"]
|
||||
levels = [0,1,2]
|
||||
|
||||
methods = ["SF", "SR", "FF"]
|
||||
|
||||
plot_lock = ReentrantLock()
|
||||
|
||||
slices_offset_0 = [0, 1, 2, 8, 14, 15, 30, 31, 32, 55, 56, 61, 62, 63]
|
||||
#slices_offset_0 = []
|
||||
|
||||
diff_slices_offset_0 = [0, 1, 2, 61, 62, 63]
|
||||
|
||||
function make_name(eap, type, level)
|
||||
string("eap/eap-with-", eap, "-prefetcher.", type, level, ".csv")
|
||||
end
|
||||
|
||||
all_file_names = fill((0,0,0,""), length(eaps), length(types), length(levels))
|
||||
Threads.@threads for x in 1:len_eaps
|
||||
for (y,type) in enumerate(types)
|
||||
for (z,level) in enumerate(levels)
|
||||
all_file_names[x,y,z] = (x,y,z,make_name(eaps[x], type, level))
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
|
||||
#files = Matrix(CSV, length(eaps), length(types), length(levels))
|
||||
files = Array{Union{Nothing, Tuple{Int64,Int64,Int64,CSV.File}},3}(nothing, length(eaps), length(types), length(levels))
|
||||
|
||||
Threads.@threads for f in all_file_names
|
||||
x = f[1]
|
||||
y = f[2]
|
||||
z = f[3]
|
||||
name = f[4]
|
||||
files[x,y,z] = (x,y,z,CSV.File(name))
|
||||
end
|
||||
|
||||
function graph_0(name, csv)
|
||||
data = [csv.Probe_FF_HR, csv.Probe_SR_HR, csv.Probe_SF_HR]
|
||||
x = range(0, 63)
|
||||
y = range(0, 2)
|
||||
function f(x, y)
|
||||
data[y + 1][x + 1]
|
||||
end
|
||||
lock(plot_lock) do
|
||||
graph = heatmap(x, y, f, yticks = ([0,1,2], ["FF", "SR", "SF"]), clims = (0, 1), xlabel="probe")
|
||||
savefig(graph, string("julia_", name, ".tikz"))
|
||||
savefig(graph, string("julia_", name, ".pdf"))
|
||||
end
|
||||
end # Todo double check if something better can be done wrt y names ?
|
||||
|
||||
# TODO :
|
||||
#
|
||||
# - Split this function in a load data into square / cube structure and a plot function
|
||||
# - Refactor the code below to compute the various squares / cubes and then do the plots.
|
||||
# - Refactor the Slicing function too
|
||||
# - Create a custom diagonal slice function ?
|
||||
|
||||
|
||||
preamble_printed = false
|
||||
|
||||
push!(PGFPlotsX.CUSTOM_PREAMBLE,raw"\newcommand{\gdfigurewidth}{150mm}")
|
||||
push!(PGFPlotsX.CUSTOM_PREAMBLE,raw"\newcommand{\gdfigureheight}{100mm}")
|
||||
|
||||
function graph2d(name, matrix, xlabel, ylabel)
|
||||
x = range(0, 63)
|
||||
y = range(0, 63)
|
||||
function hmp2d(x, y)
|
||||
matrix[x + 1, y + 1]
|
||||
end
|
||||
lock(plot_lock) do
|
||||
graph = heatmap(x, y, hmp2d, minorgrid=true, height = raw"{\gdfigureheight}}, width = {{\gdfigurewidth}", xlabel = xlabel, ylabel = ylabel, c = :blues, extra_kwargs =:subplot)
|
||||
if !preamble_printed
|
||||
global preamble_printed = true
|
||||
print(Plots.pgfx_preamble(graph))
|
||||
end
|
||||
savefig(graph, string(name, ".tikz"))
|
||||
savefig(graph, string(name, ".pdf"))
|
||||
end
|
||||
end
|
||||
|
||||
function graph2dclims(name, matrix, clims, xlabel, ylabel)
|
||||
x = range(0, 63)
|
||||
y = range(0, 63)
|
||||
function hmp2d(x, y)
|
||||
matrix[x + 1, y + 1]
|
||||
end
|
||||
lock(plot_lock) do
|
||||
graph = heatmap(x, y, hmp2d, clims = clims, minorgrid=true, height = raw"{\gdfigureheight}}, width = {{\gdfigurewidth}", xlabel = xlabel, ylabel = ylabel, extra_kwargs =:subplot)
|
||||
savefig(graph, string(name, ".tikz"))
|
||||
savefig(graph, string(name, ".pdf"))
|
||||
end
|
||||
end
|
||||
|
||||
|
||||
function graph_1(basename, csv)
|
||||
# define the 2D arrays for the 3 heatmaps
|
||||
sf_probe_heatmap = fill(-1.0, 64, 64)
|
||||
sr_probe_heatmap = fill(-1.0, 64, 64)
|
||||
ff_probe_heatmap = fill(-1.0, 64, 64)
|
||||
# define 3 1D arrays to build the heatmap for average time of the first access in FF/SR and SF modes
|
||||
sf_offset_hit_time = fill(-1.0, 64)
|
||||
sr_offset_hit_time = fill(-1.0, 64)
|
||||
ff_offset_hit_time = fill(-1.0, 64)
|
||||
# iterates on the rows and fill in the 2D arrays.
|
||||
for row in csv
|
||||
offset = row.Offset_0
|
||||
probe = row.ProbeAddr
|
||||
@assert sf_probe_heatmap[offset+1,probe+1] == -1.0
|
||||
sf_probe_heatmap[offset + 1, probe + 1] = row.Probe_SF_HR
|
||||
sr_probe_heatmap[offset + 1, probe + 1] = row.Probe_SR_HR
|
||||
ff_probe_heatmap[offset + 1, probe + 1] = row.Probe_FF_HR
|
||||
|
||||
if probe == 0
|
||||
@assert sf_offset_hit_time[offset + 1] == -1.0
|
||||
sf_offset_hit_time[offset + 1] = 0.0
|
||||
end
|
||||
sf_offset_hit_time[offset + 1] += row.Offset_0_SF_HR
|
||||
sr_offset_hit_time[offset + 1] += row.Offset_0_SR_HR
|
||||
ff_offset_hit_time[offset + 1] += row.Offset_0_FF_HR
|
||||
if probe == 63
|
||||
sf_offset_hit_time[offset + 1] /= 64
|
||||
sr_offset_hit_time[offset + 1] /= 64
|
||||
ff_offset_hit_time[offset + 1] /= 64
|
||||
end
|
||||
end
|
||||
|
||||
graph2dclims(string("julia_", basename, "_SF"), sf_probe_heatmap, (0,1), "i", "probe")
|
||||
graph2dclims(string("julia_", basename, "_SR"), sr_probe_heatmap, (0,1), "i", "probe")
|
||||
graph2dclims(string("julia_", basename, "_FF"), ff_probe_heatmap, (0,1), "i", "probe")
|
||||
|
||||
data = [ff_offset_hit_time, sr_offset_hit_time, sf_offset_hit_time]
|
||||
x = range(0, 63)
|
||||
y = range(0, 2)
|
||||
function f(x, y)
|
||||
data[y + 1][x + 1]
|
||||
end
|
||||
lock(plot_lock) do
|
||||
graph = heatmap(x, y, f)
|
||||
savefig(graph, string("julia_", basename, "_Offset_0_HT.tikz"))
|
||||
savefig(graph, string("julia_", basename, "_Offset_0_HT.pdf"))
|
||||
end
|
||||
end
|
||||
|
||||
function myfill(element, dimensions)
|
||||
res = fill(element, dimensions)
|
||||
res = map(x -> deepcopy(x), res)
|
||||
res
|
||||
end
|
||||
|
||||
function cube_flatten_z(cubes)
|
||||
len = length(cubes)
|
||||
res = myfill(myfill(0.0,(64,64)), len)
|
||||
for k in range(1,64)
|
||||
Threads.@threads for i in range(1,64)
|
||||
for j in range(1,64)
|
||||
for l in range(1,len)
|
||||
res[l][i,j] += cubes[l][i,j,k]
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
res
|
||||
end
|
||||
|
||||
function slice_extract_x(cubes, slices)
|
||||
slice_length = length(slices)
|
||||
cube_length = length(cubes)
|
||||
res = myfill(myfill(myfill(0.0, (64, 64)), slice_length), cube_length)
|
||||
for i in range(1,64)
|
||||
for j in range(1,64)
|
||||
for (k,slice) in enumerate(slices)
|
||||
for l in range(1, cube_length)
|
||||
res[l][k][i, j] = cubes[l][slice+1, i, j]
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
res
|
||||
end
|
||||
|
||||
function graph_2(basename, csv)
|
||||
# First define a 3D cube for the resulting data ?
|
||||
sf_probe_heatmap = myfill(-1.0, (64, 64, 64))
|
||||
sr_probe_heatmap = myfill(-1.0, (64, 64, 64))
|
||||
ff_probe_heatmap = myfill(-1.0, (64, 64, 64))
|
||||
# Fill in the 3D cube, then create the various slices and flattenings
|
||||
# Flattened Cube with x = first addr, y = second addr, compute the sum of prefetches ?
|
||||
# Grab a few random first adresses and look at them with x = second addr, y = probe addr
|
||||
# 0,1, 62,63 14, 15 plus one other depending on what appears
|
||||
|
||||
# Also define and fill in a 2D matrix of offset1-offset2 hit time.
|
||||
sf_offset_hit_time = myfill(-1.0, (64, 64))
|
||||
sr_offset_hit_time = myfill(-1.0, (64, 64))
|
||||
ff_offset_hit_time = myfill(-1.0, (64, 64))
|
||||
|
||||
for row in csv
|
||||
probe = row.ProbeAddr
|
||||
offset_0 = row.Offset_0
|
||||
offset_1 = row.Offset_1
|
||||
@assert sf_probe_heatmap[offset_0 + 1, offset_1 + 1, probe + 1] == -1.0
|
||||
sf_probe_heatmap[offset_0 + 1, offset_1 + 1, probe + 1] = row.Probe_SF_HR
|
||||
sr_probe_heatmap[offset_0 + 1, offset_1 + 1, probe + 1] = row.Probe_SR_HR
|
||||
ff_probe_heatmap[offset_0 + 1, offset_1 + 1, probe + 1] = row.Probe_FF_HR
|
||||
|
||||
if probe == 0
|
||||
@assert sf_offset_hit_time[offset_0 + 1, offset_1 + 1] == -1.0
|
||||
sf_offset_hit_time[offset_0 + 1, offset_1 + 1] = 0.0
|
||||
end
|
||||
sf_offset_hit_time[offset_0 + 1, offset_1 + 1] += row.Offset_1_SF_HR
|
||||
sr_offset_hit_time[offset_0 + 1, offset_1 + 1] += row.Offset_1_SR_HR
|
||||
ff_offset_hit_time[offset_0 + 1, offset_1 + 1] += row.Offset_1_FF_HR
|
||||
if probe == 63
|
||||
sf_offset_hit_time[offset_0 + 1, offset_1 + 1] /= 64
|
||||
sr_offset_hit_time[offset_0 + 1, offset_1 + 1] /= 64
|
||||
ff_offset_hit_time[offset_0 + 1, offset_1 + 1] /= 64
|
||||
end
|
||||
|
||||
end
|
||||
allprobes = cube_flatten_z([sf_probe_heatmap, sr_probe_heatmap, ff_probe_heatmap])
|
||||
sf_probe_heatmap_allprobes = allprobes[1]
|
||||
sr_probe_heatmap_allprobes = allprobes[2]
|
||||
ff_probe_heatmap_allprobes = allprobes[3]
|
||||
|
||||
|
||||
|
||||
all_slices = slice_extract_x([sf_probe_heatmap, sr_probe_heatmap, ff_probe_heatmap], slices_offset_0)
|
||||
sf_probe_slices_heatmaps = all_slices[1]
|
||||
sr_probe_slices_heatmaps = all_slices[2]
|
||||
ff_probe_slices_heatmaps = all_slices[3]
|
||||
|
||||
graph2d(string("julia_", basename, "_SF_AllProbes"), sf_probe_heatmap_allprobes, "i", "j")
|
||||
graph2d(string("julia_", basename, "_SR_AllProbes"), sr_probe_heatmap_allprobes, "i", "j")
|
||||
graph2d(string("julia_", basename, "_FF_AllProbes"), ff_probe_heatmap_allprobes, "i", "j")
|
||||
|
||||
|
||||
for (i, offset_0) in enumerate(slices_offset_0)
|
||||
print(offset_0)
|
||||
data = sf_probe_slices_heatmaps[i]
|
||||
graph2dclims(string("julia_", basename, "_SF_Slice_", offset_0),sf_probe_slices_heatmaps[i],(0,1), "j", "probe")
|
||||
graph2dclims(string("julia_", basename, "_SR_Slice_", offset_0),sr_probe_slices_heatmaps[i],(0,1), "j", "probe")
|
||||
graph2dclims(string("julia_", basename, "_FF_Slice_", offset_0),ff_probe_slices_heatmaps[i],(0,1), "j", "probe")
|
||||
end
|
||||
[sf_probe_heatmap, sr_probe_heatmap, ff_probe_heatmap]
|
||||
end
|
||||
|
||||
Threads.@threads for file in files[:,:,1]
|
||||
name = string("eap_",eaps[file[1]],"_",types[file[2]],levels[file[3]])
|
||||
graph_0(name, file[4])
|
||||
print(string(name,"\n"))
|
||||
end
|
||||
|
||||
Threads.@threads for file in files[:,:,2]
|
||||
name = string("eap_",eaps[file[1]],"_",types[file[2]],levels[file[3]])
|
||||
graph_1(name, file[4])
|
||||
print(string(name,"\n"))
|
||||
end
|
||||
|
||||
|
||||
cubes = fill(0.0, length(eaps), length(types), 3, 64, 64, 64)
|
||||
|
||||
Threads.@threads for file in files[:,:,3]
|
||||
name = string("eap_",eaps[file[1]],"_",types[file[2]],levels[file[3]])
|
||||
(sf,sr,ff) = graph_2(name, file[4])
|
||||
cubes[file[1], file[2], 1, :, :, :] = sf
|
||||
cubes[file[1], file[2], 2, :, :, :] = sr
|
||||
cubes[file[1], file[2], 3, :, :, :] = ff
|
||||
print(string(name,"\n"))
|
||||
end
|
||||
|
||||
|
||||
|
||||
|
||||
print("Computing 14 union 13...")
|
||||
|
||||
function cube_max(cubes_1, cubes_2)
|
||||
@assert size(cubes_1) == size(cubes_2)
|
||||
sizes = size(cubes_1)
|
||||
@assert length(sizes) == 5
|
||||
res = fill(0.0, sizes)
|
||||
for i in range(1,sizes[1])
|
||||
for j in range(1,sizes[2])
|
||||
Threads.@threads for k in range(1,64)
|
||||
for l in range(1, 64)
|
||||
for m in range(1, 64)
|
||||
res[i,j,k,l,m] = max(cubes_1[i,j,k,l,m], cubes_2[i,j,k,l,m])
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
res
|
||||
end
|
||||
|
||||
index_0 = findfirst(isequal(0), eaps)
|
||||
index_12 = findfirst(isequal(12), eaps)
|
||||
index_13 = findfirst(isequal(13), eaps)
|
||||
index_14 = findfirst(isequal(14), eaps)
|
||||
|
||||
cube_max_13_14 = cube_max(cubes[index_13,:,:,:,:,:], cubes[index_14,:,:,:,:,:])
|
||||
|
||||
function do_cubes(name, cubes)
|
||||
cube_list = []
|
||||
index_list = []
|
||||
for type in range(1,length(types))
|
||||
for method in range(1,3)
|
||||
push!(cube_list, cubes[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(name, "_", types[type], "2_", methods[method], "_AllProbes"), allgraphs[i], "i", "j")
|
||||
for slice in diff_slices_offset_0
|
||||
graph2d(string(name,"_", types[type], "2_", methods[method], "_Slice_", slice), cubes[type, method, slice+1,:,:], "j", "probe")
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
graph_13_14 = @task begin
|
||||
do_cubes("julia_max_13_14", cube_max_13_14)
|
||||
cube_list = []
|
||||
index_list = []
|
||||
for type in range(1,length(types))
|
||||
for method in range(1,3)
|
||||
push!(cube_list, cube_max_13_14[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_max_13_14_", types[type], "2_", methods[method], "_AllProbes"), allgraphs[i], "i", "j")
|
||||
end
|
||||
end
|
||||
schedule(graph_13_14)
|
||||
|
||||
|
||||
print(" OK\n")
|
||||
|
||||
print("Computing Any difference between 0 and 12...")
|
||||
|
||||
function cube_differences(cubes_1, cubes_2)
|
||||
@assert size(cubes_1) == size(cubes_2)
|
||||
sizes = size(cubes_1)
|
||||
@assert length(sizes) == 5
|
||||
res = fill(0.0, sizes)
|
||||
for i in range(1,sizes[1])
|
||||
for j in range(1,sizes[2])
|
||||
Threads.@threads for k in range(1,64)
|
||||
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")
|
||||
74
analysis/sort.sh
Executable file
74
analysis/sort.sh
Executable file
@ -0,0 +1,74 @@
|
||||
#!/bin/sh
|
||||
|
||||
mkdir -p _/0
|
||||
mkdir -p _/1
|
||||
mkdir -p _/2
|
||||
|
||||
mv *{S,U}0* _/0/
|
||||
mv *{S,U}1* _/1/
|
||||
mv *{S,U}2* _/2/
|
||||
|
||||
mkdir -p A/1/
|
||||
mkdir -p A/2/
|
||||
mkdir -p A/3/
|
||||
mkdir -p A/4/
|
||||
mkdir -p A/8/
|
||||
mkdir -p B/8/
|
||||
mkdir -p B/4/
|
||||
mkdir -p B/3/
|
||||
mkdir -p B/2/
|
||||
mkdir -p B/1/
|
||||
mkdir -p C/1/
|
||||
mkdir -p C/2/
|
||||
mkdir -p C/3/
|
||||
mkdir -p C/4/
|
||||
mkdir -p C/8/
|
||||
mkdir -p D/8/
|
||||
mkdir -p D/1/
|
||||
mkdir -p D/2/
|
||||
mkdir -p D/3/
|
||||
mkdir -p D/4/
|
||||
mkdir -p E/4/
|
||||
mkdir -p E/3/
|
||||
mkdir -p E/2/
|
||||
mkdir -p F/1/
|
||||
mkdir -p F/-1/
|
||||
mkdir -p F/2/
|
||||
mkdir -p F/-2/
|
||||
mkdir -p F/3/
|
||||
mkdir -p F/-3/
|
||||
mkdir -p F/4/
|
||||
mkdir -p F/-4/
|
||||
|
||||
mv *A1_* A/1/
|
||||
mv *A2_* A/2/
|
||||
mv *A3_* A/3/
|
||||
mv *A4_* A/4/
|
||||
mv *A8_* A/8/
|
||||
mv *B8_* B/8/
|
||||
mv *B4_* B/4/
|
||||
mv *B3_* B/3/
|
||||
mv *B2_* B/2/
|
||||
mv *B1_* B/1/
|
||||
mv *C1_* C/1/
|
||||
mv *C2_* C/2/
|
||||
mv *C3_* C/3/
|
||||
mv *C4_* C/4/
|
||||
mv *C8_* C/8/
|
||||
mv *D8_* D/8/
|
||||
mv *D1_* D/1/
|
||||
mv *D2_* D/2/
|
||||
mv *D3_* D/3/
|
||||
mv *D4_* D/4/
|
||||
mv *E4_* E/4/
|
||||
mv *E3_* E/3/
|
||||
mv *E2_* E/2/
|
||||
mv *F1_* F/1/
|
||||
mv *F-1_* F/-1/
|
||||
mv *F2_* F/2/
|
||||
mv *F-2_* F/-2/
|
||||
mv *F3_* F/3/
|
||||
mv *F-3_* F/-3/
|
||||
mv *F4_* F/4/
|
||||
mv *F-4_* F/-4/
|
||||
|
||||
76
prefetcher_reverse/Readme.md
Normal file
76
prefetcher_reverse/Readme.md
Normal file
@ -0,0 +1,76 @@
|
||||
CacheObserver - monitor what happens in the cache when doing memory accesses
|
||||
============================================================================
|
||||
|
||||
This framework, derived from https://github.com/MIAOUS-group/calibration-done-right,
|
||||
is built to help reverse engineer prefetchers on Intel CPUs.
|
||||
|
||||
The main entry point of the framework is the `prefetcher_reverse` crate.
|
||||
|
||||
The code presented runs under Fedora 30, and can also be made to run on Ubuntu 18.04 LTS with minor tweaks
|
||||
|
||||
(Notably, lib cpupower may also be called lib cpufreq)
|
||||
|
||||
## Usage
|
||||
|
||||
Requires rust nightly features. Install rust nightly using rustup,
|
||||
known working versions are listed at the end of the document.
|
||||
|
||||
This tool needs access to MSR and thus requires sudo access.
|
||||
The setup.sh script disables turbo boost and makes sure the frequency is set to the max
|
||||
non-boosted frequency.
|
||||
|
||||
One can run all the experiments with the following instructions :
|
||||
|
||||
```
|
||||
cd prefetcher_reverse
|
||||
mkdir results-xxx
|
||||
cd results-xxx
|
||||
sudo ../setup.sh
|
||||
../run-msr-all.sh 15
|
||||
../run-msr-all.sh 14
|
||||
../run-msr-all.sh 13
|
||||
../run-msr-all.sh 12
|
||||
../run-msr-all.sh 0
|
||||
# Do not forget to re-enable turbo-boost and set the cpupower frequency governor back
|
||||
```
|
||||
|
||||
This results in a set of log files that can then be analyzed.
|
||||
|
||||
**Note for default settings, this results in several GB worth of logs**
|
||||
|
||||
## General Architecture
|
||||
|
||||
`prefetcher_reverse` is where the experiments used to reverse engineer prefetcher lives.
|
||||
It contains the Prober structure, along with binaries generating patterns for the experiments
|
||||
to run and feeding them to the Prober struct.
|
||||
|
||||
The `analysis` folder contains the scripts we used to turn the logs into figures.
|
||||
To be documented. We used Julia with the Plots and PGFPlotsX backend to generate figures.
|
||||
|
||||
The flow is to first use `extract_analysis_csv.sh` to extract the CSV for each experiment from the logs.
|
||||
|
||||
Then one can use the makeplots Julia scripts (those are unfortunately not optimized and may run for several hours, as the LaTeX backend is not thread-safe and generates many figures).
|
||||
|
||||
Those scripts expect to find the CSVs at a specific path and require their output folder
|
||||
by MSR 420 (0x1A4) values to exist beforehand (so 15,14,13,12,0 must exist beforehand).
|
||||
They are still quite rough and undocumented, rough edges are to be expected.
|
||||
(A better version could be released if the paper is accepted)
|
||||
|
||||
The resulting figures can then be sorted into subfolders for easier browsing, and the change colormap script can be used to tweak the tikz file colormaps for use in papers
|
||||
|
||||
Crates originally from the *Calibration done right* framework, slightly modified :
|
||||
|
||||
- `basic_timing_cache_channel` contains generic implementations of Naive and Optimised cache side channels, that just require providing the actual operation used
|
||||
- `cache_side_channel` defines the interface cache side channels have to implement
|
||||
- `cache_utils` contains utilities related to cache attacks
|
||||
- `cpuid` is a small crate that handles CPU microarchitecture identification and provides info about what is known about it
|
||||
- `flush_flush` and `flush_reload` are tiny crates that use `basic_timing_cache_channel` to export Flush+Flush and Flush+Reload primitives
|
||||
- `turn_lock` is the synchronization primitive used by `cache_utils`
|
||||
|
||||
|
||||
### Rust versions
|
||||
|
||||
Known good nightly :
|
||||
|
||||
- rustc 1.54.0-nightly (eab201df7 2021-06-09)
|
||||
- rustc 1.55.0-nightly (885399992 2021-07-06)
|
||||
Loading…
Reference in New Issue
Block a user