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Commit a5702706 authored by Heyd's avatar Heyd
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Supprimer P4a

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load("E:\\Documents\\IUT - Semestre 4\\Module - P4a - Performance\\P4a\\.RData")
perfArray
GraphArray <- ggplot(perfArray, aes(x=Taille, y=CPU, color="red")) + geom_point()
library(ggplot2)
GraphArray <- ggplot(perfArray, aes(x=Taille, y=CPU, color="red")) + geom_point()
GraphArray
perfTableau
GraphTableau <- ggplot(perfTableau, aes(x=Taille, y=CPU, color="blue")) + geom_point()
GraphTableau
GraphTableau
GraphTableau <- ggplot(perfTableau, aes(x=Taille, y=CPU, color="green")) + geom_point()
GraphTableau
GraphTableau <- ggplot(perfTableau, aes(x=Taille, y=CPU, color='green')) + geom_point()
GraphTableau
GraphArray
GraphTableau <- ggplot(perfTableau, aes(x=Taille, y=CPU, color='green')) + geom_point(color="green")
GraphTableau
GraphArray <- ggplot(perfArray, aes(x=Taille, y=CPU, color="red")) + geom_point(color="red")
GraphArray
perfLinked
GraphLinked = ggplot(perfLinked, aes(x=Taille, y=CPU, color="blue")) + geom_point(color="blue")
GraphLinked
GraphPerfInitializing <- rbind(GraphArray, GraphTableau, GraphLinked)
GraphPerfInitializing
GraphPerf <- ggplot(GraphPerfInitializing, aes(x=Taille, y=CPU)) + geom_point()
ggplot(GraphPerfInitializing, aes(x=Taille, y=CPU)) + geom_point()
GraphTableau
test<- rbind(perfArray, perfTableau, perfLinked)
GraphTest <- ggplot(test, aes(x=Taille, y=CPU)) + geom_point()
GraphTest
ggplot(perfArray, aes(x=Taille, y=CPU)) + geom_point() + geom_smooth(fill="blue", colour="darkblue", size=1)
warnings()
save.image("E:\\Documents\\IUT - Semestre 4\\Module - P4a - Performance\\P4a\\.RData")
q()
load("E:\\Documents\\IUT - Semestre 4\\Module - P4a - Performance\\P4a\\.RData")
perfArray
Array
graphArray
arrayGraph
GraphArray
GraphArray <- ggplot(perfArray, aes(x=Taille, y=CPU, color="red")) + geom_point(color="red") + geom_smooth()
library(ggplot2)
GraphArray <- ggplot(perfArray, aes(x=Taille, y=CPU, color="red")) + geom_point(color="red") + geom_smooth()
GraphArray <- ggplot(perfArray, aes(x=Taille, y=CPU, color="red")) + geom_point(color="red") + geom_smooth()
GraphArray
warnings()
q()
perf <- read.csv2("perf.csv", sep="\t", dec=".")
perfTableau <- read.csv2("perfTableau.csv", sep="\t", dec=".")
perfTableau <- read.csv2("perfTableau.csv", sep="\t", dec=".")
perfArray <- read.csv2("perfArray.csv", sep="\t", dec=".")
perfLinked <- read.csv2("perfLinked.csv", sep="\t", dec=".")
graphTableau <- ggplot(perfTableau, aes(x=Taille,y=CPU,label="Performance Add Tableau")) + geom_smooth(color=blue")
)
"
graphTableau <- ggplot(perfTableau, aes(x=Taille,y=CPU,label="Performance Add Tableau")) + geom_smooth(color="blue")
library(ggplot2)
graphTableau <- ggplot(perfTableau, aes(x=Taille,y=CPU,label="Performance Add Tableau")) + geom_smooth(color="blue")
graphTableau
graphTableau <- ggplot(perfTableau, aes(x=Taille,y=CPU,label="Performance Add Tableau")) + geom_smooth(color="blue") + ggtitle("Evaluation du temps d'xcution de Add sur un tableau")
graphTableau <- ggplot(perfTableau, aes(x=Taille,y=CPU,colour="Performance Add Tableau")) + geom_smooth(color="blue") + ggtitle("Evaluation du temps d'xcution de Add sur un tableau")
graphTableau
graphTableau <- ggplot(perfTableau, aes(x=Taille,y=CPU,colour=Performance Add Tableau)) + geom_smooth(color="blue") + ggtitle("Evaluation du temps d'xcution de Add sur un tableau")
graphTableau <- ggplot(perfTableau, aes(x=Taille,y=CPU,color="Performance Add Tableau")) + geom_smooth(color="blue") + ggtitle("Evaluation du temps d'xcution de Add sur un tableau")
graphTableau
graphTableau <- ggplot(perfTableau, aes(x=Taille,y=CPU,color="red")) + geom_smooth(color="blue") + ggtitle("Evaluation du temps d'xcution de Add sur un tableau")
graphTableau
graphTableau <- ggplot(perfTableau, aes(x=Taille,y=CPU,color=red)) + geom_smooth(color="blue") + ggtitle("Evaluation du temps d'xcution de Add sur un tableau")
graphTableau
graphTableau <- ggplot(perfTableau, aes(x=Taille,y=CPU,color=time)) + geom_smooth(color="blue") + ggtitle("Evaluation du temps d'xcution de Add sur un tableau")
graphTableau
graphTableau
graphTableau <- ggplot(perfTableau, aes(x=Taille,y=CPU,color=CPU)) + geom_smooth(color="blue") + ggtitle("Evaluation du temps d'xcution de Add sur un tableau")
graphTableau
graphArray <- ggplot(perfArray, aes(x=Taille,y=CPU,color=CPU)) + geom_smooth(color="red") + ggtitle("Evaluation du temps d'xcution de Add sur une Array")
graphArray
graphLinked <- ggplot(perfLinked, aes(x=Taille,y=CPU,color=CPU)) + geom_smooth(color="green") + ggtitle("Evaluation du temps d'xcution de Add sur une LinkedList")
graphLinked
graph <- ggarrange(graphTableau, graphArray, graphLinked, Labels=c("Tableau","Array","Linked"), ncol=2, nrow=2)
library(ggpubr)
install.package(ggpubr)
instal.package(ggpubr)
local({pkg <- select.list(sort(.packages(all.available = TRUE)),graphics=TRUE)
if(nchar(pkg)) library(pkg, character.only=TRUE)})
instal.packages(ggpubr)
install.packages(ggpubr)
if(!require(devtools)) install.packages("devtools")
devtools::install_github("kassambara/ggpubr")
devtools::install_github("kassambara/ggpubr")
install.packages(ggpubr)
local({pkg <- select.list(sort(.packages(all.available = TRUE)),graphics=TRUE)
if(nchar(pkg)) library(pkg, character.only=TRUE)})
library(devtools)
library("devtools")
library("devtools")
local({pkg <- select.list(sort(.packages(all.available = TRUE)),graphics=TRUE)
if(nchar(pkg)) library(pkg, character.only=TRUE)})
local({pkg <- select.list(sort(.packages(all.available = TRUE)),graphics=TRUE)
if(nchar(pkg)) library(pkg, character.only=TRUE)})
print(perfArray)
print(graphArray)
print(graphLinked)
using pushViewport()
pushViewport(viewport(layout = grid.layout(2,2)))
if(!require(devtools)) install.packages("devtools")
devtools::install_github("kassambara/ggpubr")
devtools::install_github("kassambara/ggpubr")
install.packages("ggpubr")
libraryr(ggpubr)
library(ggpubr)
graph <- ggarrange(graphTableau, graphArray, graphLinked, Labels=c("Tableau","Array","Linked"), ncol=2, nrow=2)
graph
save.image("E:\\Documents\\IUT - Semestre 4\\Module - P4a - Performance\\P4a\\.RData")
perf <- read.csv2("perf.csv", sep="\t", dec=".")
perf
perf <- read.csv2("perf.csv", sep="\t", dec=".")
perf
ggplot(perf,aes(y = CPU, x = Taille, colour = Structure, shape =Structure))
ggplot(perf,aes(y = CPU, x = Taille, colour = Structure, shape =Structure)) + geom_point() + geom_smooth()
ggplot(perf,aes(y = CPU, x = Taille, colour = Structure, shape =Structure)) + geom_point() + geom_smooth() + ggtitle("Evaluation de la performance CPU de la mthode ADD en fonction de la taille")
perfAdd <- read.csv2("perf.csv", sep="\t", dec=".")
GraphAdd <- ggplot(perfAdd,aes(y = CPU, x = Taille, colour = Structure, shape =Structure)) + geom_point() + geom_smooth() + ggtitle("Evaluation de la performance CPU de la mthode ADD en fonction de la taille")
GraphAdd
GraphAddCPU <- ggplot(perfAdd,aes(y = CPU, x = Taille, colour = Structure, shape =Structure)) + geom_point() + geom_smooth() + ggtitle("Evaluation de la performance CPU de la mthode ADD en fonction de la taille")
GraphAddMemoire <- ggplot(perfAdd,aes(y = CPU, x = Taille, colour = Structure, shape =Structure)) + geom_point() + geom_smooth() + ggtitle("Evaluation de la performance mmoire de la mthode ADD en fonction de la taille")
GraphAddMemoire
GraphAddMemoire <- ggplot(perfAdd,aes(y = Memoire, x = Taille, colour = Structure, shape =Structure)) + geom_point() + geom_smooth() + ggtitle("Evaluation de la performance mmoire de la mthode ADD en fonction de la taille")
GraphAddMemoire
GraphAddMemoire <- ggplot(perfAdd,aes(y = Mem, x = Taille, colour = Structure, shape =Structure)) + geom_point() + geom_smooth() + ggtitle("Evaluation de la performance mmoire de la mthode ADD en fonction de la taille")
GraphAddMemoire
save.image("E:\\Documents\\IUT - Semestre 4\\Module - P4a - Performance\\P4a\\.RData")
q()
Main.jar 0 → 100644
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File added
README.md
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...@@ -26,7 +26,7 @@ Contrainte : il faut de l’abstraction, et au moins un tableau ET une liste cha ...@@ -26,7 +26,7 @@ Contrainte : il faut de l’abstraction, et au moins un tableau ET une liste cha
**Organisation du projet** **Organisation du projet**
![](/UML_P4a.PNG) ![](/UML_P4a.png)
## Dispositif expérimental ## Dispositif expérimental
......
UML.drawio 0 → 100644
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UML_P4a.png

82.7 KiB

perf.csv
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Tableau Structure Test Taille CPU Mem
Taille, CPU, Mem Tableau 1 11797000 1.31 343900
100, 0.03, 27576 Tableau 2 8166000 0.70 233216
1000, 0.06, 27592 Tableau 3 13790000 1.65 356292
10000, 0.04, 28100 Tableau 4 11637000 1.34 345296
100000, 0.06, 30216 Tableau 5 23771000 2.37 689876
1000000, 0.09, 48400 Tableau 6 11941000 1.76 344132
10000000, 0.90, 310548 Tableau 7 713000 0.12 42612
100000000, 14.26, 2427740 Tableau 8 4318000 0.40 119112
Array Tableau 9 32655000 4.23 875968
Taille, CPU, Mem Tableau 10 13708000 1.45 356808
100, 0.03, 27588 Tableau 11 14941000 1.68 359964
1000, 0.03, 27632 Tableau 12 15392000 1.73 389132
10000, 0.03, 28288 Tableau 13 759000 0.07 43416
100000, 0.06, 31348 Tableau 14 23614000 2.40 689056
1000000, 0.14, 59088 Tableau 15 10158000 0.85 302888
10000000, 1.73, 369432 Tableau 16 16554000 1.93 445944
100000000, 21.17, 2843616 Tableau 17 28786000 2.92 781460
Linked Tableau 18 25403000 2.76 765952
Taille, CPU, Mem Tableau 19 23059000 2.23 682272
100, 0.03, 27604 Tableau 20 13667000 1.56 356096
1000, 0.04, 27676 Tableau 21 7115000 0.45 212516
10000, 0.06, 28336 Tableau 22 17501000 2.64 480652
100000, 0.06, 32424 Tableau 23 18640000 2.78 506536
1000000, 0.40, 94300 Tableau 24 257000 0.06 33684
10000000, 4.76, 524520 Tableau 25 5044000 0.40 152680
100000000, 68.70, 4308476 Tableau 26 18854000 3.06 509684
Tableau 27 14979000 1.50 360400
Tableau 28 9572000 0.68 300576
Tableau 29 23717000 2.32 685720
Tableau 30 22982000 1.89 571200
Tableau 31 22523000 1.85 564612
Tableau 32 10340000 0.85 303644
Tableau 33 22902000 1.96 569696
Tableau 34 28631000 3.04 764548
Tableau 35 17528000 3.04 480468
Tableau 36 20195000 3.37 538412
Tableau 37 15525000 1.73 364192
Tableau 38 10613000 0.78 304644
Tableau 39 24075000 3.67 658280
Tableau 40 14601000 1.62 357228
Tableau 41 9476000 0.87 299252
Tableau 42 16182000 1.45 368228
Tableau 43 5125000 0.46 151040
Tableau 44 31959000 4.39 844072
Tableau 45 14531000 1.75 385024
Tableau 46 19408000 3.14 521208
Tableau 47 18598000 2.87 503544
Tableau 48 14159000 1.75 353492
Tableau 49 21235000 2.07 536552
Tableau 50 2213000 0.20 96272
Array 1 10315000 2.67 373540
Array 2 1286000 0.06 70756
Array 3 26868000 6.43 925488
Array 4 1845000 0.26 107172
Array 5 24806000 4.15 841244
Array 6 9983000 2.42 371548
Array 7 12737000 3.07 443156
Array 8 31557000 7.17 1065296
Array 9 31490000 7.31 1092564
Array 10 17012000 3.43 593728
Array 11 1472000 0.35 96484
Array 12 7698000 1.39 282748
Array 13 23331000 4.59 769748
Array 14 4994000 0.98 214032
Array 15 30203000 6.42 968600
Array 16 27670000 4.32 842488
Array 17 13408000 3.32 452796
Array 18 7322000 1.51 280932
Array 19 24355000 5.01 792152
Array 20 6366000 1.29 280628
Array 21 10108000 2.14 364604
Array 22 23009000 4.15 772016
Array 23 28412000 4.87 907132
Array 24 5398000 1.07 220844
Array 25 28364000 6.15 871080
Array 26 19539000 3.51 594276
Array 27 29098000 7.85 941600
Array 28 22299000 6.71 780996
Array 29 14385000 3.12 508348
Array 30 20619000 3.43 645844
Array 31 5565000 0.85 223180
Array 32 22529000 3.96 769200
Array 33 16979000 3.51 593924
Array 34 28921000 4.68 842872
Array 35 28208000 4.31 842084
Array 36 12434000 2.51 383216
Array 37 22912000 4.29 775936
Array 38 3459000 0.50 154244
Array 39 10163000 2.39 365056
Array 40 30438000 6.45 970160
Array 41 9501000 2.26 364408
Array 42 5408000 1.01 220584
Array 43 7486000 1.59 281012
Array 44 31843000 7.12 1095532
Array 45 26598000 3.73 842636
Array 46 19435000 3.34 596964
Array 47 15321000 3.28 520288
Array 48 19483000 3.17 597024
Array 49 15012000 3.00 523032
Array 50 26206000 4.35 840600
Linked 1 14278000 7.56 772120
Linked 2 20522000 10.39 1042584
Linked 3 7287000 3.95 376932
Linked 4 696000 0.26 78316
Linked 5 13809000 8.17 765984
Linked 6 28957000 17.20 1428072
Linked 7 23574000 13.75 1158152
Linked 8 10911000 6.23 661668
Linked 9 20974000 10.73 1055816
Linked 10 5826000 2.71 353996
Linked 11 12058000 6.37 662956
Linked 12 4735000 2.32 286480
Linked 13 29197000 16.98 1429412
Linked 14 15900000 8.64 859316
Linked 15 24727000 13.39 1160996
Linked 16 24019000 12.71 1155592
Linked 17 23074000 13.81 1139456
Linked 18 4985000 2.07 280620
Linked 19 11597000 6.79 641480
Linked 20 6848000 4.62 361460
Linked 21 20634000 11.95 1057272
Linked 22 14742000 8.34 742256
Linked 23 24361000 15.82 1276240
Linked 24 10553000 6.85 637972
Linked 25 28159000 18.71 1412356
Linked 26 11363000 7.25 641320
Linked 27 18275000 11.68 961572
Linked 28 15076000 9.90 832720
Linked 29 937000 0.53 94268
Linked 30 25853000 16.14 1285976
Linked 31 14963000 7.84 771352
Linked 32 25294000 14.92 1300764
Linked 33 23465000 12.95 1156372
Linked 34 22955000 14.65 1137660
Linked 35 27698000 17.06 1417600
Linked 36 21766000 13.15 1145816
Linked 37 4058000 2.09 281260
Linked 38 20027000 12.03 1034644
Linked 39 13904000 7.70 767256
Linked 40 17898000 9.32 856000
Linked 41 8144000 3.81 375672
Linked 42 20864000 10.79 1053304
Linked 43 17793000 8.96 869748
Linked 44 17323000 9.76 863384
Linked 45 8432000 4.73 460316
Linked 46 10632000 5.42 547440
Linked 47 14806000 8.32 753160
Linked 48 6059000 2.76 347912
Linked 49 25885000 15.87 1279276
Linked 50 32566000 20.04 1612876
Maillon 1 18520000 4.01 686260
Maillon 2 2410000 1.32 117680
Maillon 3 15546000 2.89 513916
Maillon 4 28782000 4.42 838148
Maillon 5 27312000 4.68 878476
Maillon 6 29996000 5.45 994392
Maillon 7 7387000 1.75 297592
Maillon 8 6622000 1.42 224716
Maillon 9 30046000 5.50 1018232
Maillon 10 11692000 2.51 366116
Maillon 11 4734000 1.35 212068
Maillon 12 15072000 2.70 499292
Maillon 13 25509000 4.48 860900
Maillon 14 9184000 2.31 327332
Maillon 15 21616000 4.37 742784
Maillon 16 15828000 2.93 513940
Maillon 17 17598000 3.59 656176
Maillon 18 9095000 1.90 282628
Maillon 19 12353000 2.79 381044
Maillon 20 706000 0.15 47116
Maillon 21 12100000 2.20 352948
Maillon 22 19645000 3.96 638440
Maillon 23 13976000 3.17 474072
Maillon 24 25591000 4.51 851680
Maillon 25 7165000 1.93 294620
Maillon 26 1678000 0.84 98336
Maillon 27 5326000 1.56 214796
Maillon 28 4390000 1.10 169344
Maillon 29 26082000 4.37 843172
Maillon 30 2386000 0.87 108892
Maillon 31 9896000 2.14 353832
Maillon 32 27561000 4.42 869976
Maillon 33 10480000 2.18 383432
Maillon 34 25517000 4.31 863732
Maillon 35 440000 0.04 40056
Maillon 36 25887000 4.37 846120
Maillon 37 31290000 5.54 1015908
Maillon 38 8979000 1.93 289272
Maillon 39 21349000 3.23 681984
Maillon 40 8257000 1.84 279348
Maillon 41 5320000 1.21 218332
Maillon 42 26300000 4.57 851036
Maillon 43 31038000 6.21 1020768
Maillon 44 4385000 1.54 170384
Maillon 45 3979000 1.31 160460
Maillon 46 8843000 1.82 312764
Maillon 47 931000 0.14 51924
Maillon 48 31311000 5.70 1025596
Maillon 49 5685000 1.28 215732
Maillon 50 6524000 1.51 223644
perf.sh deleted 100644 → 0
+ 0
− 17
View file @ 68e0759d
##!/usr/bin/env bash
NTEST=3
TAILLES="100 1000 10000 100000 1000000 10000000 100000000"
echo "Taille, CPU, Mem"
for taille in $TAILLES
do
for i in `seq $NTEST`
do
res=`time "%U, %M" ./Main $taille > /dev/null`
echo "$taille, $req"
done
done
perf2.sh
+ 32
− 5
View file @ a5702706
#!/usr/bin/env bash #!/usr/bin/env bash
NTEST=50
TAILLE="1000000 2000000 3000000 4000000 5000000 6000000 7000000 8000000 9000000 10000000 11000000 1200000"
NTEST=20
echo "Taille, CPU, Mem" echo -e "Structure\tTest\tTaille\tCPU\tMem"
for i in `seq $NTEST` for i in `seq $NTEST`
do
name="Tableau"
taille=${RANDOM}000
res=`(/usr/bin/time -f "%U\t%M" java -jar Main.jar "Tableau" $taille > /dev/null) 2>&1`
echo -e "$name\t$i\t$taille\t$res"
done
for i in `seq $NTEST`
do
name="Array"
taille=${RANDOM}000
res=`(/usr/bin/time -f "%U\t%M" java -jar Main.jar "Array" $taille > /dev/null) 2>&1`
echo -e "$name\t$i\t$taille\t$res"
done
res=`(/usr/bin/time -f "%U, %M" java -jar Main.jar "Linked" $nombre > /dev/null) 2>&1` for i in `seq $NTEST`
echo "$taille, $res" do
name="Linked"
taille=${RANDOM}000
res=`(/usr/bin/time -f "%U\t%M" java -jar Main.jar "Linked" $taille > /dev/null) 2>&1`
echo -e "$name\t$i\t$taille\t$res"
done
for i in `seq $NTEST`
do
name="Maillon"
taille=${RANDOM}000
res=`(/usr/bin/time -f "%U\t%M" java -jar Main.jar "Maillon" $taille > /dev/null) 2>&1`
echo -e "$name\t$i\t$taille\t$res"
done done
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