Evaluation scripts
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eugen.betke
parent
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#!/usr/bin/env Rscript
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library(sqldf)
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library(plyr)
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library(plot3D)
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library(ggplot2)
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args = commandArgs(trailingOnly=TRUE)
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print(args)
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if (2 != length(args)) {
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print("Requires 2 parameters)")
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q()
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}
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file_db = args[1]
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folder_out = args[2]
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print(file_db)
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make_facet_label <- function(variable, value){
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return(paste0(value, " KiB"))
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}
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#connection = dbConnect(SQLite(), dbname='results.ddnime.db')
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print(file_db)
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connection = dbConnect(SQLite(), dbname=file_db)
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#dbdata = dbGetQuery(connection,'select mnt, siox, avg(duration) as ad, app, procs, blocksize from p group by mnt, siox, procs, blocksize, app')
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#dbdata = dbGetQuery(connection,'select * from p where tag=="mpio-individual"')
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#dbdata = dbGetQuery(connection,'select *, (x*y*z) as blocksize from p where count=8')
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#dbdata = dbGetQuery(connection,'select * from p where count<5')
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dbdata = dbGetQuery(connection,'select * from p where ppn==1 or ppn=4 or ppn=8')
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dbdata[,"blocksize"] = dbdata$x * dbdata$y * dbdata$z * 4
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summary(dbdata)
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nn_lab <- sprintf(fmt="NN=%d", unique(dbdata$nn))
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names(nn_lab) <- unique(dbdata$nn)
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ppn_lab <- sprintf(fmt="PPN=%d", unique(dbdata$ppn))
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names(ppn_lab) <- unique(dbdata$ppn)
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breaks <- c(unique(dbdata$blocksize))
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fig_w = 4
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fig_h = 4
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w = c(4, 6, 4)
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h = c(4, 4, 4)
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event = c("paper", "isc-pres", "poster")
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dims_list = data.frame(h, w, event) # df is a data frame
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fss = unique(dbdata$fs)
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for (fs in fss) {
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data1 = dbdata[fs == dbdata$fs, ]
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ifaces = unique(data1$iface)
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for (iface in ifaces) {
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data2 = data1[iface == data1$iface, ]
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apps = unique(data2$app)
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for (app in apps) {
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data3 = data2[app == data2$app, ]
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types = unique(data3$type)
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for (type in types) {
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data4 = data3[type == data3$type, ]
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chunkeds = unique(data4$chunked)
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for (chunked in chunkeds) {
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data5 = data4[chunked == data4$chunked, ]
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filleds = unique(data4$filled)
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for (filled in filleds) {
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data6 = data5[filled == data5$filled, ]
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unlimiteds = unique(data5$unlimited)
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for (unlimited in unlimiteds) {
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data = data6[unlimited == data5$unlimited, ]
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ggplot(data=data, aes(x=nn, y=write, colour=as.factor(blocksize/1024), group=blocksize), ymin=0) +
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#ggtitle("Write") +
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facet_grid(ppn ~ ., labeller = labeller(nn = as_labeller(nn_lab), ppn = as_labeller(ppn_lab))) +
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xlab("Nodes") +
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ylab("Performance in MiB/s") +
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theme(axis.text.x=element_text(angle=90, hjust=0.95, vjust=0.5)) +
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theme(legend.position="bottom") +
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#scale_y_log10() +
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scale_x_continuous(breaks = c(unique(data$nn))) +
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scale_color_manual(name="Blocksize in KiB: ", values=c('#999999','#E69F00', '#56B4E9', '#000000'), breaks=sort(unique(data$blocksize)/1024)) +
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#stat_summary(fun.y="median", geom="line", aes(group=factor(blocksize))) +
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stat_summary(fun.y="max", geom="line", aes(group=factor(blocksize))) +
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#geom_boxplot()
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geom_point()
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filename_eps = sprintf("%s/performance_%s_%s_%s_%s_CHUNK:%s_FILL:%s_LIM:%s_%s.eps", folder_out, app, fs, iface, type, chunked, filled, unlimited, "write")
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filename_png = sprintf("%s/performance_%s_%s_%s_%s_CHUNK:%s_FILL:%s_LIM:%s_%s.png", folder_out, app, fs, iface, type, chunked, filled, unlimited, "write")
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ggsave(filename_png, width = 6, height = 4)
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ggsave(filename_eps, width = 6, height = 4)
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system(sprintf("epstopdf %s", filename_eps))
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system(sprintf("rm %s", filename_eps))
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ggplot(data=data, aes(x=nn, y=read, colour=as.factor(blocksize/1024), group=blocksize), ymin=0) +
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#ggtitle("Read") +
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facet_grid(ppn ~ ., labeller = labeller(nn = as_labeller(nn_lab), ppn = as_labeller(ppn_lab))) +
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xlab("Nodes") +
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ylab("Performance in MiB/s") +
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theme(axis.text.x=element_text(angle=90, hjust=0.95, vjust=0.5)) +
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theme(legend.position="bottom") +
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#scale_y_log10() +
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scale_x_continuous(breaks = c(unique(data$nn))) +
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scale_color_manual(name="Blocksize in KiB: ", values=c('#999999','#E69F00', '#56B4E9', '#000000'), breaks=sort(unique(data$blocksize)/1024)) +
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#stat_summary(fun.y="median", geom="line", aes(group=factor(blocksize))) +
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stat_summary(fun.y="max", geom="line", aes(group=factor(blocksize))) +
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#geom_boxplot()
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geom_point()
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filename_eps = sprintf("%s/performance_%s_%s_%s_%s_CHUNK:%s_FILL:%s_LIM:%s_%s.eps", folder_out, app, fs, iface, type, chunked, filled, unlimited, "read")
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filename_png = sprintf("%s/performance_%s_%s_%s_%s_CHUNK:%s_FILL:%s_LIM:%s_%s.png", folder_out, app, fs, iface, type, chunked, filled, unlimited, "read")
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ggsave(filename_png, width = 6, height = 4)
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ggsave(filename_eps, width = 6, height = 4)
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system(sprintf("epstopdf %s", filename_eps))
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system(sprintf("rm %s", filename_eps))
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#ggplot(data=data, aes(x=blocksize, y=read, colour=app, group=blocksize)) +
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# ggtitle("Read") +
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# facet_grid(ppn ~ nn, labeller = labeller(nn = as_labeller(nn_lab), ppn = as_labeller(ppn_lab))) +
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# xlab("Blocksize in KiB") +
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# ylab("Performance in MiB/s") +
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# theme(axis.text.x=element_text(angle=90, hjust=0.95, vjust=0.5)) +
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# scale_y_log10() +
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# scale_x_log10(breaks = breaks, labels=breaks/1024) +
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# geom_boxplot()
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##geom_line() +
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##geom_point()
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#filename_eps = sprintf("%s/performance_%s_%s_%s_%s_%s.eps", folder_out, app, fs, iface, type, "read")
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#ggsave(filename_eps, width = 8, height = 6)
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##system(sprintf("epstopdf %s", filename_eps))
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}}}}}}}
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#!/usr/bin/env Rscript
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library(sqldf)
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library(plyr)
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library(plot3D)
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library(ggplot2)
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library(gtools)
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args = commandArgs(trailingOnly=TRUE)
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#print(args)
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#if (2 != length(args)) {
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#print("Requires 2 parameters)")
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#q()
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#}
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#file_db = args[1]
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#folder_out = args[2]
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file_db = 'results_benchtool.db'
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folder_out = 'plot_coll_chunked'
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print(file_db)
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make_facet_label <- function(variable, value){
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return(paste0(value, " KiB"))
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}
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#connection = dbConnect(SQLite(), dbname='results.ddnime.db')
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print(file_db)
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connection = dbConnect(SQLite(), dbname=file_db)
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#dbdata = dbGetQuery(connection,'select mnt, siox, avg(duration) as ad, app, procs, blocksize from p group by mnt, siox, procs, blocksize, app')
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#dbdata = dbGetQuery(connection,'select * from p where tag=="mpio-individual"')
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#dbdata = dbGetQuery(connection,'select *, (x*y*z) as blocksize from p where count=8')
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#dbdata = dbGetQuery(connection,'select * from p where count<5')
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dbdata = dbGetQuery(connection,'select * from p where nn==10 and ppn=8')
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dbdata[,"blocksize"] = dbdata$x * dbdata$y * dbdata$z * 4
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summary(dbdata)
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nn_lab <- sprintf(fmt="NN %d", unique(dbdata$nn))
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names(nn_lab) <- unique(dbdata$nn)
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ppn_lab <- sprintf(fmt="PPN %d", unique(dbdata$ppn))
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names(ppn_lab) <- unique(dbdata$ppn)
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breaks <- c(unique(dbdata$blocksize))
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fig_w = 4
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fig_h = 4
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w = c(4, 6, 4)
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h = c(4, 4, 4)
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event = c("paper", "isc-pres", "poster")
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dims_list = data.frame(h, w, event) # df is a data frame
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for (scale in c('log', 'linear')) {
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fss = unique(dbdata$fs)
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for (fs in fss) {
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data1 = dbdata[fs == dbdata$fs, ] # ime, lustre, fuse
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ifaces = unique(data1$iface)
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for (iface in ifaces) {
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data2 = data1[iface == data1$iface, ] # posix, mpio, ime
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apps = unique(data2$app)
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for (app in apps) {
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data3 = data2[app == data2$app, ] # ior, benchtool
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filleds = unique(data3$filled)
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for (filled in filleds) {
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data4 = data3[filled == data2$filled, ]
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unlimiteds = unique(data4$unlimited)
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for (unlimited in unlimiteds) {
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data = data4[unlimited == data3$unlimited, ]
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dat_write <- data.frame(chunked=data$chunked, type=data$type, perf=data$write, blocksize=data$blocksize, access="write")
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dat_read <- data.frame(chunked=data$chunked, type=data$type, perf=data$read, blocksize=data$blocksize, access="read")
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dat <- rbind(dat_write, dat_read)
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#dat$lab <- paste0(dat$blocksize/1024, "/", dat$access)
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dat$lab <- paste0(dat$blocksize/1024)
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dat$lab_type <- data$type;
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dat$lab_type[dat$lab_type == "coll"] = "Collective"
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dat$lab_type[dat$lab_type == "ind"] = "Independent"
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dat$lab_chunked <- data$chunked;
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dat$lab_chunked[dat$lab_chunked == "auto"] = "Chunking"
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dat$lab_chunked[dat$lab_chunked == "notset"] = "No chunking"
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print(summary(dat))
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print(mixedsort(unique(dat$lab)))
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p <- ggplot(data=dat, aes(x=lab, y=perf, colour=as.factor(blocksize/1024), group=interaction(access, blocksize)), ymin=0) +
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#ggtitle("Write") +
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#facet_grid(ppn ~ ., labeller = labeller(nn = as_labeller(nn_lab), ppn = as_labeller(ppn_lab))) +
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facet_grid(. ~ lab_type + lab_chunked + access) +
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xlab("Blocksizes in KiB / Access") +
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ylab("Performance in MiB/s") +
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theme(axis.text.x=element_text(angle=90, hjust=0.95, vjust=0.5)) +
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theme(legend.position="bottom") +
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#ylim(0, 100000) +
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#scale_x_continuous(breaks = c(unique(data$nn))) +
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#scale_color_manual(name="Blocksize in KiB: ", values=c('#999999','#E69F00', '#56B4E9', '#000000'), breaks=sort(unique(data$blocksize)/1024)) +
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scale_color_manual(name="Blocksize in KiB: ", values=c('#999999','#E69F00', '#56B4E9', '#000000', '#999999','#E69F00', '#56B4E9', '#000000'), breaks=mixedsort(unique(dat$lab))) +
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scale_fill_manual(name="Blocksize in KiB: ", values=c('#999999','#E69F00', '#56B4E9', '#000000', '#999999','#E69F00', '#56B4E9', '#000000'), breaks=mixedsort(unique(dat$lab))) +
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#stat_summary(fun.y="median", geom="line", aes(group=factor(blocksize))) +
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#stat_summary(fun.y="max", geom="line", aes(group=factor(blocksize))) +
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geom_boxplot()
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#geom_bar()
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#geom_point()
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if ('log' == scale) {
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p = p + scale_y_log10(breaks=c(100, 1000, 10000, 40000))
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}
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{
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p = p + scale_x_discrete(breaks=mixedsort(unique(dat$lab)), limits=mixedsort(unique(dat$lab)))
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}
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filename_eps = sprintf("%s/performance_%s_FS:%s_IFACE:%s_FILLED_%s_LIM:%s_SCALE:%s.eps", folder_out, app, fs, iface, filled, unlimited, scale)
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filename_png = sprintf("%s/performance_%s_FS:%s_IFACE:%s_FILLED_%s_LIM:%s_SCALE:%s.png", folder_out, app, fs, iface, filled, unlimited, scale)
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ggsave(filename_eps, width = 8, height = 8)
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ggsave(filename_png, width = 8, height = 8)
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system(sprintf("epstopdf %s", filename_eps))
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system(sprintf("rm %s", filename_eps))
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}}}}}}
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#}}
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#!/usr/bin/env Rscript
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library(sqldf)
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library(plyr)
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library(plot3D)
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library(ggplot2)
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args = commandArgs(trailingOnly=TRUE)
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print(args)
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if (2 != length(args)) {
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print("Requires 2 parameters)")
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q()
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}
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file_db = args[1]
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folder_out = args[2]
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print(file_db)
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make_facet_label <- function(variable, value){
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return(paste0(value, " KiB"))
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}
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#connection = dbConnect(SQLite(), dbname='results.ddnime.db')
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print(file_db)
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connection = dbConnect(SQLite(), dbname=file_db)
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#dbdata = dbGetQuery(connection,'select mnt, siox, avg(duration) as ad, app, procs, blocksize from p group by mnt, siox, procs, blocksize, app')
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#dbdata = dbGetQuery(connection,'select * from p where tag=="mpio-individual"')
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#dbdata = dbGetQuery(connection,'select *, (x*y*z) as blocksize from p where count=8')
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#dbdata = dbGetQuery(connection,'select * from p where count<5')
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dbdata = dbGetQuery(connection,'select *, (nn*ppn) as procs from p ')
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dbdata[,"blocksize"] = dbdata$x * dbdata$y * dbdata$z * 4
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summary(dbdata)
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nn_lab <- sprintf(fmt="NN %d", unique(dbdata$nn))
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names(nn_lab) <- unique(dbdata$nn)
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ppn_lab <- sprintf(fmt="PPN %d", unique(dbdata$ppn))
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names(ppn_lab) <- unique(dbdata$ppn)
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breaks <- c(unique(dbdata$blocksize))
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fig_w = 4
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fig_h = 4
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w = c(4, 6, 4)
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h = c(4, 4, 4)
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event = c("paper", "isc-pres", "poster")
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dims_list = data.frame(h, w, event) # df is a data frame
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fss = unique(dbdata$fs) # lustre, ime, fuse
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for (fs in fss) {
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data1 = dbdata[fs == dbdata$fs, ]
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ifaces = unique(data1$iface)
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for (iface in ifaces) { # mpio, ime, posix
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data2 = data1[iface == data1$iface, ]
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apps = unique(data2$app)
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for (app in apps) { # benchtool, ior
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data = data2[app == data2$app, ]
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#ggplot(data=data, aes(x=nn, y=ropen, colour=as.factor(blocksize/1024), group=blocksize), ymin=0) +
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ggplot(data=data, aes(x=nn, y=ropen, color=ppn)) +
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geom_point() +
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xlab("Nodes") +
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ylab("Duration in sec") +
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theme(axis.text.x=element_text(angle=90, hjust=0.95, vjust=0.5)) +
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theme(legend.position="right") +
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#scale_y_log10() +
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scale_x_continuous(breaks = c(unique(data$nn))) +
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geom_smooth(data=data[data$ppn==8,]) +
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geom_smooth(data=data[data$ppn==6,]) +
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geom_smooth(data=data[data$ppn==4,]) +
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geom_smooth(data=data[data$ppn==2,]) +
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geom_smooth(data=data[data$ppn==1,]) +
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scale_colour_gradientn(colours = rainbow(7)) # + geom_abline(slope=0.1089, intercept=0.1315)
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filename_eps = sprintf("%s/performance_%s_%s_%s_%s.eps", folder_out, app, fs, iface, "readopen")
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ggsave(filename_eps, width = 6, height = 4)
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system(sprintf("epstopdf %s", filename_eps))
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system(sprintf("rm %s", filename_eps))
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ggplot(data=data, aes(x=nn, y=wopen, color=ppn)) +
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geom_point() +
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xlab("Nodes") +
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ylab("Duration in sec") +
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theme(axis.text.x=element_text(angle=90, hjust=0.95, vjust=0.5)) +
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theme(legend.position="right") +
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#scale_y_log10() +
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scale_x_continuous(breaks = c(unique(data$nn))) +
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geom_smooth(data=data[data$ppn==8,]) +
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geom_smooth(data=data[data$ppn==6,]) +
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geom_smooth(data=data[data$ppn==4,]) +
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geom_smooth(data=data[data$ppn==2,]) +
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geom_smooth(data=data[data$ppn==1,]) +
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scale_colour_gradientn(colours = rainbow(7)) # + geom_abline(slope=0.1089, intercept=0.1315)
|
||||
filename_eps = sprintf("%s/performance_%s_%s_%s_%s.eps", folder_out, app, fs, iface, "writeopen")
|
||||
ggsave(filename_eps, width = 6, height = 4)
|
||||
system(sprintf("epstopdf %s", filename_eps))
|
||||
system(sprintf("rm %s", filename_eps))
|
||||
|
||||
|
||||
|
||||
}}}
|
||||
|
|
@ -0,0 +1,207 @@
|
|||
#!/usr/bin/env Rscript
|
||||
|
||||
library(sqldf)
|
||||
library(plyr)
|
||||
library(plot3D)
|
||||
library(ggplot2)
|
||||
require(gridExtra)
|
||||
|
||||
|
||||
theme_set(theme_gray(base_size = 25))
|
||||
|
||||
args = commandArgs(trailingOnly=TRUE)
|
||||
print(args)
|
||||
if (2 != length(args)) {
|
||||
print("Requires 2 parameters)")
|
||||
q()
|
||||
}
|
||||
|
||||
file_db = args[1]
|
||||
folder_out = args[2]
|
||||
print(file_db)
|
||||
|
||||
make_facet_label <- function(variable, value){
|
||||
return(paste0(value, " KiB"))
|
||||
}
|
||||
|
||||
|
||||
#connection = dbConnect(SQLite(), dbname='results.ddnime.db')
|
||||
print(file_db)
|
||||
connection = dbConnect(SQLite(), dbname=file_db)
|
||||
|
||||
#dbdata = dbGetQuery(connection,'select mnt, siox, avg(duration) as ad, app, procs, blocksize from p group by mnt, siox, procs, blocksize, app')
|
||||
#dbdata = dbGetQuery(connection,'select * from p where tag=="mpio-individual"')
|
||||
#dbdata = dbGetQuery(connection,'select *, (x*y*z) as blocksize from p where count=8')
|
||||
#dbdata = dbGetQuery(connection,'select * from p where count<5')
|
||||
#dbdata = dbGetQuery(connection,'select * from p where iface="mpio" and (ppn==1 or ppn=4 or ppn=8)')
|
||||
dbdata = dbGetQuery(connection,'select * from p where (ppn==1 or ppn=4 or ppn=8)')
|
||||
dbdata[,"blocksize"] = dbdata$x * dbdata$y * dbdata$z * 4
|
||||
|
||||
|
||||
#summary(dbdata)
|
||||
|
||||
nn_lab <- sprintf(fmt="NN=%d", unique(dbdata$nn))
|
||||
names(nn_lab) <- unique(dbdata$nn)
|
||||
|
||||
ppn_lab <- sprintf(fmt="PPN=%d", unique(dbdata$ppn))
|
||||
names(ppn_lab) <- unique(dbdata$ppn)
|
||||
|
||||
breaks <- c(unique(dbdata$blocksize))
|
||||
|
||||
|
||||
#fig_w = 4
|
||||
#fig_h = 4
|
||||
|
||||
#w = c(4, 6, 4)
|
||||
#h = c(4, 4, 4)
|
||||
#event = c("paper", "isc-pres", "poster")
|
||||
#dims_list = data.frame(h, w, event) # df is a data frame
|
||||
|
||||
|
||||
|
||||
for (scale in c('log', 'linear')) {
|
||||
fss = unique(dbdata$fs)
|
||||
for (fs in fss) {
|
||||
data1 = dbdata[fs == dbdata$fs, ]
|
||||
#apps = unique(data1$app)
|
||||
ifaces = unique(data1$iface)
|
||||
|
||||
for (iface in ifaces) {
|
||||
data2 = data1[iface == data1$iface, ]
|
||||
apps = unique(data2$app)
|
||||
|
||||
for (app in apps) {
|
||||
data3 = data2[app == data2$app, ]
|
||||
types = unique(data3$type)
|
||||
|
||||
for (type in types) {
|
||||
data4 = data3[type == data3$type, ]
|
||||
chunkeds = unique(data4$chunked)
|
||||
|
||||
for (chunked in chunkeds) {
|
||||
data5 = data4[chunked == data4$chunked, ]
|
||||
filleds = unique(data4$filled)
|
||||
|
||||
for (filled in filleds) {
|
||||
data6 = data5[filled == data5$filled, ]
|
||||
unlimiteds = unique(data5$unlimited)
|
||||
|
||||
for (unlimited in unlimiteds) {
|
||||
data = data6[unlimited == data5$unlimited, ]
|
||||
|
||||
dat_write <- data.frame(real_perf=data$fsize/data$wio/1024^2, nn=data$nn, ppn=data$ppn, iface=data$iface, chunked=data$chunked, type=data$type, perf=data$write, blocksize=data$blocksize, access="write", tio="wio", stringsAsFactors = FALSE)
|
||||
dat_read <- data.frame(real_perf=data$fsize/data$rio/1024^2, nn=data$nn, ppn=data$ppn, iface=data$iface, chunked=data$chunked, type=data$type, perf=data$read, blocksize=data$blocksize, access="read", tio="rio", stringsAsFactors = FALSE)
|
||||
dat <- rbind(dat_write, dat_read)
|
||||
|
||||
|
||||
dat$lab_ppn <- paste0("PPN=", dat$ppn)
|
||||
|
||||
dat$lab_iface <- dat$iface
|
||||
dat$lab_iface[dat$lab_iface == "posix"] = "POSIX"
|
||||
dat$lab_iface[dat$lab_iface == "mpio"] = "MPIIO"
|
||||
dat$lab_iface[dat$lab_iface == "ime"] = "IME"
|
||||
|
||||
dat$lab_access <- dat$access
|
||||
dat$lab_access[dat$lab_access == "write"] = "Write"
|
||||
dat$lab_access[dat$lab_access == "read"] = "Read"
|
||||
|
||||
|
||||
print(summary(dat))
|
||||
#print(dat[0:10])
|
||||
|
||||
|
||||
#library(ggplot2)
|
||||
#p = qplot(1, 1)
|
||||
#grid.arrange(p, p, respect=TRUE) # both viewports are square
|
||||
#grid.arrange(p, p, respect=TRUE, heights=c(1,2)) # relative heights
|
||||
|
||||
#p1 = p + theme(aspect.ratio=3)
|
||||
#grid.arrange(p,p1, respect=TRUE) # one is square, the other thinner
|
||||
|
||||
|
||||
for (print_legend in c("yes", "no")) {
|
||||
|
||||
#p <- ggplot(data=dat, aes(x=nn, y=perf, colour=as.factor(blocksize/1024), group=blocksize), ymin=0) +
|
||||
p <- ggplot(data=dat, aes(x=nn, y=real_perf, colour=as.factor(blocksize/1024), group=blocksize), ymin=0) +
|
||||
#ggtitle("Write") +
|
||||
#facet_grid(ppn ~ ., labeller = labeller(nn = as_labeller(lab), ppn = as_labeller(lab))) +
|
||||
#facet_grid(lab_ppn ~ lab_iface + lab_access) +
|
||||
facet_grid(lab_ppn ~ lab_access) +
|
||||
xlab("Nodes") +
|
||||
ylab("Performance in MiB/s") +
|
||||
theme(axis.text.x=element_text(angle=90, hjust=0.95, vjust=0.5)) +
|
||||
#scale_y_log10() +
|
||||
scale_x_continuous(breaks = c(unique(data$nn))) +
|
||||
scale_color_manual(name="Blocksize in KiB: ", values=c('#999999','#E69F00', '#56B4E9', '#000000'), breaks=sort(unique(data$blocksize)/1024)) +
|
||||
#stat_summary(fun.y="median", geom="line", aes(group=factor(blocksize))) +
|
||||
stat_summary(fun.y="max", geom="line", aes(group=factor(blocksize))) +
|
||||
#coord_fixed(ratio=1) +
|
||||
theme(aspect.ratio=1) +
|
||||
theme(plot.margin=grid::unit(c(0,0,0,0), "mm")) +
|
||||
#geom_boxplot()
|
||||
geom_point()
|
||||
|
||||
|
||||
#grid.arrange(p, p, respect=TRUE) # both viewports are square
|
||||
|
||||
|
||||
#p1 = p + theme(aspect.ratio=3)
|
||||
#grid.arrange(p,p1, respect=TRUE) # one is square, the other thinner
|
||||
|
||||
#p = qplot(1, 1)
|
||||
#grid.arrange(p, p, respect=TRUE) # both viewports are square
|
||||
#grid.arrange(p, p, respect=TRUE, heights=c(1,2)) # relative heights
|
||||
|
||||
if(fs=="lustre") {
|
||||
print("Lustre limit")
|
||||
p = p + ylim(0, 20000)
|
||||
}
|
||||
#if(fs=="fuse") {
|
||||
#p = p + theme(legend.position="bottom")
|
||||
#}
|
||||
if(print_legend=="yes") {
|
||||
p = p + theme(legend.position="bottom")
|
||||
}
|
||||
else {
|
||||
p = p + theme(legend.position="none")
|
||||
}
|
||||
|
||||
if ('log' == scale) {
|
||||
p = p + scale_y_log10()
|
||||
p = p + scale_x_log10(breaks = c(unique(data$nn)))
|
||||
#p = p + scale_y_log10(breaks=c(100, 1000, 10000, 40000))
|
||||
}
|
||||
{
|
||||
#p = p + scale_x_discrete(breaks=mixedsort(unique(dat$lab)), limits=mixedsort(unique(dat$lab)))
|
||||
}
|
||||
|
||||
filename_eps_base = sprintf("%s/performance_%s_%s_%s_%s_CHUNK:%s_FILL:%s_LIM:%s_legend:%s_SCALE:%s", folder_out, app, fs, iface, type, chunked, filled, unlimited, print_legend, scale)
|
||||
filenmae_eps=""
|
||||
|
||||
if(fs=="ime") {
|
||||
filename = sprintf("%s_size:%dx%d", filename_eps_base, 6, 8)
|
||||
filename_eps = sprintf("%s.eps", filename)
|
||||
filename_png = sprintf("%s.png", filename)
|
||||
filename_pdf = sprintf("%s.pdf", filename)
|
||||
ggsave(filename_eps, width = 6, height = 6)
|
||||
ggsave(filename_png, dpi=300)
|
||||
system(sprintf("epstopdf %s", filename_eps))
|
||||
system(sprintf("rm %s", filename_eps))
|
||||
system(sprintf("pdfcrop %s %s", filename_pdf, filename_pdf))
|
||||
}
|
||||
|
||||
#filename = sprintf("%s_size:%dx%d", filename_eps_base, 12, 8)
|
||||
filename = sprintf("%s_size:%dx%d", filename_eps_base, 9, 6)
|
||||
filename_eps = sprintf("%s.eps", filename)
|
||||
filename_png = sprintf("%s.png", filename)
|
||||
filename_pdf = sprintf("%s.pdf", filename)
|
||||
#ggsave(filename_eps, width = 12, height = 6)
|
||||
ggsave(filename_eps, dpi=300)
|
||||
ggsave(filename_png, dpi=300)
|
||||
system(sprintf("epstopdf %s", filename_eps))
|
||||
system(sprintf("rm %s", filename_eps))
|
||||
system(sprintf("pdfcrop %s %s", filename_pdf, filename_pdf))
|
||||
} # for legend
|
||||
|
||||
}}}}}}}
|
||||
} # scale
|
||||
|
|
@ -0,0 +1,75 @@
|
|||
#!/usr/bin/env Rscript
|
||||
|
||||
library(sqldf)
|
||||
library(plyr)
|
||||
library(plot3D)
|
||||
library(ggplot2)
|
||||
library(gtools)
|
||||
|
||||
|
||||
args = commandArgs(trailingOnly=TRUE)
|
||||
#print(args)
|
||||
#if (2 != length(args)) {
|
||||
#print("Requires 2 parameters)")
|
||||
#q()
|
||||
#}
|
||||
|
||||
#file_db = args[1]
|
||||
#folder_out = args[2]
|
||||
|
||||
file_db_random = 'results_random.db'
|
||||
file_db_sequential = 'results_sequential.db'
|
||||
folder_out = 'plot_read_write'
|
||||
|
||||
#file_db = file_db_sequential
|
||||
file_db = file_db_random
|
||||
|
||||
make_facet_label <- function(variable, value){
|
||||
return(paste0(value, " KiB"))
|
||||
}
|
||||
|
||||
|
||||
#connection = dbConnect(SQLite(), dbname='results.ddnime.db')
|
||||
print(file_db)
|
||||
connection = dbConnect(SQLite(), dbname=file_db)
|
||||
|
||||
dbdata = dbGetQuery(connection,'select * from p')
|
||||
dbdata[,"blocksize"] = dbdata$x * dbdata$y * dbdata$z * 4
|
||||
|
||||
dbdata$nn_lab <- sprintf(fmt="NN=%d; PPN=1-10", dbdata$nn)
|
||||
dbdata$nn_lab_f <- factor(dbdata$nn_lab, sprintf(fmt="NN=%d; PPN=1-10", sort(unique(dbdata$nn))))
|
||||
print(dbdata$nn_lab)
|
||||
#names(nn_lab) <- unique(dbdata$nn)
|
||||
|
||||
summary(dbdata)
|
||||
|
||||
fss = unique(dbdata$fs)
|
||||
for (fs in fss) {
|
||||
data = dbdata[fs == dbdata$fs, ]
|
||||
|
||||
ggplot(data=data, aes(x=read, y=write, colour=as.factor(blocksize/1024), group=blocksize), ymin=0, xmin=0) +
|
||||
#ggtitle("Write") +
|
||||
facet_grid(. ~ nn_lab_f) +
|
||||
facet_wrap(~ nn_lab_f) +
|
||||
xlab("Read Performance in MiB/s") +
|
||||
ylab("Write Performance in MiB/s") +
|
||||
#theme(axis.text.x=element_text(angle=90, hjust=0.95, vjust=0.5)) +
|
||||
theme(legend.position="bottom") +
|
||||
theme(aspect.ratio=1) +
|
||||
scale_y_log10() +
|
||||
scale_x_log10() +
|
||||
scale_color_manual(name="Blocksize in KiB: ", values=c('#999999','#E69F00', '#56B4E9', '#000000','#999999','#E69F00', '#56B4E9', '#000000','#999999','#E69F00', '#56B4E9', '#000000' )) +
|
||||
geom_point()
|
||||
|
||||
filename = sprintf("%s/performance_overview_rnd_%s", folder_out, fs)
|
||||
filename_eps = sprintf("%s.eps", filename)
|
||||
filename_png = sprintf("%s.png", filename)
|
||||
filename_pdf = sprintf("%s.pdf", filename)
|
||||
#ggsave(filename_eps, width = 12, height = 6)
|
||||
#ggsave(filename_eps, dpi=1000)
|
||||
ggsave(filename_eps, width = 16)
|
||||
ggsave(filename_png, dpi=300)
|
||||
system(sprintf("epstopdf %s", filename_eps))
|
||||
system(sprintf("rm %s", filename_eps))
|
||||
system(sprintf("pdfcrop %s %s", filename_pdf, filename_pdf))
|
||||
}
|
||||
Loading…
Reference in New Issue