starpu_paje_draw_histogram.R 4.6 KB

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  1. # StarPU --- Runtime system for heterogeneous multicore architectures.
  2. #
  3. # Copyright (C) 2014 Université Joseph Fourier
  4. #
  5. # StarPU is free software; you can redistribute it and/or modify
  6. # it under the terms of the GNU Lesser General Public License as published by
  7. # the Free Software Foundation; either version 2.1 of the License, or (at
  8. # your option) any later version.
  9. #
  10. # StarPU is distributed in the hope that it will be useful, but
  11. # WITHOUT ANY WARRANTY; without even the implied warranty of
  12. # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
  13. #
  14. # See the GNU Lesser General Public License in COPYING.LGPL for more details.
  15. # R script that is giving statistical analysis of the paje trace
  16. # Can be called from the command line with:
  17. # Rscript $this_script $range1 $range2 $name $outputfile $inputfiles
  18. # Package containing ddply function
  19. library(plyr)
  20. library(ggplot2)
  21. library(data.table)
  22. # Function for reading .csv file
  23. read_df <- function(file,range1,range2) {
  24. df<-read.csv(file, header=FALSE, strip.white=TRUE)
  25. names(df) <- c("Nature","ResourceId","Type","Start","End","Duration", "Depth", "Value")
  26. df = df[!(names(df) %in% c("Nature","Type", "Depth"))]
  27. df$Origin<-file
  28. # Changing names if needed:
  29. df$Value <- as.character(df$Value)
  30. df$Value <- ifelse(df$Value == "F", "Freeing", as.character(df$Value))
  31. df$Value <- ifelse(df$Value == "A", "Allocating", as.character(df$Value))
  32. df$Value <- ifelse(df$Value == "W", "WritingBack", as.character(df$Value))
  33. df$Value <- ifelse(df$Value == "No", "Nothing", as.character(df$Value))
  34. df$Value <- ifelse(df$Value == "I", "Initializing", as.character(df$Value))
  35. df$Value <- ifelse(df$Value == "D", "Deinitializing", as.character(df$Value))
  36. df$Value <- ifelse(df$Value == "Fi", "FetchingInput", as.character(df$Value))
  37. df$Value <- ifelse(df$Value == "Po", "PushingOutput", as.character(df$Value))
  38. df$Value <- ifelse(df$Value == "C", "Callback", as.character(df$Value))
  39. df$Value <- ifelse(df$Value == "B", "Overhead", as.character(df$Value))
  40. df$Value <- ifelse(df$Value == "Sl", "Sleeping", as.character(df$Value))
  41. df$Value <- ifelse(df$Value == "P", "Progressing", as.character(df$Value))
  42. df$Value <- ifelse(df$Value == "U", "Unpartitioning", as.character(df$Value))
  43. df$Value <- ifelse(df$Value == "Ar", "AllocatingReuse", as.character(df$Value))
  44. df$Value <- ifelse(df$Value == "R", "Reclaiming", as.character(df$Value))
  45. df$Value <- ifelse(df$Value == "Co", "DriverCopy", as.character(df$Value))
  46. df$Value <- ifelse(df$Value == "CoA", "DriverCopyAsync", as.character(df$Value))
  47. # Considering only the states with a given name
  48. if (name != "All")
  49. df<-df[df$Value %in% name[[1]],]
  50. # Aligning to begin time from 0
  51. m <- min(df$Start)
  52. df$Start <- df$Start - m
  53. df$End <- df$Start+df$Duration
  54. # Taking only the states inside a given range
  55. df <- df[df$Start>=range1 & df$End<=range2,]
  56. # Return data frame
  57. df
  58. }
  59. #########################################
  60. #########################################
  61. # Main
  62. #########################################
  63. # Reading command line arguments
  64. args <- commandArgs(trailingOnly = TRUE)
  65. range1<-as.numeric(args[1])
  66. if (range1==-1)
  67. range1<-Inf
  68. range2<-as.numeric(args[2])
  69. if (range2==-1)
  70. range2<-Inf
  71. name<-strsplit(args[3], ",")
  72. # Reading first file
  73. filename<-args[4]
  74. df<-read_df(filename,range1,range2)
  75. i=5
  76. while (i <= length(args))
  77. {
  78. # Reading next input file
  79. filename<-args[i]
  80. dft<-read_df(filename,range1,range2)
  81. df<-rbindlist(list(df,dft))
  82. i <- i+1
  83. }
  84. # Error: if there is no results for a given range and state
  85. if (nrow(df)==0)
  86. stop("Result is empty!")
  87. # Plotting histograms
  88. plot <- ggplot(df, aes(x=Duration)) + geom_histogram(aes(y=..count.., fill=..count..),binwidth = diff(range(df$Duration))/30)
  89. plot <- plot + theme_bw() + scale_fill_gradient(high = "#132B43", low = "#56B1F7") + ggtitle("Histograms for state distribution") + ylab("Count") + xlab("Time [ms]") + theme(legend.position="none") + facet_grid(Origin~Value,scales = "free_y")
  90. # Adding text for total duration
  91. ad<-ggplot_build(plot)$data[[1]]
  92. al<-ggplot_build(plot)$panel$layout
  93. ad<-merge(ad,al)
  94. anno1 <- ddply(ad, .(ROW), summarise, x = max(x)*0.7, y = max(y)*0.9)
  95. anno1<-merge(anno1,al)
  96. anno2 <- ddply(df, .(Origin,Value), summarise, tot=as.integer(sum(Duration)))
  97. anno2$PANEL <- row.names(anno2)
  98. anno2$lab <- sprintf("Total duration: \n%ims",anno2$tot)
  99. anno <- merge(anno1,anno2)
  100. plot <- plot + geom_text(data = anno, aes(x=x, y=y, label=lab, colour="red"))
  101. # Printing plot
  102. plot
  103. # End
  104. write("Done producing a histogram plot. Open Rplots.pdf located in this folder to see the results", stdout())