starpu_paje_state_stats.R 4.4 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 $inputfiles
  18. # Package containing ddply function
  19. library(plyr)
  20. # Function for reading .csv file
  21. read_df <- function(file,range1,range2) {
  22. df<-read.csv(file, header=FALSE, strip.white=TRUE)
  23. names(df) <- c("Nature","ResourceId","Type","Start","End","Duration", "Depth", "Value")
  24. df = df[!(names(df) %in% c("Nature","Type", "Depth"))]
  25. # Changing names if needed:
  26. df$Value <- as.character(df$Value)
  27. df$Value <- ifelse(df$Value == "F", "Freeing", as.character(df$Value))
  28. df$Value <- ifelse(df$Value == "A", "Allocating", as.character(df$Value))
  29. df$Value <- ifelse(df$Value == "W", "WritingBack", as.character(df$Value))
  30. df$Value <- ifelse(df$Value == "No", "Nothing", as.character(df$Value))
  31. df$Value <- ifelse(df$Value == "I", "Initializing", as.character(df$Value))
  32. df$Value <- ifelse(df$Value == "D", "Deinitializing", as.character(df$Value))
  33. df$Value <- ifelse(df$Value == "Fi", "FetchingInput", as.character(df$Value))
  34. df$Value <- ifelse(df$Value == "Po", "PushingOutput", as.character(df$Value))
  35. df$Value <- ifelse(df$Value == "C", "Callback", as.character(df$Value))
  36. df$Value <- ifelse(df$Value == "B", "Overhead", as.character(df$Value))
  37. df$Value <- ifelse(df$Value == "Sl", "Sleeping", as.character(df$Value))
  38. df$Value <- ifelse(df$Value == "P", "Progressing", as.character(df$Value))
  39. df$Value <- ifelse(df$Value == "U", "Unpartitioning", as.character(df$Value))
  40. df$Value <- ifelse(df$Value == "Ar", "AllocatingReuse", as.character(df$Value))
  41. df$Value <- ifelse(df$Value == "R", "Reclaiming", as.character(df$Value))
  42. df$Value <- ifelse(df$Value == "Co", "DriverCopy", as.character(df$Value))
  43. df$Value <- ifelse(df$Value == "CoA", "DriverCopyAsync", as.character(df$Value))
  44. df$Value <- ifelse(df$Value == "Su", "SubmittingTask", as.character(df$Value))
  45. # Considering only the states with a given name
  46. if (name != "All")
  47. df<-df[df$Value %in% name[[1]],]
  48. # Aligning to begin time from 0
  49. m <- min(df$Start)
  50. df$Start <- df$Start - m
  51. df$End <- df$Start+df$Duration
  52. # Taking only the states inside a given range
  53. df <- df[df$Start>=range1 & df$End<=range2,]
  54. # Return data frame
  55. df
  56. }
  57. #########################################
  58. #########################################
  59. # Main
  60. #########################################
  61. # Reading command line arguments
  62. args <- commandArgs(trailingOnly = TRUE)
  63. range1<-as.numeric(args[1])
  64. if (range1==-1)
  65. range1<-Inf
  66. range2<-as.numeric(args[2])
  67. if (range2==-1)
  68. range2<-Inf
  69. name<-strsplit(args[3], ",")
  70. outputfile<-args[4]
  71. # Reading first file
  72. filename<-args[5]
  73. df<-read_df(filename,range1,range2)
  74. # Getting summary of the first file
  75. dfout<-ddply(df, c("Value"), summarize, Events_ = length(as.numeric(Duration)), Duration_ = sum(as.numeric(Duration)))
  76. names(dfout)<-c("Value",sprintf("Events_%s",filename),sprintf("Duration_%s",filename))
  77. i=6
  78. while (i <= length(args))
  79. {
  80. # Reading next input file
  81. filename<-args[i]
  82. df<-read_df(filename,range1,range2)
  83. # Getting summary of the next file
  84. dp<-ddply(df, c("Value"), summarize, Events_ = length(as.numeric(Duration)), Duration_ = sum(as.numeric(Duration)))
  85. names(dp)<-c("Value",sprintf("Events_%s",filename),sprintf("Duration_%s",filename))
  86. # Merging results into one single data frame
  87. if (nrow(dp)>0)
  88. {
  89. if (nrow(dfout)>0)
  90. dfout<-merge(dfout,dp, by = "Value", all=TRUE)
  91. else
  92. dfout<-dp
  93. }
  94. i <- i+1
  95. }
  96. # Cosmetics: change NA to 0
  97. dfout[is.na(dfout)] <- 0
  98. # Error: if there is no results for a given range and state
  99. if (nrow(dfout)==0)
  100. stop("Result is empty!")
  101. # Write results into the new .csv file
  102. write.table(dfout, file=outputfile, row.names=FALSE, sep = ", ")