heat: Add test experiment and plot
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garlic/exp/heat/test.nix
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66
garlic/exp/heat/test.nix
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{
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stdenv
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, stdexp
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, bsc
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, targetMachine
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, stages
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}:
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with stdenv.lib;
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let
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# Initial variable configuration
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varConf = with bsc; {
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bsx = [ 1024 2048 4096 ];
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};
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machineConfig = targetMachine.config;
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# Generate the complete configuration for each unit
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genConf = with bsc; c: targetMachine.config // rec {
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expName = "heat";
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unitName = "${expName}.bsx-${toString bsx}";
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inherit (machineConfig) hw;
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# heat options
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inherit (c) bsx;
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timesteps = 10;
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# Repeat the execution of each unit 30 times
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loops = 10;
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# Resources
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qos = "debug";
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ntasksPerNode = 1;
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nodes = 1;
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time = "02:00:00";
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# Assign one socket to each task (only one process)
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cpuBind = "verbose,sockets";
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jobName = unitName;
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};
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# Compute the array of configurations
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configs = stdexp.buildConfigs {
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inherit varConf genConf;
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};
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exec = {nextStage, conf, ...}: with conf; stages.exec {
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inherit nextStage;
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argv = [ "-s" 1024 "-t" timesteps ];
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env = ''
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export LD_DEBUG=libs
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export NANOS6_LOADER_VERBOSE=1
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cp ${nextStage}/etc/heat.conf .
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'';
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};
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program = {nextStage, conf, ...}: with conf;
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bsc.garlic.apps.heat.override {
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inherit bsx;
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};
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pipeline = stdexp.stdPipeline ++ [ exec program ];
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in
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stdexp.genExperiment { inherit configs pipeline; }
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95
garlic/fig/heat/test.R
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95
garlic/fig/heat/test.R
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@ -0,0 +1,95 @@
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library(ggplot2)
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library(dplyr)
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library(scales)
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library(jsonlite)
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args=commandArgs(trailingOnly=TRUE)
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# Read the timetable from args[1]
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input_file = "input.json"
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if (length(args)>0) { input_file = args[1] }
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# Load the dataset in NDJSON format
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dataset = jsonlite::stream_in(file(input_file)) %>%
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jsonlite::flatten()
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# We only need the nblocks and time
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df = select(dataset, config.bsx, time) %>%
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rename(bsx=config.bsx)
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df$bsx = as.factor(df$bsx)
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# Normalize the time by the median
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D=group_by(df, bsx) %>%
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mutate(tnorm = time / median(time) - 1)
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print(D)
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ppi=300
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h=5
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w=5
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png("box.png", width=w*ppi, height=h*ppi, res=ppi)
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#
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#
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#
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# Create the plot with the normalized time vs nblocks
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p = ggplot(data=D, aes(x=bsx, y=tnorm)) +
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# Labels
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labs(x="bsx", y="Normalized time",
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title=sprintf("Heat normalized time"),
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subtitle=input_file) +
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# Center the title
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#theme(plot.title = element_text(hjust = 0.5)) +
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# Black and white mode (useful for printing)
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#theme_bw() +
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# Add the maximum allowed error lines
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geom_hline(yintercept=c(-0.01, 0.01),
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linetype="dashed", color="red") +
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# Draw boxplots
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geom_boxplot() +
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#scale_y_continuous(breaks = scales::pretty_breaks(n = 10)) +
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theme_bw() +
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theme(plot.subtitle=element_text(size=8)) +
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theme(legend.position = c(0.85, 0.85)) #+
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# Render the plot
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print(p)
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## Save the png image
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dev.off()
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#
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png("scatter.png", width=w*ppi, height=h*ppi, res=ppi)
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#
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## Create the plot with the normalized time vs nblocks
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p = ggplot(D, aes(x=bsx, y=time)) +
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labs(x="bsx", y="Time (s)",
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title=sprintf("Heat granularity"),
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subtitle=input_file) +
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theme_bw() +
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theme(plot.subtitle=element_text(size=8)) +
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theme(legend.position = c(0.5, 0.88)) +
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geom_point(shape=21, size=3) +
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#scale_x_continuous(trans=log2_trans()) +
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scale_y_continuous(trans=log2_trans())
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# Render the plot
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print(p)
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# Save the png image
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dev.off()
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18
overlay.nix
18
overlay.nix
@ -340,6 +340,10 @@ let
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mpi_omp = callPackage ./garlic/exp/hpcg/mpi+omp.nix { };
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oss = callPackage ./garlic/exp/hpcg/oss.nix { };
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};
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heat = {
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test = callPackage ./garlic/exp/heat/test.nix { };
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};
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};
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# Datasets used in the figures
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@ -353,27 +357,35 @@ let
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hpcg = with exp.hpcg; {
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oss = merge [ oss ];
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};
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heat = with exp.heat; {
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test = merge [ test ];
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};
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};
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# Figures generated from the experiments
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fig = with self.bsc.garlic; {
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nbody = {
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baseline = pp.rPlot {
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script = ./garlic/fig/nbody/baseline.R;
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dataset = ds.nbody.baseline;
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};
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jemalloc = pp.rPlot {
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script = ./garlic/fig/nbody/jemalloc.R;
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dataset = ds.nbody.jemalloc;
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};
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freeCpu = pp.rPlot {
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script = ./garlic/fig/nbody/freeCpu.R;
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dataset = ds.nbody.freeCpu;
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};
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};
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heat = {
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test = with ds.heat; pp.rPlot {
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script = ./garlic/fig/heat/test.R;
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dataset = test;
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};
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};
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};
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};
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