heat: add cache miss experiment and figure
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87
garlic/exp/heat/cache.nix
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87
garlic/exp/heat/cache.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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, garlicTools
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}:
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with stdenv.lib;
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with garlicTools;
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let
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# Initial variable configuration
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varConf = with bsc; {
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cbs = range2 8 4096;
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rbs = range2 32 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 +
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".cbs-${toString cbs}" +
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".rbs-${toString rbs}";
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inherit (machineConfig) hw;
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# heat options
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timesteps = 10;
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cols = 1024 * 16; # Columns
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rows = 1024 * 16; # Rows
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cbs = c.cbs;
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rbs = c.rbs;
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gitBranch = "garlic/tampi+isend+oss+task";
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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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cpusPerTask = hw.cpusPerSocket;
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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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perf = {nextStage, conf, ...}: stages.perf {
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inherit nextStage;
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perfOptions = "stat -o .garlic/perf.csv -x , " +
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"-e cycles,instructions,cache-references,cache-misses";
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};
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exec = {nextStage, conf, ...}: stages.exec {
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inherit nextStage;
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argv = [
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"--rows" conf.rows
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"--cols" conf.cols
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"--rbs" conf.rbs
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"--cbs" conf.cbs
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"--timesteps" conf.timesteps
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];
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# The next stage is the program
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env = ''
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ln -sf ${nextStage}/etc/heat.conf heat.conf || true
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'';
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};
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program = {nextStage, conf, ...}: bsc.garlic.apps.heat.override {
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inherit (conf) gitBranch;
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};
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pipeline = stdexp.stdPipeline ++ [ perf exec program ];
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in
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stdexp.genExperiment { inherit configs pipeline; }
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@ -65,6 +65,7 @@
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heat = {
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granul = callPackage ./heat/granul.nix { };
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cache = callPackage ./heat/cache.nix { };
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};
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bigsort = rec {
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51
garlic/fig/heat/cache.R
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51
garlic/fig/heat/cache.R
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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.cbs, config.rbs, perf.cache_misses) %>%
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rename(cbs=config.cbs, rbs=config.rbs)
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df$cbs = as.factor(df$cbs)
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df$rbs = as.factor(df$rbs)
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# Normalize the time by the median
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df=group_by(df, cbs, rbs) %>%
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mutate(median.misses = median(perf.cache_misses)) %>%
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mutate(log.median.misses = log(median.misses)) %>%
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ungroup()
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ppi=300
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h=5
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w=5
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png("heatmap.png", width=1.5*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(df, aes(x=cbs, y=rbs, fill=log.median.misses)) +
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geom_raster() +
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scale_fill_gradient(high="black", low="white") +
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coord_fixed() +
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theme_bw() +
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theme(plot.subtitle=element_text(size=8)) +
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labs(x="cbs", y="rbs",
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title=sprintf("Heat granularity: cache misses"),
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subtitle=input_file)
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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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@ -46,6 +46,7 @@ in
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heat = with exp.heat; {
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granul = stdPlot ./heat/granul.R [ granul ];
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cache = customPlot ./heat/cache.R (ds.perf.stat cache.result);
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};
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creams = with exp.creams; {
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