Saiph: adding granularity experiment and figures

This commit is contained in:
Sandra 2020-11-12 19:37:30 +01:00
parent 86d1d426ec
commit 4ae66adb9a
4 changed files with 192 additions and 7 deletions

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@ -8,10 +8,15 @@
, boost
, gitBranch ? "master"
, numComm ? null
, nbx ? null
, nby ? null
, nbz ? null
, vectFlags ? null
#, breakpointHook
}:
with stdenv.lib;
stdenv.mkDerivation rec {
name = "saiph";
@ -20,7 +25,7 @@ stdenv.mkDerivation rec {
ref = "${gitBranch}";
};
programPath = "/bin/ExHeat3D";
programPath = "/bin/Heat3D_vect";
enableParallelBuilding = true;
dontStrip = true;
@ -49,15 +54,18 @@ stdenv.mkDerivation rec {
makeFlags = [
"-f" "Makefile.${cc.cc.CC}"
"apps"
"APP=ExHeat3D"
( if (numComm != null) then "NUM_COMM=${toString numComm}" else "" )
( if (vectFlags != null) then "VECT_FLAGS=${toString vectFlags}" else "" )
];
"APP=Heat3D_vect"
] ++ optional (nbx != null) "NB_X=${toString nbx}"
++ optional (nby != null) "NB_Y=${toString nby}"
++ optional (nbz != null) "NB_Z=${toString nbz}"
++ optional (numComm != null) "NUM_COMM=${toString numComm}"
++ optional (vectFlags != null) "VECT_FLAGS=${toString vectFlags}"
;
installPhase = ''
mkdir -p $out/lib
mkdir -p $out/bin
cp obj/libsaiphv2.so $out/lib/
cp bin/ExHeat3D $out/bin/
cp bin/Heat3D_vect $out/bin/
'';
}

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@ -0,0 +1,68 @@
{
stdenv
, stdexp
, bsc
, targetMachine
, stages
}:
with stdenv.lib;
let
# Initial variable configuration
varConf = with bsc; {
nb = [ 1 2 4 8 ];
};
# Generate the complete configuration for each unit
genConf = with bsc; c: targetMachine.config // rec {
expName = "saiph.granularity";
unitName = "${expName}.nbx-nby-nbz-${toString nbx}-${toString nby}-${toString nbz}";
# saiph options
nbx = c.nb;
nby = c.nb;
nbz = c.nb;
mpi = impi;
gitBranch = "garlic/tampi+isend+oss+task+simd";
# Repeat the execution of each unit 50 times
loops = 50;
# Resources
qos = "debug";
time = "00:30:00";
ntasksPerNode = 1;
nodes = 1;
cpuBind = "sockets,verbose";
jobName = "${unitName}-${gitBranch}";
};
# Compute the array of configurations
configs = stdexp.buildConfigs {
inherit varConf genConf;
};
exec = {nextStage, conf, ...}: with conf; stages.exec {
inherit nextStage;
env = ''
export OMP_NUM_THREADS=${toString hw.cpusPerSocket}
export NANOS6_REPORT_PREFIX="#"
export I_MPI_THREAD_SPLIT=1
export ASAN_SYMBOLIZER_PATH=${bsc.clangOmpss2Unwrapped}/bin/llvm-symbolizer
'';
};
program = {nextStage, conf, ...}: with conf;
let
customPkgs = stdexp.replaceMpi conf.mpi;
in
customPkgs.apps.saiph.override {
inherit nbx nby nbz mpi gitBranch;
};
pipeline = stdexp.stdPipeline ++ [ exec program ];
in
stdexp.genExperiment { inherit configs pipeline; }

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@ -0,0 +1,100 @@
library(ggplot2)
library(dplyr)
library(scales)
library(jsonlite)
args=commandArgs(trailingOnly=TRUE)
# Read the timetable from args[1]
input_file = "input.json"
if (length(args)>0) { input_file = args[1] }
# Load the dataset in NDJSON format
dataset = jsonlite::stream_in(file(input_file)) %>%
jsonlite::flatten()
# We only need the nblocks and time
df = select(dataset, config.nbx, time) %>%
rename(nbx=config.nbx)
df$nbx = as.factor(df$nbx)
# Normalize the time by the median
D=group_by(df, nbx) %>%
mutate(tnorm = time / median(time) - 1) %>%
mutate(bad = max(ifelse(abs(tnorm) >= 0.01, 1, 0)))
D$bad = as.factor(D$bad)
print(D)
ppi=300
h=5
w=5
png("box.png", width=w*ppi, height=h*ppi, res=ppi)
#
#
#
# Create the plot with the normalized time vs nblocks
p = ggplot(data=D, aes(x=nbx, y=tnorm, color=bad)) +
# Labels
labs(x="nbx", y="Normalized time",
title=sprintf("Saiph-Heat3D normalized time"),
subtitle=input_file) +
# Center the title
#theme(plot.title = element_text(hjust = 0.5)) +
# Black and white mode (useful for printing)
#theme_bw() +
# Add the maximum allowed error lines
geom_hline(yintercept=c(-0.01, 0.01),
linetype="dashed", color="gray") +
# Draw boxplots
geom_boxplot() +
scale_color_manual(values=c("black", "brown")) +
#scale_y_continuous(breaks = scales::pretty_breaks(n = 10)) +
theme_bw() +
theme(plot.subtitle=element_text(size=8)) +
theme(legend.position = "none")
#theme(legend.position = c(0.85, 0.85))
# Render the plot
print(p)
## Save the png image
dev.off()
#
png("scatter.png", width=w*ppi, height=h*ppi, res=ppi)
#
## Create the plot with the normalized time vs nblocks
p = ggplot(D, aes(x=nbx, y=time)) +
labs(x="nbx", y="Time (s)",
title=sprintf("Saiph-Heat3D granularity"),
subtitle=input_file) +
theme_bw() +
theme(plot.subtitle=element_text(size=8)) +
theme(legend.position = c(0.5, 0.88)) +
geom_point(shape=21, size=3) +
#scale_x_continuous(trans=log2_trans()) +
scale_y_continuous(trans=log2_trans())
# Render the plot
print(p)
# Save the png image
dev.off()

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@ -330,6 +330,7 @@ let
saiph = {
numcomm = callPackage ./garlic/exp/saiph/numcomm.nix { };
granularity = callPackage ./garlic/exp/saiph/granularity.nix { };
};
creams = {
@ -371,6 +372,7 @@ let
saiph = with exp.saiph; {
numcomm = merge [ numcomm ];
granularity = merge [ granularity ];
};
heat = with exp.heat; {
@ -402,6 +404,13 @@ let
};
};
saiph = {
granularity = with ds.saiph; pp.rPlot {
script = ./garlic/fig/saiph/granularity.R;
dataset = granularity;
};
};
heat = {
test = with ds.heat; pp.rPlot {
script = ./garlic/fig/heat/test.R;