From ee94a849ecb331d3d506dbd7467f01f79263bf17 Mon Sep 17 00:00:00 2001
From: Martina Maggio <maggio.martina@gmail.com>
Date: Tue, 9 Apr 2019 20:43:09 +0200
Subject: [PATCH] adding readme
---
artifact/README | 186 ++++++++++++++++++++++++++++++++++++++++++++++++
1 file changed, 186 insertions(+)
create mode 100644 artifact/README
diff --git a/artifact/README b/artifact/README
new file mode 100644
index 0000000..7b0f5ee
--- /dev/null
+++ b/artifact/README
@@ -0,0 +1,186 @@
+
+------------------------------------------------------------------
+*** GENERAL INFORMATION ***
+------------------------------------------------------------------
+
+This artifact complements the paper
+
+ DMAC: Deadline-Miss-Aware Control
+ P. Pazzaglia, C. Mandrioli, M. Maggio, and A. Cervin
+ Euromicro Conference on Real-Time Systems (ECRTS), 2019
+
+The paper describes a synthesis technique for controllers that are
+aware of deadline misses and can use three different strategies to
+handle the misses: kill the job, let the job continue and skip the
+next, let the job continue and queue the next using a queue of
+maximum size 1 that contains the freshest job.
+
+The code reproduces figures 7, 8, and 9 from the paper.
+
+------------------------------------------------------------------
+*** EXECUTION INSTRUCTIONS ***
+------------------------------------------------------------------
+
+Requirements for the code execution:
+
+ * The code is better run in a Unix platform. Specifically, the code
+ has been tested on both Linux (Fedora 25) and MAC OS X. It is
+ possible to run the code on Windows machines, but not following
+ these instructions (automation via shell scripting does not work).
+
+ * The code requires: a C++ compiler, MATLAB, and a bash shell. The
+ code has been tested with clang++ on Mac OS and g++ on Linux and
+ with different versions of MATLAB (from R2012 to R2016a).
+ Finally, the code requires a full version of latex installed for
+ the generation of the figures (that uses tikz and pgfplots).
+
+The artifact has the following folder structure:
+
+ | - figures
+ | | - fig7.tex
+ | | - fig8.tex
+ | | - fig9.tex
+ | - src
+ | | - matlab
+ | | | - ...
+ | | - scenario
+ | | | - ...
+ | | - sim
+ | | | - ...
+ | - tasksets
+ | | - ...
+ | generate_results.sh
+ | process_results.sh
+ | plot_results.sh
+
+ The folder tasksets contains many tasksets that can be tested. In
+ the figures shown in the paper we use 7 of these tasksets:
+ n5_u70taskset_25.csv,
+ n5_u70taskset_100.csv,
+ n5_u80taskset_25.csv,
+ n10_u70taskset_25.csv,
+ n10_u70taskset_100.csv,
+ n20_u70taskset_25.csv,
+ n20_u70taskset_100.csv.
+ The other files are given in case the reviewer wants to experiment
+ with different values (this requires modifications of the scripts).
+
+ The folder figures contains the latex sources for the figures.
+
+ The folder src contains the source code.
+
+ Finally, there are three scripts in the main folder:
+ generate_results.sh, process_results.sh, and plot_results.sh.
+
+To run the code for the artifact four steps are required:
+
+ 1) Modify the MATLAB path folder in process_results.sh to point to
+ the folder where MATLAB is installed. Two examples are given for
+ standard Linux and MAC OS X installations.
+
+ MATLABPATH="/usr/local"
+ MATLABPATH="/Applications/MATLAB_R2017a.app"
+
+ 2) Open a terminal and run the script to generate the result files
+ with the following command:
+
+ chmod a+x generate_results.sh && ./generate_results.sh
+
+ NOTE: this command will take quite a long time to execute.
+ On an machine with 8 cores this command ran for >48 hours.
+
+ Running this script performs the following operations:
+
+ - runs the scenario theory C program to determine the
+ number of experiments to perform
+ - runs the C++ simulator to produce the data (this step is
+ parallelized, 7 processes called "simulator" are launched),
+ they write files in the "results" folder that is created by
+ the script
+
+ The output shown at the command line should resemble this:
+
+ ************************************************************
+ ~$ ./generate_results.sh
+
+ ------------------------------------------------
+ Scenario Theory:
+ ------------------------------------------------
+ epsilon = 0.003000
+ beta = 0.010000
+ experiments = 1533
+ ------------------------------------------------
+ Simulator:
+ ------------------------------------------------
+ num_tests = 1533
+ num_jobs = 500
+ number of time steps = 15
+ num samples execution time = 5
+ skew factor = 0.75
+ - launched result generation for n5_u70taskset_25.csv
+ - launched result generation for n10_u70taskset_25.csv
+ - launched result generation for n20_u70taskset_25.csv
+ - launched result generation for n20_u70taskset_100.csv
+ - launched result generation for n5_u80taskset_25.csv
+ - launched result generation for n10_u70taskset_100.csv
+ - launched result generation for n5_u70taskset_100.csv
+ ------------------------------------------------
+ data generation terminated
+ ------------------------------------------------
+
+ ************************************************************
+
+ 3) Once step 2 is completed run the script to process the data,
+ generate the controller and perform the control analysis, with
+ the following command:
+
+ chmod a+x process_results.sh && ./process_results.sh
+
+ NOTE: this command will take some time to execute.
+ On an machine with 8 cores this command ran for >8 hours.
+
+ Running this script runs the MATLAB program that processes the
+ data (in a parallelized form). The output shown at the command
+ line should resemble this:
+
+ ************************************************************
+
+ ------------------------------------------------
+ Matlab wrote results for n10_u70_f100
+ Matlab wrote results for n10_u70_f25
+ Matlab wrote results for n20_u70_f100
+ Matlab wrote results for n20_u70_f25
+ Matlab wrote results for n5_u70_f100
+ Matlab wrote results for n5_u70_f25
+ Matlab wrote results for n5_u80_f25
+ ------------------------------------------------
+ data processing terminated
+ ------------------------------------------------
+
+ ************************************************************
+
+ 4) Once step 3 is completed run the script to generate the figures
+ for the paper using the following command:
+
+ chmod a+x plot_results.sh && ./plot_results.sh
+
+ This command uses the results saved in the result folder to plot
+ the figures that are shown in the paper. In particular, the
+ script generates three files {fig7.pdf, fig8.pdf, fig9.pdf} that
+ correspond to the paper figures.
+
+ Due to randomness (in the sequence generation), the figures may
+ differ from the paper ones, but the trends should be the same
+ and the plots should generally be similar.
+
+-----
+NOTE:
+-----
+
+ It is possible to bypass step 1, 2 and 3, downloading the zip files
+ that contains the result files from the following link:
+
+ http://XXX
+
+ Once downloaded, unzip the file in the artifact folder and
+ follow (only) step 4.
--
GitLab