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This exercise uses a graph-plotting program (gnuplot) to convert tabular data into an image. This is a technique that is very widely used to visualize scientific data; with appropriate instructions, gnuplot can produce significantly more complex graphs than almost all of its competitors.
Note that povray and gnuplot have quite substantially different ways of being controlled. The povray executable (from the previous example) has a complex command line interface that has been configured into the Unicore server. By comparison, gnuplot is extremely simple (so much so that it doesn't need explicit support at the server level) but it has to have the name of associated files placed in its control file: this increased coupling tends to make code more fragile.
1. Save this job definition to a JSON file called gnuplot.u:
{
Executable: "/bin/sh",
Arguments: ["control.sh"],
Imports: [
{From: "control.sh", To: "control.sh"},
{From: "data.csv", To: "data.csv"},
],
Exports: [
{From: "output.png", To: "plot.png"}
}
Research the phenomenon of data races. Give an example of how an unprotected data race can give rise to data inconsistency. How do OpenMP and Cilk resolve this problem? Data
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what are disadvantages of using single directory
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