Start writing about benchmarking

report/report.tex

@@ -740,13 +740,49 @@ data could be efficiently compressed in this way.
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 \section{Benchmarking}
 
+Benchmarking turned out to be, quite surprisingly, the hardest part of the
+project. It ended up requiring a lot of investigation to find a working
+protocol, and afterwards, a good deal of code reading and coding to get the
+solution working.
+
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 \subsection{Requirements}
-\todo{}
+
+To provide relevant benchmarks of the \ehelfs{} performance, one must sample at
+least a few hundreds or thousands of stack unwinding, since a single frame
+unwinding with regular DWARF takes the order of magnitude of $10\,\mu s$, and
+\ehelfs{} were expected to have significantly better performance.
+
+However, unwinding over and over again from the same program point would have
+had no interest at all, since \prog{libunwind} would have simply cached the
+relevant DWARF row. In the mean time, making sure that the various unwinding
+are made from different locations is somehow cheating, since it makes useless
+\prog{libunwind}'s caching. All in all, the benchmarking method must have a
+``natural'' distribution of unwindings.
+
+Another requirement is to also distribute quite evenly the unwinding points
+across the program: we would like to benchmark stack unwindings crossing some
+standard library functions, starting from inside them, etc.
+
+Finally, the unwound program must be interesting enough to enter and exit a lot
+of function, nest function calls, have FDEs that are not as simple as in
+Listing~\ref{lst:ex1_dw}, etc.
+
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 \subsection{Presentation of \prog{perf}}
-\todo{}
+
+\prog{Perf} is a \emph{profiler} that comes with the Linux ecosystem (actually,
+\prog{perf} is developed within the Linux kernel source tree). A profiler is a
+program that analyzes the performance of programs by recording the time spent
+in each function, including within nested calls.
+
+For this purpose, the basic idea is to stop the traced program at regular
+intervals, unwind its stack, write down the current nested function calls, and
+integrate the sampled data in the end.
+
+\todo{Is it necessary to write more about \prog{perf} here?}
+
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 \subsection{Benchmarking with \prog{perf}}