155 lines
7.8 KiB
TeX
155 lines
7.8 KiB
TeX
\pagestyle{empty} %
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\thispagestyle{empty}
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%% Attention: pas plus d'un recto-verso!
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% Ne conservez pas les questions
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\section*{Internship synthesis}
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\subsection*{The general context}
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The standard debugging data format for ELF binary files, DWARF, contains a lot
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of information, which is generated mostly when passing \eg{} the switch
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\lstbash{-g} to \prog{gcc}. This information, essentially provided for
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debuggers, contains all that is needed to connect the generated assembly with
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the original code, information that can be used by sanitizers (\eg{} the type
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of each variable in the source language), etc.
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Even in stripped (non-debug) binaries, a small portion of DWARF data remains.
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Among this essential data that is never stripped is the stack unwinding data,
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which allows to unwind stack frames, restoring machine registers to the value
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they had in the previous frame, for instance within the context of a debugger
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or a profiler.
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This data is structured into tables, each row corresponding to an program
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counter (PC) range for which it describes valid unwinding data, and each column
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describing how to unwind a particular machine register (or virtual register
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used for various purposes). These rules are mostly basic, consisting in offsets
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from memory addresses stored in registers (such as \reg{rbp} or \reg{rsp}), but
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in some cases, they can take the form of a stack-machine expression that can
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access virtually all the process's memory and perform Turing-complete
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computation~\cite{oakley2011exploiting}.
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\subsection*{The research problem}
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As debugging data can easily get heavy beyond reasonable if stored carelessly,
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the DWARF standard pays a great attention to data compactness and compression,
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and succeeds particularly well at it. But this, as always, is at the expense
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of efficiency: accessing stack unwinding data for a particular program point
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can be quite costly.
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This is often not a huge problem, as stack unwinding is mostly thought of as a
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debugging procedure: when something behaves unexpectedly, the programmer might
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be interested in exploring the stack. Yet, stack unwinding might, in some
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cases, be performance-critical: for instance, profiler programs needs to
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perform a whole lot of stack unwindings. Even worse, exception handling relies
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on stack unwinding in order to find a suitable catch-block! For such
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applications, it might be desirable to find a different time/space trade-off,
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allowing a slightly space-heavier, but far more time-efficient unwinding
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procedure.
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This different trade-off is the question that I explored during this
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internship: what good alternative trade-off is reachable when storing the stack
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unwinding data completely differently?
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It seems that the subject has not really been explored yet, and as of now, the
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most widely used library for stack unwinding,
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\prog{libunwind}~\cite{libunwind}, essentially makes use of aggressive but
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fine-tuned caching and optimized code to mitigate this problem.
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% What is the question that you studied?
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% Why is it important, what are the applications/consequences?
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% Is it a new problem?
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% If so, why are you the first researcher in the universe who consider it?
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% If not, why did you think that you could bring an original contribution?
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\subsection*{Your contribution}
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This internship explored the possibility to compile DWARF's stack unwinding
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data directly into native assembly on the x86\_64 architecture. Instead of
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parsing and interpreting at runtime the debug data, the stack unwinding data is
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accessed as a function of a dynamically-loaded shared library.
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Multiple approaches have been tried, in order to determine which compilation
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process leads to the best time/space trade-off.
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Quite unexpectedly, the part that proved hardest of the project was finding a
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benchmarking protocol that was both relevant and reliable. Unwinding one single
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frame is way too fast to be benched on a few samples (around $10\,\mu s$ per
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frame), and having a lot of samples is quite complex, since one must avoid
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unwinding the same frame over and over again, which would only benchmark the
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caching mechanism. The other problem is to distribute evenly the unwinding
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measures across the various program positions, including directly into the
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loaded libraries (\eg{} the \prog{libc}).
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The solution eventually chosen was to modify \prog{perf}, the standard
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profiling program for Linux, in order to gather statistics and benchmarks of
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its unwindings, and produce an alternative version of \prog{libunwind} using
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the compiled debugging data, in order to interface it with \prog{perf},
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allowing to benchmark \prog{perf} with both the standard stack unwinding data
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and the alternative experimental compiled format. As a free and enjoyable
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side-effect, the experimental unwinding data is perfectly interfaced with
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\prog{libunwind}, and thus interfaceable at practically no cost with any
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existing project using the \textit{de facto} standard library \prog{libunwind}.
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% What is your solution to the question described in the last paragraph?
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%
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% Be careful, do \emph{not} give technical details, only rough ideas!
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%
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% Pay a special attention to the description of the \emph{scientific} approach.
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\subsection*{Arguments supporting its validity}
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% What is the evidence that your solution is a good solution?
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% Experiments? Proofs?
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%
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% Comment the robustness of your solution: how does it rely/depend on the working assumptions?
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The goal was to obtain a compiled version of unwinding data that was faster
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than DWARF, reasonably heavier and reliable. The benchmarks mentioned have
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yielded convincing results: on the experimental setup created (detailed later
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in this report), the compiled version is up to 25 times faster than the DWARF
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version, while it remains only around 2.5 times bigger than the original data.
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Even though the implementation is more a research prototype than a release
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version, is still reasonably robust, compared to \prog{libunwind}, which is
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built for robustness. Corner cases are frequent while analyzing stack data, and
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even more when analyzing them through a profiler; yet the prototype fails only
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on around 200 cases more than \prog{libunwind} on a 27000 samples test (1099
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failures, against 885 for \prog{libunwind}).
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The prototype, unlike \prog{libunwind}, does not support $100\,\%$ of the DWARF
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instructions present in the DWARF5 standard~\cite{dwarf5std}. It is also
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limited to the x86\_64 architecture, and relies to some extent on the Linux
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operating system. But none of those limitations are real problems in practice.
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As argued later on, the vast majority of the DWARF instruction set actually
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used in the wild is implemented; other processor architectures and ABIs are
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only a matter of time spent and engineering work; and the operating system
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dependency is only present in the libraries developed in order to interact with
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the compiled unwinding data, which can be developed for virtually any operating
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system.
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\subsection*{Summary and future work}
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In most cases of everyday's life, a slow stack unwinding is not a problem, or
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even an annoyance. Yet, having a 25 times speed-up on stack unwinding-heavy
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tasks, such as profiling, can be really useful to profile heavy programs,
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particularly if one wants to profile many times in order to analyze the impact
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of multiple changes. It can also be useful for exception-heavy
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programs~\qtodo{cite Stephen's software?}. Thus, it might be interesting to
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implement a more stable version, and try to interface it cleanly with
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mainstream tools, such as \prog{perf}.
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Another question worth exploring might be whether it is possible to shrink even
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more the original DWARF unwinding data, which would be stored in a format not
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too far from the original standard, by applying techniques close to those
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used to shrink the compiled unwinding data.
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% What is next? In which respect is your approach general?
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% What did your contribution bring to the area?
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% What should be done now?
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% What is the good \emph{next} question?
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\pagestyle{plain}
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\newpage
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