161 lines
8.2 KiB
TeX
161 lines
8.2 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, DWARF, contains tables that, for a given
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instruction pointer (IP), permit to understand how the assembly instruction
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relates to the source code, where variables are currently allocated in memory
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or if they are stored in a register, what are their type and how to unwind the
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current stack frame. This information is generated when passing \eg{} the
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switch \lstbash{-g} to \prog{gcc} or equivalents.
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Even in stripped (non-debug) binaries, a small portion of DWARF data remains:
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the stack unwinding data. This information is necessary to unwind stack
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frames, restoring machine registers to the value they had in the previous
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frame.
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This data is structured into tables, each row corresponding to an IP range for
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which it describes valid unwinding data, and each column describing how to
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unwind a particular machine register (or virtual register used for various
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purposes). The vast majority of the rules actually used are basic --~see
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Section~\ref{ssec:instr_cov}~\textendash, consisting in offsets from memory
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addresses stored in registers (such as \reg{rbp} or \reg{rsp}). Yet, the
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standard defines rules that take the form of a stack-machine expression that
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can 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 take an unreasonable space and grow larger than
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the program itself if stored carelessly, the DWARF standard pays a great
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attention to data compactness and compression. It succeeds particularly well
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at it, but at the expense of efficiency: accessing stack
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unwinding data for a particular program point is an expensive operation --~the
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order of magnitude is $10\,\mu{}\text{s}$ on a modern computer.
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This is often not a problem, as stack unwinding is often thought of as a
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debugging procedure: when something behaves unexpectedly, the programmer might
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be interested in opening their debugger and exploring the stack. Yet, stack
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unwinding might, in some cases, be performance-critical: for instance, polling
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profilers repeatedly perform stack unwindings to observe which functions are
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active. Even worse, C++ exception handling relies on stack unwinding in order
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to find a suitable catch-block! For such applications, it might be desirable to
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find a different time/space trade-off, storing a bit more for a faster
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unwinding.
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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 been explored yet, and as of now, the most
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widely used library for stack unwinding, \prog{libunwind}~\cite{libunwind},
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essentially makes use of aggressive but fine-tuned caching and optimized code
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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, in order to
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provide fast access to the data at assembly level. This compilation process was
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fully implemented and tested on complex, real-world examples. The integration
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of compiled DWARF into existing projects have been made easy by implementing an
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alternative version of the \textit{de facto} standard library for this purpose,
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\prog{libunwind}.
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Multiple approaches have been tried and evaluated to determine which
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compilation process leads to the best time/space trade-off.
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Unexpectedly, the part that proved hardest of the project was finding and
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implementing a benchmarking protocol that was both relevant and reliable.
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Unwinding one single frame is too fast to provide a reliable benchmarking on a
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few samples (around $10\,\mu s$ per frame) to avoid statistical errors. Having
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enough samples for this purpose --~at least a few thousands~-- is not easy,
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since one must avoid unwinding the same frame over and over again, which would
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only benchmark the caching mechanism. The other problem is to distribute
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evenly the unwinding measures across the various IPs, including directly into
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the 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. Modifying \prog{perf} was an additional challenge that turned
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out to be harder than expected, since the source code is hard to read, and
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optimisations make some parts counter-intuitive. To overcome this, we designed
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an alternative version of \prog{libunwind} interfaced with the
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compiled debugging data.
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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 of this project was to design a compiled version of unwinding data
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that is faster than DWARF, while still being reliable and reasonably compact.
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The benchmarks mentioned have yielded convincing results: on the experimental
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setup created --~detailed on Section~\ref{sec:benchmarking} below~\textendash,
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the compiled version is around 26 times faster than the DWARF version, while it
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remains only around 2.5 times bigger than the original data.
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We support the vast majority --~more than $99.9\,\%$~-- of the instructions
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actually used in binaries, although we do not support all of DWARF5 instruction
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set. We are almost as robust as libunwind: on a $27000$ samples test, 885
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failures were observed for \prog{libunwind}, against $1099$ for the compiled
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DWARF version (failures are due to signal handlers, unusual instructions,
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\ldots) --~see Section~\ref{ssec:timeperf}.
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The implementation is not yet release-ready, as it does not support 100\ \% of
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the DWARF5 specification~\cite{dwarf5std} --~see Section~\ref{ssec:ehelfs}
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below. Yet, it supports the vast majority --~more than $99.9$\ \%~-- of the
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cases seen in the wild, and is decently robust compared to \prog{libunwind},
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the reference implementation. Indeed, corner cases occur often, and on a 27000
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samples test, 885 failures were observed for \prog{libunwind}, against 1099 for
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the compiled DWARF version (see Section~\ref{ssec:timeperf}).
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The implementation, however, is not production-ready: it only supports the
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x86\_64 architecture, and relies to some extent on the Linux operating system.
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None of those are real problems in practice. Supporting other processor
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architectures and ABIs are only a matter of engineering,. 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, left
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apart an annoyance. Yet, having a 26 times speed-up on stack unwinding-heavy
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tasks can be really useful to \eg{} profile large programs, particularly if one
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wants to profile many times in order to analyze the impact of multiple changes.
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It can also be useful for exception-heavy programs. Thus, we plan to address
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the limitations and integrate it cleanly with mainstream tools, such as
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\prog{perf}.
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Another research direction is to investigate how to compress even more the
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original DWARF unwinding data using outlining techniques, as we already do for
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the compiled data successfully.
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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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