[llvm-dev] The AnghaBench collection of compilable programs (original) (raw)
Fernando Magno Quintao Pereira via llvm-dev llvm-dev at lists.llvm.org
Sat Feb 22 06:55:03 PST 2020
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Dear LLVMers,
we, at UFMG, have been building a large collection of compilablebenchmarks. Today, we have one million C files, mined from open-source repositories, that compile into LLVM bytecodes (and from there to object files). To ensure compilation, we perform type inference on the C programs. Type inference lets us replace missing dependencies.
The benchmarks are available at: http://cuda.dcc.ufmg.br/angha/
We have a technical report describing the construction of this collection: http://lac.dcc.ufmg.br/pubs/TechReports/LaC_TechReport012020.pdf
Many things can be done with so many LLVM bytecodes. A few examples follow below:
We can autotune compilers. We have trained YaCoS, a tool used to find good optimization sequences. The objective function is code size. We find the best optimization sequence for each program in the database. To compile an unknown program, we get the program in the database that is the closest, and apply the same optimization sequence. Results are good: we can improve on clang -Oz by almost 10% in MiBench, for instance.
We can perform many types of explorations on real-world code. For instance, we have found that 95.4% of all the interference graphs of these programs, even in machine code (no phi-functions and lots of pre-colored registers), are chordal.
We can check how well different tools are doing on real-world code. For instance, we can use these benchmarks to check how many programs can be analyzed by Ultimate Buchi Automizer (https://ultimate.informatik.uni-freiburg.de/downloads/BuchiAutomizer/). This is a tool that tries to prove termination or infinite execution for some programs.
We can check how many programs can be compiled by different high-level synthesis tools into FPGAs. We have tried LegUp and Vivado, for instance.
Our webpage contains a search box, so that you can get the closest programs to a given input program. Currently, we measure program distance as the Euclidian distance on Namolaru feature vectors.
We do not currently provide inputs for those programs. It's possible to execute the so called "leaf-functions", e.g., functions that do not call other routines. We have thousands of them. However, we do not guarantee the absence of undefined behavior during the execution.
Regards,
Fernando
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