[llvm-dev] The AnghaBench collection of compilable programs (original) (raw)

Chris Lattner via llvm-dev llvm-dev at lists.llvm.org
Fri Feb 28 18:07:14 PST 2020

Sounds great! If there are any that can be merged into test-suite, that would make it easier for CI systems to use it.

-Chris

On Feb 28, 2020, at 3:21 AM, Fernando Magno Quintao Pereira <pronesto at gmail.com> wrote:

Thank you for the feedback, Chris and Florian. We will start updating the benchmarks with the licenses from the original repositories where they came from. Once we update the individual benchmarks, we will try to make them available as an external test in LLVM. Regards, Fernando On Fri, Feb 28, 2020 at 2:21 AM Chris Lattner <clattner at nondot.org> wrote:

Hi Fernando, My understanding is that LLVM’s test-suite is under a weird mix of different licenses. So long as you preserve the original licenses (and only include ones with reasonable licenses), it should be possible I think. -Chris

On Feb 22, 2020, at 12:30 PM, Fernando Magno Quintao Pereira via llvm-dev <llvm-dev at lists.llvm.org> wrote:

Hi Florian, we though about using UIUC, like in LLVM. Do you guys know if that could be a problem, given that we are mining the functions from github?

Have you thought about integrating the benchmarks as external tests into LLVM’s test-suite? That would make it very easy to play around with. We did not think about it actually. But we would be happy to do it, if the community accepts it. Regards, Fernando On Sat, Feb 22, 2020 at 5:16 PM Florian Hahn <florianhahn at apple.com> wrote:

Hi Fernando, That sounds like a very useful resource to improve testing and also get easier access to good stress tests (e.gQuite a few very large functions have proven to surface compile time problems in some backend passes). From a quick look on the website I couldn’t find under which license the code is published. That may be a problem for some users. Have you thought about integrating the benchmarks as external tests into LLVM’s test-suite? That would make it very easy to play around with. Cheers, Florian

On 22 Feb 2020, at 14:56, Fernando Magno Quintao Pereira via llvm-dev <llvm-dev at lists.llvm.org> wrote:

Dear LLVMers, we, at UFMG, have been building a large collection of compilable benchmarks. 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/LaCTechReport012020.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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