Effective Performance Issue Diagnosis with Value-Assisted Cost Profiling

Diagnosing performance issues is often difficult, especially when they occur only during some program executions. Profilers can help with performance debugging, but are ineffective when the most costly functions are not the root causes of performance issues. To address this problem, we introduce a new profiling methodology, value-assisted cost profiling, and a tool vprof. Our insight is that capturing the values of variables can greatly help diagnose performance issues. vprof continuously records values while profiling normal and buggy program executions. It identifies anomalies in the values and the functions where they occur to pinpoint the real root causes of performance issues.

Download the directory

git clone git@github.com:wenglingmei/vprofAE.git

Install software dependencies

install llvm-project

$ git clone https://github.com/llvm/llvm-project.git
$ cd llvm-project
$ cmake -S llvm -B build -G "Unix Makefiles" -DLLVM_ENABLE_PROJECTS="clang;lld" -DCMAKE_BUILD_TYPE=Release
$ cmake --build .

install libunwind

$ git clone https://github.com/libunwind/libunwind.git
$ cd libunwind
$ autoreconf -i
$ ./configure
$ make
$ make install

install pytelftools

$ pip install pyelftools

Create a soft link from llvm-project/build to /usr/local/opt/llvm

$ ln -s llvm-project/build /usr/local/opt/llvm

Setup vprof

$./prepare.sh

Run testcase.

$ cd redis-8145
$./test.sh

Reference

Effective Performance Issue Diagnosis with Value-Assisted Cost Profiling (Eurosys'23)