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I'm not sure if this will give exactly what you want as it's more meant for benchmarking speed of forward/rev model vs size.
For the mvn benchmarks, it's known that multivariate_normal and multivariate_normal_prec are not fully optimized (see stan-dev/math#2544). The benchmark to compare against at this time is multivariate_normal_cholesky.
Steps to bench:
- Clone stan-math.
- Setup Google Benchmark
cd lib/benchmark_1.5.1
mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=RELEASE
make
cd ../../..- Run the develop branch benchmark
git checkout develop
./benchmarks/benchmark.py "multi_normal_cholesky_lpdf(vector, vector, matrix) => real" --skip_similar_signatures --csv benchmark_results.csvThe benchmark_results.csv contains the benchmarks.
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