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Terry CojeanThomas Grützmacher
Terry Cojean
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Thomas Grützmacher
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Review update: review style of Benchmarking.md
Co-authored-by: Thomas Grützmacher <[email protected]>
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BENCHMARKING.md

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@@ -17,7 +17,11 @@ utility](https://github.com/ginkgo-project/ssget) has to be installed on the
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system. The purpose of this file is to explain in detail the capacities of this
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benchmarking suite as well as how to properly setup everything.
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There are two ways to benchmark `ginkgo`. When compiling the benchmark suite, executables are generated for collecting matrix statistics, running sparse-matrix vector product, solvers (possibly distributed) benchmarks. Another way to run benchmarks is through the convenience script `run_all_benchmarks.sh`, but not all features are exposed through this tool!
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There are two ways to benchmark Ginkgo. When compiling the benchmark suite,
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executables are generated for collecting matrix statistics, running
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sparse-matrix vector product, solvers (possibly distributed) benchmarks. Another
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way to run benchmarks is through the convenience script `run_all_benchmarks.sh`,
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but not all features are exposed through this tool!
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Here is a short description of the content of this file:
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1. Ginkgo setup and best practice guidelines
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```
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### 3: Running benchmarks manually
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When compiling `ginkgo` with the flag `-DGINKGO_BUILD_BENCHMARKS=on`, a suite of
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executables will be generated depending on the `CMake` configuration. These
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When compiling Ginkgo with the flag `-DGINKGO_BUILD_BENCHMARKS=ON`, a suite of
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executables will be generated depending on the CMake configuration. These
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executables are the backbone of the benchmarking suite. Note that all of these
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executables describe the available options and the required input format when
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running them with the `--help` option. All executables have multiple variants
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```
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The files have to be in matrix market format.
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Some benchmarks require some extra fields. For example the solver benchmarks requires the field `"optimal": {"spmv": "matrix format (such as csr)"}`. This is automatically populated when running the `spmv` benchmark which finds the optimal (fastest) format among all requested formats.
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Some benchmarks require some extra fields. For example the solver benchmarks
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requires the field `"optimal": {"spmv": "matrix format (such as csr)"}`. This is
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automatically populated when running the `spmv` benchmark which finds the
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optimal (fastest) format among all requested formats.
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After writing the necessary data in a JSON file, the benchmark can be called by
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passing in the input via stdin, i.e.
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./solver < input.json
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```
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The output of our benchmarks is again JSON, and it is printed to stdout, while our status messages are printed to stderr. So, the output can be stored with
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The output of our benchmarks is again JSON, and it is printed to stdout, while
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our status messages are printed to stderr. So, the output can be stored with
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```
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./solver < input.json > output.json
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to analyze Ginkgo's performance.
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These features are implemented thanks to the loggers located in the file
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`${ginkgo_src_dir}/benchmark/utils/loggers.hpp`. Ginkgo possesses hooks at all important code
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location points which can be inspected thanks to the logger. In this fashion, it
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is easy to use these loggers also for tracking memory allocation sizes and other
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important library aspects.
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`${ginkgo_src_dir}/benchmark/utils/loggers.hpp`. Ginkgo possesses hooks at all
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important code location points which can be inspected thanks to the logger. In
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this fashion, it is easy to use these loggers also for tracking memory
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allocation sizes and other important library aspects.
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### 7: Available benchmark options
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