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nathanrboyergdalle
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Co-authored-by: Guillaume Dalle <[email protected]>
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optimizing/index.md

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@@ -57,9 +57,9 @@ The Chairmarks.jl package provides convenient syntax to do just that.
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### Chairmarks
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[Chairmarks.jl](https://github.com/LilithHafner/Chairmarks.jl) is the latest and greatest benchmarking suite used to make fast and accurate timing measurements.
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[Chairmarks.jl](https://github.com/LilithHafner/Chairmarks.jl) is the latest benchmarking toolkit, designed to make fast and accurate timing measurements.
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Chairmarks offers `@b` (for "benchmark") which can be used in the same way as `@time` but will run the code multiple times and provide a minimum execution time.
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Alternatively, Chairmarks also provides `@be` to run the benchmark and output all of its statistics.
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Alternatively, Chairmarks also provides `@be` to run the same benchmark and output all of its statistics.
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```>chairmarks-example
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using Chairmarks
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To find bottlenecks in a larger program, you should rather use a [profiler](#profiling) or the package [TimerOutputs.jl](https://github.com/KristofferC/TimerOutputs.jl).
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It allows you to label different sections of your code, then time them and display a table of grouped by label.
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[BenchmarkTools.jl](https://github.com/JuliaCI/BenchmarkTools.jl) was the previous standard for benchmarking in Julia. It is still widely used today.
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However, it is slower than Chairmarks and requires interpolating variables into the benchmarked expressions with `$`.
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[BenchmarkTools.jl](https://github.com/JuliaCI/BenchmarkTools.jl) is the older standard for benchmarking in Julia. It is still widely used today.
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However, its default parameters run benchmarks for longer than Chairmarks, and it requires interpolating variables into the benchmarked expressions with `$`.
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Finally, if you know a loop is slow and you'll need to wait for it to be done, you can use [ProgressMeter.jl](https://github.com/timholy/ProgressMeter.jl) or [ProgressLogging.jl](https://github.com/JuliaLogging/ProgressLogging.jl) to track its progress.
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