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Notebook","funding_links":["https://github.com/sponsors/JuliaLang"],"categories":[],"sub_categories":[],"readme":"# Microbenchmarks\n\n[![Benchmarks](https://github.com/JuliaLang/Microbenchmarks/actions/workflows/benchmarks.yml/badge.svg)](https://github.com/JuliaLang/Microbenchmarks/actions/workflows/benchmarks.yml)\n\nA collection of micro-benchmarks comparing Julia's performance against other languages.\n\n**[View results](https://julialang.github.io/Microbenchmarks/dev/benchmarks)**\n\n## Benchmarks\n\nAll benchmarks implement identical algorithms across languages (serial, single-core).\nTimes are normalized relative to C.\n\n| Benchmark | Description |\n|:----------|:------------|\n| `iteration_pi_sum` | Alternating power-series summation (nested loops) |\n| `recursion_fibonacci` | Doubly-recursive Fibonacci(20) |\n| `recursion_quicksort` | Quicksort on 5,000 random numbers |\n| `parse_integers` | Parse 1,000 random hex strings to integers |\n| `print_to_file` | Write 100,000 formatted lines to /dev/null |\n| `matrix_statistics` | Statistics on random 5x5 matrices (1,000 iterations) |\n| `matrix_multiply` | Multiply two random 1,000x1,000 matrices (BLAS) |\n| `userfunc_mandelbrot` | Mandelbrot set computation over a grid |\n\n## Languages\n\n* [C](c/perf.c)\n* [Fortran](fortran/perf.f90)\n* [Go](go/perf.go)\n* [Java](java/src/main/java/PerfBLAS.java)\n* [JavaScript](javascript/perf.js)\n* [Julia](julia/perf.jl)\n* [LuaJIT](lua/perf.lua)\n* [Numba](numba/perf.py)\n* [Octave](octave/perf.m)\n* [Python](python/perf.py)\n* [R](r/perf.R)\n* [Rust](rust/src/main.rs)\n* [Scala](scala/src/main/scala/perf.scala)\n* [Swift](swift/Sources/perf/main.swift)\n\nMathematica and Matlab benchmarks are available but not run in CI.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjulialang%2Fmicrobenchmarks","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjulialang%2Fmicrobenchmarks","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjulialang%2Fmicrobenchmarks/lists"}