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🚀 Performance Benchmarking Suite

This project compares the execution speed of a simple computational task across different programming languages.

Inspired by Ben Dicken's loop performance comparison and his excellent visual analysis.

🎯 The Task

Each benchmark performs the same computation:

  • Creates an array of 10,000 elements
  • Runs nested loops to perform arithmetic operations
  • Measures and reports execution time

🔧 Supported Languages

  • Python 🐍 (using PyPy)
  • JavaScript 🟨
  • Go 🦫
  • C 🎯
  • Rust 🦀

📋 Prerequisites

Make sure you have the following installed:

  • PyPy
  • Node.js
  • Go
  • GCC (GNU Compiler Collection)
  • Rust

🏃‍♂️ Running the Benchmarks

Simply execute the benchmark script:

./run_benchmarks.sh

My Results

My machine:

  Chip: Apple M3 Pro
  Total Number of Cores: 11 (5 performance and 6 efficiency)
  Memory: 18 GB
Running benchmarks with hyperfine...
-----------------------------------
Benchmark 1: node src/loop_benchmark.js
  Time (mean ± σ):     764.0 ms ±  24.4 ms    [User: 751.3 ms, System: 7.6 ms]
  Range (min … max):   744.8 ms … 815.3 ms    10 runs

Benchmark 2: pypy src/loop_benchmark.py
  Time (mean ± σ):      1.035 s ±  0.014 s    [User: 1.022 s, System: 0.010 s]
  Range (min … max):    1.025 s …  1.061 s    10 runs

Benchmark 3: ./build/loop_benchmark_go
  Time (mean ± σ):     292.8 ms ±  36.6 ms    [User: 289.7 ms, System: 1.8 ms]
  Range (min … max):   268.4 ms … 387.1 ms    10 runs

Benchmark 4: ./build/loop_benchmark_c
  Time (mean ± σ):       1.8 ms ±   0.5 ms    [User: 0.4 ms, System: 0.7 ms]
  Range (min … max):     1.3 ms …   2.5 ms    10 runs

Benchmark 5: ./build/loop_benchmark_rust
  Time (mean ± σ):       1.9 ms ±   0.5 ms    [User: 0.7 ms, System: 0.7 ms]
  Range (min … max):     1.3 ms …   2.8 ms    10 runs

Summary
  ./build/loop_benchmark_c ran
    1.08 ± 0.42 times faster than ./build/loop_benchmark_rust
  162.60 ± 47.66 times faster than ./build/loop_benchmark_go
  424.30 ± 113.33 times faster than node src/loop_benchmark.js
  574.87 ± 152.64 times faster than pypy src/loop_benchmark.py

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