Performance Test: Language Reactor

This repository contains implementations of the is_prime function in multiple programming languages using the same algorithm. The goal is to compare the performance of different languages and runtimes in a standardized environment.

🚀 New Features

⚡ Real-time Cloud Benchmarking - Run actual benchmarks on the server with live output streaming via Server-Sent Events (SSE).

💬 Persistent Community Feedback - Integrated with Turso (LibSQL) to store comments permanently in the cloud, even on serverless platforms.

🛡️ Robust & Secure - Custom Content Security Policy (CSP), high-performance rate limiting, and an extensive profanity filtering system.

🤖 Automated Deployment - Fully containerized with Docker and automated via GitHub Actions for continuous deployment to Google Cloud Run.

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Quick Start

1. Static Mode (Frontend Only)

Open docs/index.html in a browser to view pre-calculated results and run JavaScript-based browser benchmarks.

2. Full-Stack Mode (Local Development)

1. Install dependencies:

   npm install

2. Start the server:

   npm start

3. Open browser: http://localhost:3000

3. Cloud Deployment

The project is optimized for the Google Cloud "Always Free" tier.

• See docs/meta/GCP_DEPLOYMENT.md for step-by-step instructions on deploying with Turso and GitHub Actions.

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Project Structure

• docs/: Frontend web dashboard and deployment documentation.
• server/: Node.js backend logic, API, and database drivers.
• scripts/: High-performance execution scripts for the benchmark engine.
• src/benchmarks/: Core prime-number algorithm implementations for all 16+ languages.
• result/: Repository of historical benchmark data across different CPUs.

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Supported Languages

The benchmark environment (Docker) supports:

• Compiled/Native: Assembly (NASM), C (GCC), C++ (G++), Rust, Go, Zig, Fortran, Nim, Haskell, Pascal (FPC).
• Managed/JIT: Java (OpenJDK), Node.js, C# (Mono), Dart, Julia.
• Interpreted: Python, PHP, Ruby, R.
• Specialized: Codon (High-performance Python compiler).

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Usage (CLI)

Linux/macOS

./scripts/run.sh [LANGUAGE]

Windows (PowerShell)

.\scripts\run.ps1 [LANGUAGE]

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Results: Intel(R) Core(TM) i7-8550U

Ranking	Language	Runtime/Compiler	Time	n% Slower
#1	Assembly	NASM	3.10s	Winner
#2	C	GCC	3.12s	0.64%
#3	C++	G++	3.15s	1.6%
#4	Zig	Zig 0.11.0	3.16s	1.9%
#5	Fortran	GFortran 13.1	3.18s	2.6%
#6	Go	Go	3.81s	22%
#7	Julia	Julia	3.87s	24%
#8	Rust	Rustc (O3)	3.97s	28%
#9	Nim	Nim	4.05s	30%
#10	Haskell	GHC (O3)	4.20s	35%
#11	C#	Mono	5.32s	71%
#12	Java	OpenJDK 17	5.73s	84%
#13	Js	Nodejs 20	5.80s	87%
#14	Dart	Dart	7.11s	129%
#15	Python	Codon	10.89s	251%
#16	Pascal	FPC	13.68s	341%
#17	PHP	PHP	26.32s	749%
#18	Python	Python 3	82.31s	2545%
#19	Ruby	Ruby	85.55s	2641%
#20	R	Rscript	240.0s	7641%

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Contribute

1. Optimize your favorite language without changing the algorithm or using concurrency.
2. Add a new language implementation using the same prime-number logic.
3. Share your hardware results by submitting a PR to the result/ directory.

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Modernization Credits

The project was recently restructured and modernized. For a full log of changes, see docs/meta/IMPLEMENTATION_SUMMARY.md.