In this article, we’ll explore how to benchmark the compilation speeds of various programming languages and their associated compilers. Understanding the differences in speed among compilers can help developers choose the right tools for their programming tasks, optimizing performance and efficiency.

Supported Languages and Compilers

This benchmarking tool supports a variety of languages and compilers:

Languages with Native Compilers:

• C (Compilers: gcc, clang, cproc, Cuik, tcc)
• C++ (Compilers: g++, clang++)
• D (Compilers: dmd, ldmd2, gdc)
• Go (Compilers: go, gccgo)
• Swift (Compiler: swiftc)
• Rust (Compiler: rustc)
• Nim (Compiler: nim)
• Julia (Compiler: julia)
• Ada (Compiler: gnat)
• Zig (Compiler: zig)
• V (Compiler: v)
• Vox (Compiler: vox)
• C3 (Compiler: c3c)
• Pareas (Compiler: pareas)

Languages with Bytecode Compilers:

• OCaml (Compiler: ocamlopt)
• C# (Compiler: mcs)
• Java (Compiler: javac)

Installation on Ubuntu

A subset of these compilers can be installed on Ubuntu by executing the script install-compilers-on-ubuntu-20.04.sh. For Python packages, use install-python-packages.sh.

How It Works

The benchmark process is akin to a marathon race where the speed and stamina of various runners (i.e., compilers) are tested under equal conditions. For instance, you can benchmark using:

.benchmark --function-count=$FUNCTION_COUNT --function-depth=$FUNCTION_DEPTH --run-count=5

Here, $FUNCTION_COUNT and $FUNCTION_DEPTH are parameters that can be adjusted based on your testing needs.

Alternatively, you can use default values by simply running:

.benchmark

Generating Code for Benchmarking

For example, running:

.benchmark --function-count=3 --function-depth=2 --run-count=5

Will generate a code file called generated/c/main.c which contains functions for the benchmark. The generated code tests how well each compiler can process different functions, similar to a cooking competition where chefs tackle the same dish with different ingredients.

Interpreting the Results

The results of the benchmark are displayed in a Markdown-formatted table, detailing parameters like compilation time, execution time, and memory usage for each language and compiler combination. Each result provides insight into the capabilities of the compilers, helping developers make informed decisions.

Troubleshooting Tips

If you encounter any issues while setting up or running your benchmarks, consider the following troubleshooting ideas:

• Ensure all required compilers and dependencies are properly installed.
• Run the benchmark command in the terminal with the correct permissions.
• Validate your system environment and compatibility with the chosen languages.

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Conclusion

This benchmark provides valuable insights into the performance of various programming languages and compilers. The Tiny C Compiler (TCC) emerged as one of the fastest due to its efficient single-pass code generation. Meanwhile, others like GCC and Clang showed varying performance with each new release.

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.