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This paper explores parallelism performance for C, C++, Go, Java, Julia, and Rust on N-body simulations. We begin with a basic O( \(N^2\) ) simulation for each language based on the n-body benchmark in the Benchmark Game. The original benchmark is adjusted to include a larger number of particles and run in parallel. We also add parallelism to the force calculations using a kD-tree. This work builds on previous work by including parallelism and adding the Julia programming language to our survey. We find that for straight number-crunching, all of these languages provide similar performance, and all have sufficient support for parallelism that runtimes scale well with thread counts. On the other hand, when a spatial data structure, such as the kD-tree, is introduced, the runtimes vary dramatically between languages. In that situation, Julia’s performance looks more like Python, taking over 100 times as long as Rust/C/C++ to finish. Rust comes out on top with an impressive 50% lead over C and C++.

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Parallel N-Body Performance Comparison: Julia, Rust, and More

  • 会议论文

  • 发表日期：

    2025年

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  • Mark C. Lewis,
  • Clarissa Garcia,
  • Audrey Tollett,
  • Seven Aguirre,
  • Henry Hafner,
  • John McMahon,
  • Amanda A. Sickafoose

摘要

This paper explores parallelism performance for C, C++, Go, Java, Julia, and Rust on N-body simulations. We begin with a basic O( \(N^2\) ) simulation for each language based on the n-body benchmark in the Benchmark Game. The original benchmark is adjusted to include a larger number of particles and run in parallel. We also add parallelism to the force calculations using a kD-tree. This work builds on previous work by including parallelism and adding the Julia programming language to our survey. We find that for straight number-crunching, all of these languages provide similar performance, and all have sufficient support for parallelism that runtimes scale well with thread counts. On the other hand, when a spatial data structure, such as the kD-tree, is introduced, the runtimes vary dramatically between languages. In that situation, Julia’s performance looks more like Python, taking over 100 times as long as Rust/C/C++ to finish. Rust comes out on top with an impressive 50% lead over C and C++.