Speeding up the Rust compiler without changing its code (2022)
Efforts to enhance the Rust compiler's performance include expanding PGO profiling, updating LLVM, and refining benchmarks. Challenges on macOS hinder progress, but improvements in profiling precision show potential for optimization.
Read original article
The blog post discusses efforts to enhance the performance of the Rust compiler (rustc) without altering its source code. The author, a contributor to the rustc performance working group, outlines various strategies implemented over several months to optimize the compilation process. Key improvements include expanding Profile-Guided Optimization (PGO) profiling for LLVM, updating LLVM versions, and refining the PGO benchmark suite. The author highlights the importance of gathering accurate PGO profiles to optimize both LLVM and rustc effectively. Additionally, attempts were made to apply PGO on macOS, although challenges with CI build times hindered progress. The post also details improvements in precision for PGO profiling and the exploration of Call-Site aware PGO, which, despite mixed results, indicates potential for future optimization. The author emphasizes the significance of using modern benchmarks and adapting the PGO process to include a wider range of crates, ultimately leading to performance gains. The ongoing work aims to ensure that rustc remains efficient and competitive in the landscape of programming languages.
- The Rust compiler's performance is being improved through various optimization techniques without changing its source code.
- Key strategies include expanding PGO profiling, updating LLVM versions, and refining benchmark suites.
- Challenges with CI build times on macOS have limited the application of PGO on that platform.
- Improvements in profiling precision have led to better optimization outcomes.
- The ongoing efforts focus on adapting to modern benchmarks and enhancing the efficiency of rustc.
Related
Rustgo: Calling Rust from Go with near-zero overhead
An experiment explores calling Rust code from Go to enhance performance in critical applications. It proposes linking Rust directly into Go, avoiding cgo overhead, and details calling conventions for efficient integration.
Clang vs. Clang
The blog post critiques compiler optimizations in Clang, arguing they often introduce bugs and security vulnerabilities, diminish performance gains, and create timing channels, urging a reevaluation of current practices.
Language Compilation Speed (2021)
The article examines Rust's compilation speed compared to C/C++, noting frustrations among developers. It proposes a benchmarking method, revealing GCC compiles at 5,000 lines per second and Clang at 4,600.
Doctests – How were they improved?
Rust's documentation generator, rustdoc, has improved doctest efficiency by merging compatible tests, significantly reducing compilation times and enhancing error handling, with future updates expected for binary crate functionality.
Should you use Rust in LLM based tools for performance?
The article highlights the advantages of using Rust for text processing software, showing its superior performance over Python's Langchain, particularly in indexing and querying for LLM tools.
3 commentsIt is clickbait, what was actually changed?
Related
Rustgo: Calling Rust from Go with near-zero overhead
An experiment explores calling Rust code from Go to enhance performance in critical applications. It proposes linking Rust directly into Go, avoiding cgo overhead, and details calling conventions for efficient integration.
Clang vs. Clang
The blog post critiques compiler optimizations in Clang, arguing they often introduce bugs and security vulnerabilities, diminish performance gains, and create timing channels, urging a reevaluation of current practices.
Language Compilation Speed (2021)
The article examines Rust's compilation speed compared to C/C++, noting frustrations among developers. It proposes a benchmarking method, revealing GCC compiles at 5,000 lines per second and Clang at 4,600.
Doctests – How were they improved?
Rust's documentation generator, rustdoc, has improved doctest efficiency by merging compatible tests, significantly reducing compilation times and enhancing error handling, with future updates expected for binary crate functionality.
Should you use Rust in LLM based tools for performance?
The article highlights the advantages of using Rust for text processing software, showing its superior performance over Python's Langchain, particularly in indexing and querying for LLM tools.