IIUC clang is expected to compile faster which I understand to be a time-saver when testing source packages or ebuilds.
However as far as robustness is concerned I'm far from switching
As far as performance is concerned I know there are packages which do perform much faster when build with clang.
Code: Select all
list of packages well known to be much faster when compiled with clang
ChatGPT said:
Here are several software packages that are known to perform significantly faster when compiled with Clang compared to other compilers like GCC or older versions of Clang. These improvements typically stem from Clang's optimizations, particularly with its aggressive vectorization and ability to make better use of CPU-specific features.
1. LLVM-based Projects (Naturally)
LLVM (the compiler infrastructure itself): Compiling LLVM with Clang often results in better performance because LLVM is designed with Clang as its primary compiler frontend.
Clang itself: When Clang is compiled using Clang, it typically benefits from Clang’s own optimizations and better handling of LLVM’s intermediate representation.
2. Rust
Rust (via rustc and LLVM): Rust's compiler (rustc) is heavily based on LLVM, and when Clang is used for Rust's back-end compilation, it can often outperform GCC in terms of both speed and optimized code.
3. WebAssembly Projects
Emscripten: Emscripten compiles C/C++ code to WebAssembly. Clang produces faster WebAssembly code in comparison to GCC due to its superior handling of modern C++ features and optimizations.
4. C++ Projects
Google Chrome (V8 engine): The V8 JavaScript engine performs better when compiled with Clang due to its optimization capabilities, especially with the modern C++ features it uses.
libc++ (C++ Standard Library): Clang's own implementation of the C++ standard library is known to offer better performance than GCC’s libstdc++ in some cases, particularly with newer C++ standards.
5. Game Engines
Unreal Engine: Unreal Engine tends to show performance gains when compiled with Clang, especially on platforms like macOS and iOS, where Clang is the default compiler. The optimizations Clang offers make Unreal Engine perform better in both resource usage and raw speed.
Unity: Unity also benefits from Clang optimizations when building for Apple platforms, improving performance in rendering and physics simulations.
6. OpenCL
AMD ROCm and Intel OpenCL: Many OpenCL codebases, especially those targeting GPUs, show performance improvements when compiled with Clang, particularly for platforms optimized for Clang’s LLVM backends (such as AMD and Intel's GPUs).
7. Database Engines
SQLite: Clang often outperforms GCC when compiling SQLite, especially in terms of code size and execution speed, due to Clang’s high-level optimizations and its support for advanced CPU features like AVX.
PostgreSQL: Compiling PostgreSQL with Clang can sometimes result in better performance, particularly with newer processor architectures and when using advanced vectorization.
8. Machine Learning Frameworks
TensorFlow: TensorFlow can experience faster compilation and better runtime performance when compiled with Clang, especially when targeting specific hardware features like AVX-512 or ARM-specific optimizations.
PyTorch: Like TensorFlow, PyTorch may benefit from Clang optimizations when compiled from source, especially for large-scale model training and inference on modern CPUs and GPUs.
9. Multithreading Libraries
Threading Building Blocks (TBB): Intel’s TBB is known to compile more efficiently and perform better when Clang is used, largely because of its LLVM-based optimization strategies.
OpenMP: While GCC supports OpenMP, Clang often delivers better performance in multi-threaded programs thanks to its more efficient handling of parallelism.
10. Graphics Libraries
Vulkan: Graphics code, particularly in Vulkan applications, can show performance gains with Clang because of how Clang optimizes for specific hardware and makes use of its highly efficient code generation techniques.
OpenGL: Clang’s optimizations allow it to generate faster code for OpenGL applications, especially for modern OpenGL features and shaders.
11. Zlib & Compression Libraries
Zlib: Compression algorithms like Zlib often run faster when compiled with Clang, due to its advanced optimization passes.
Brotli: Similar to Zlib, Brotli (a compression algorithm) shows performance improvements in both compression and decompression speeds when Clang is used for compilation.
12. Networking Libraries
nginx: Clang can sometimes generate faster code for server-side applications like nginx, particularly in areas such as memory management and HTTP protocol handling.
13. Scientific Computing Libraries
BLAS/LAPACK: For high-performance scientific computing, Clang has optimizations that improve both the speed and accuracy of linear algebra routines in libraries like BLAS (Basic Linear Algebra Subprograms) and LAPACK (Linear Algebra PACKage).
OpenBLAS: OpenBLAS compiled with Clang can outperform GCC in terms of floating-point operations and memory optimizations on certain hardware platforms.
14. Custom Performance-critical Applications
Custom C/C++ applications: Applications that make extensive use of SIMD (Single Instruction, Multiple Data) instructions, or rely on compiler-specific optimizations, may see significant performance boosts when compiled with Clang. This is especially true on modern x86 and ARM hardware that Clang optimizes for.
General Observations:
Apple Platforms: On macOS and iOS, Clang is the default compiler, and it is highly optimized for these platforms. Apps compiled with Clang often exhibit better performance due to the deep integration of Clang with Apple's hardware and software optimizations.
Modern CPUs: Clang tends to outperform GCC on modern CPUs (especially Intel and AMD chips) because of its sophisticated optimizations that are better tuned to these architectures.
Overall, Clang’s superior optimization strategies—especially those based on its LLVM back-end—often result in noticeable performance improvements across various types of software.Hopefully one day I will reconsider my POV, on a per package basis.
