{"id":111450,"date":"2023-11-12T03:10:13","date_gmt":"2023-11-12T01:10:13","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/v-nochnyh-sborkah-rust-rasshireny-vozmozhnosti-rasparallelivaniya-kompilyaczii"},"modified":"2023-11-12T03:10:13","modified_gmt":"2023-11-12T01:10:13","slug":"v-nochnyh-sborkah-rust-rasshireny-vozmozhnosti-rasparallelivaniya-kompilyaczii","status":"publish","type":"post","link":"https:\/\/prohoster.info\/en\/blog\/news\/v-nochnyh-sborkah-rust-rasshireny-vozmozhnosti-rasparallelivaniya-kompilyaczii","title":{"rendered":"Nightly builds of Rust have expanded parallel compilation capabilities.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"
In the Rust compiler's frontend, which performs tasks like parsing, type checking, and borrow checking, support for parallel execution has been implemented, significantly reducing compilation time. Parallelization is already available in Rust nightly builds and can be enabled using the option \u2018-Z threads=8\u2019. This feature is planned to be included in the stable branch in 2024. <\/p>\n
Efforts to reduce compilation time in Rust have been underway for several years. In the first 10 months of 2023, the average compilation time was reduced by 13%, peak memory consumption decreased by 15%, and the size of generated files was cut by 7%. At this stage, acceleration was achieved through optimizations to the compiler itself. After this, developers shifted their focus to speeding up operations through parallelization during compilation. <\/p>\n
Until now, parallelization in Rust has primarily been achieved at the process level, for example, the package manager Cargo can run several rustc processes to compile multiple packages simultaneously. Support for parallelization is also present on the backend side, which handles operations related to code generation \u2014 the Rust backend can generate code in chunks that LLVM can process in parallel. However, the frontend could only handle source code in single-threaded mode until now. <\/p>\n
To support parallelization, the frontend has been transitioned to use the Rayon library and significantly revamped; for example, many of its components are now synchronized using mutexes and read\/write locks, and atomic types are employed in the code. In performance testing, the new parallelizable implementation was able to compile up to 2% slower when operating in single-threaded mode (-Z threads=1), but when more than one thread was used, the speed increased significantly. For instance, with 8 threads set (-Z threads=8), compilation time was successfully reduced by 50% in certain situations. <\/p>\n
However, the results depend heavily on the environment settings and the code being compiled \u2014 for very small programs, which compile quickly anyway, compiling in multi-threaded mode may actually be slower. Additionally, memory consumption in multi-threaded mode can increase significantly; for instance, tests have shown a memory consumption rise of up to 35%. \n Source: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"