Lesson plan
Automatic parallelization
Automatic parallelization, also auto-parallelization or autoparallelization, is a compiler optimization in which a compiler or other software tool transforms sequential program code so that some of its operations can execute in parallel. The generated program may use multiple processor cores or hardware threads, vector instructions, or other forms of parallel execution. Automatic parallelization attempts to reduce the amount of explicit parallel programming required of the programmer. To do so, a compiler must determine whether operations can execute concurrently without changing the behavior of the program and whether executing them in parallel is likely to improve performance. This involves analyses such as dependence analysis, alias analysis and data-flow analysis, together with program transformations that expose or increase usable parallelism. Loops have historically been an important target for automatic parallelization, particularly in numerical programs with regular array accesses. Automatic parallelization is therefore closely related to automatic vectorization, loop transformation, and other compiler techniques for exploiting parallel hardware.
Article summary
Automatic parallelization, also auto-parallelization or autoparallelization, is a compiler optimization in which a compiler or other software tool transforms sequential program code so that some of its operations can execute in parallel. The generated program may use multiple processor cores or hardware threads, vector instructions, or other forms of parallel execution. Automatic parallelization attempts to reduce the amount of explicit parallel programming required of the programmer. To do so, a compiler must determine whether operations can execute concurrently without changing the behavior of the program and whether executing them in parallel is likely to improve performance. This involves analyses such as dependence analysis, alias analysis and data-flow analysis, together with program transformations that expose or increase usable parallelism. Loops have historically been an important target for automatic parallelization, particularly in numerical programs with regular array accesses. Automatic parallelization is therefore closely related to automatic vectorization, loop transformation, and other compiler techniques for exploiting parallel hardware.
Key claims
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Discussion questions
- Summarise the article in your own words. Which single claim would you verify first, and why?
- Which claim in this article is most likely to be revised as the sources update? How would you check its current status?
- If two sources disagreed about one of these facts, what would you need in order to trust one over the other?
Bibliography
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Key claims and bibliography are generated from the same tracked claims and sources as the article page.