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{{Short description|Method of improving computer program speed}}
{{More citations needed|date=February 2008}}
{{Use dmy dates|date=January 2022}}
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The [[Scheduling (computing)|scheduler]] will list all the tasks and their dependencies on each other in terms of execution and start times. The scheduler will produce the optimal schedule in terms of number of processors to be used or the total execution time for the application.
===Code
The [[Scheduling (computing)|scheduler]] will generate a list of all the tasks and the details of the cores on which they will execute along with the time that they will execute for. The code Generator will insert special constructs in the code that will be read during execution by the scheduler. These constructs will instruct the scheduler on which core a particular task will execute along with the start and end times.
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Recently, Aubert, Rubiano, Rusch, and [[Thomas Seiller|Seiller]]<ref>{{cite book |last1=Aubert |first1=Clément |last2=Rubiano |first2=Thomas
|last3=Rusch |first3=Neea |last4=Seiller |first4=Thomas |chapter= Distributing and Parallelizing Non-canonical Loops |title= Verification, Model Checking, and Abstract Interpretation |series=Lecture Notes in Computer Science |date=2023 |volume=13881 |pages=91–108 |doi=10.1007/978-3-031-24950-1_1 |isbn=978-3-031-24949-5 }}</ref> used a dependency analysis technique <ref>{{cite book |last1=Moyen |first1=Jean-Yves |last2=Rubiano |first2=Thomas |last3=Seiller |first3=Thomas |chapter=Loop Quasi-Invariant Chunk Detection |title=Automated Technology for Verification and Analysis |series=Lecture Notes in Computer Science |date=2017 |volume=10482 |pages=91–108 |doi=10.1007/978-3-319-68167-2_7|isbn=978-3-319-68166-5 }}</ref> to automatically parallelise loops in [[C (programming language)|C]] code.
==See also==
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