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Scalable self-improvement for compiler optimization

Most systems we regularly interact with, such as computer operating systems, are faced with the challenge of providing good performance, while managing limited resources like computational time and memory. Since it is challenging to optimally manage these resources, there is increasing interest in the use of machine learning (ML) to make this decision-making data driven rather than heuristic. In compiler optimization, inlining is the process of replacing a call to a function in a program with th...

Read more at research.google

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