Using Machine-Learning to Efficiently Explore the Architecture/Compiler Co-Design Space / Libristo.pl
Using Machine-Learning to Efficiently Explore the Architecture/Compiler Co-Design Space

Code: 05026509

Using Machine-Learning to Efficiently Explore the Architecture/Compiler Co-Design Space

by Christophe Dubach

Designing new microprocessors is a time consuming task. Architects rely on slow simulators to evaluate performance and a significant proportion of the design space has to be explored before an implementation is chosen. This proces ... more


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Book synopsis

Designing new microprocessors is a time consuming task. Architects rely on slow simulators to evaluate performance and a significant proportion of the design space has to be explored before an implementation is chosen. This process becomes more time consuming when compiler optimisations are also considered. Once the architecture is selected, a new compiler must be developed and tuned. What is needed are techniques that can speedup this whole process and develop a new optimising compiler automatically. This thesis proposes the use of machine-learning techniques to address architecture/compiler co-design.

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Book category Books in English Computing & information technology Computer programming / software development Extreme programming

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