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EN FR
CAMUS - 2018


Section: New Results

A language extension set to generate adaptive versions automatically

Participants : Maxime Schmitt, Cédric Bastoul.

A large part of the development effort of compute-intensive applications is devoted to optimization, i.e., achieving the computation within a finite budget of time, space or energy. Given the complexity of modern architectures, writing simulation applications is often a two-step workflow. Firstly, developers design a sequential program for algorithmic tuning and debugging purposes. Secondly, experts optimize and exploit possible approximations of the original program to scale to the actual problem size. This second step is a tedious, time-consuming and error-prone task. During this year, we investigated language extensions and compiler tools to achieve that task semi-automatically in the context of approximate computing. We identified the semantic and syntactic information necessary for a compiler to automatically handle approximation and adaptive techniques for a particular class of programs. We proposed a set of language extensions generic enough to provide the compiler with the useful semantic information when approximation is beneficial. We implemented the compiler infrastructure to exploit these extensions and to automatically generate the adaptively approximated version of a program. We conducted an experimental study of the impact and expressiveness of our language extension set on various applications.

These language extensions and the underlying compiler infrastructure are a significant output of collaboration with Inria Nancy - Grand Est team TONUS, specialized on applied mathematics (contact: Philippe Helluy), to bring models and techniques from this field to compilers. A paper presenting these extensions has been accepted to the OGST journal, targeting typical end-users.