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Scientific software applications are increasingly developed by largeinterdiscplinary teams operating on functional modules organized around acommon software framework, which is capable of integrating new functionalcapabilities without modifying the core of the framework. In such environment,software correctness and modularity take precedence at the expense of codeperformance, which is an important concern during execution on supercomputingfacilities, where the allocation of core-hours is a valuable resource. Toalleviate the performance problems, we propose automated performance tuning(autotuning) of software to extract the maximum performance on a given hardwareplatform and to enable performance portability across heterogeneous hardwareplatforms. The resulting code remains generic without committing to aparticular software stack and yet is compile-time specializable for maximalsustained performance.

Software Autotuning for Sustainable Performance Portability