Software Autotuning for Sustainable Performance Portability

Scientific software applications are increasingly developed by large interdiscplinary teams operating on functional modules organized around a common software framework, which is ca-pable of integrating new functional capabilities without modifying the core of the framework. In such environment, software correctness and modularity take precedence at the expense of code performance, which is an important concern during execution on supercomputing facil-ities, where the allocation of core-hours is a valuable resource. To alleviate the performance problems, we propose automated performance tuning (autotuning) of software to extract the maximum performance on a given hardware platform and to enable performance portability across heterogeneous hardware platforms. The resulting code remains generic without commit-ting to a particular software stack and yet is compile-time specializable for maximal sustained performance.