Summary The 3‐P challenge of high‐performance programming—performance, portability and productivity—has become more difficult than ever in the age of heterogeneous computing. It would be naïve to think that the performance portability problem can be completely solved, but it can certainly be reduced and made tolerable. However, first and foremost, an agreement is needed on what it means for an application to be performance portable. Unfortunately, there is still no consensus in the scientific community on a workable definition of the term performance portability. Several years ago, a comprehensive effort was made to formulate a novel definition of performance portability and an associated metric. Since the new metric was first introduced, it has been widely adopted by the scientific community, and many advanced studies have used it. Unfortunately, the definition of the new metric has flaws. This article presents a proof of the theoretical flaws in the definition of the new metric, considers the practical implications of these flaws as reflected in many studies that have used it in recent years, and proposes a revised metric that addresses the flaws and provides guidelines on how to use it correctly.

Parallelization lets applications exploit the high throughput of new multicore processors, and the OpenMP parallel programming model helps developers create multithreaded applications.

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