The Impact of Parallel Programming Interfaces on the Aging of a Multicore Embedded Processor

Abstract

In order to meet the increasing performance demand of applications, the amount of cores in a single chip package has been increasing. However, the heat has been rising at a higher scale, which accelerates the aging process in modern processors. Therefore, wisely balancing the use of resources is important to extend its longevity. Frequency performance stagnates after a certain amount of concurrent threads starts executing. In such cases, the only result is a temperature rise that directly influences the aging process, reducing the processor lifetime. This unbalance between threads can be originated from many factors, which includes the way threads communicate and synchronize. Considering that those characteristics are related to the Parallel Programming Interface (PPI) used to parallelize the application, this work proposes to evaluate three widely used PPIs executing on an embedded multicore. We show that, depending on the characteristic of the application, by only switching from one PPI to another, it is possible to reduce the effects of aging. For that, we have developed a model based on the Arrhenius equation. We show that OpenMP has a lower impact on the processor aging for memory-bound applications: up to 38% and 68% lower than PThreads and MPI, respectively. On the other hand, PThreads presents the lowest impact on the processor aging for CPU-bound applications.

Experiences on the characterization of parallel applications in embedded systems with Extrae/Paraver

“…This promotes the evolution of embedded software stacks from simple micro-controllers, where sequential execution is predominant, to complex parallel frameworks, where parallel programming models are key to fully exploit the performance capabilities of parallel architectures. In this context, fine-grained models such as OpenMP or Pthreads [27,35,41] are already being considered as appropriate solutions to leverage the potential of the newest embedded systems. Particularly, OpenMP has been shown to provide time predictability [30,31] and correctness [26] capabilities at parallel programming model level.…”