Delivering optimum performance on a parallel computer is highly dependant on the efficiency of the scheduling and mapping procedure. If the composition of the parallel application is known a prior, the mapping can be accomplished statically on the compilation time. The mapping algorithm uses the model of the parallel application and maps its tasks to processors in a way to minimize the total execution time. In this article, current modeling approaches have discussed. Later, a new modeling schema named Model of Exascale Message-Passing Programs on Heterogeneous Architectures (MEMPHA) has proposed. A comparative study has been performed between MEMPHA and existing models. To exhibit the efficiency of the MEMPHA, experiments have performed on a set of data-set hypergraphs. The results obtained from the experiments show that deploying the MEMPHA helps to optimize metrics, including the congestion, total communication volume and maximum volume of data being sent or received. These improvements vary from 76 to 1 percent, depending on the metric and benchmark model. Moreover, MEMPHA supports the modeling of applications with multiple producers for a single data transmission, where the rest of the approaches fail.

中文翻译：

---

MEMPHA：异构架构上的 Exascale 消息传递程序模型

在并行计算机上提供最佳性能高度依赖于调度和映射过程的效率。如果事先知道并行应用程序的组成，则可以在编译时静态完成映射。映射算法使用并行应用程序的模型并将其任务映射到处理器以最小化总执行时间。在本文中，讨论了当前的建模方法。后来，提出了一种名为 Model of Exascale Message-Passing Programs on Heterogeneous Architectures (MEMPHA) 的新建模模式。已经在 MEMPHA 和现有模型之间进行了比较研究。为了展示 MEMPHA 的效率，对一组数据集超图进行了实验。从实验中获得的结果表明，部署 MEMPHA 有助于优化指标，包括拥塞、总通信量和发送或接收的最大数据量。这些改进从 76% 到 1% 不等，具体取决于指标和基准模型。此外，MEMPHA 支持对具有多个生产者的应用程序进行建模以进行单个数据传输，而其余方法都失败了。