Dataflow Computing for Engineering Fluid Simulations (DFC4EFS)

HPC使许多公司能够在基于CPU或GPU的大型节点集群上执行更复杂的流体模拟。这些模拟消耗大量电力，但对于设计更高效的产品是必需的。该项目将探索使用Maxeler Technologies及其数据流引擎开创的创新数据流计算范例，以显著提高CFD模拟的性能，同时提高整个模拟过程的能效。因此，主要目标是将工程CFD代码映射到Maxeler的Dataflow发动机上，并通过典型叶轮机械测试案例的运行来演示模拟能耗的改进，同时提供计算性能的阶跃变化。该项目的创新方面是(1)使用用于CFD的数据流计算编程范例；(2)在工业强度工程模拟应用中部署数据流引擎。

HPC has given many companies the ability to perform more complex fluid simulation on large clusters of CPU or GPU based nodes. These simulations consume large amounts of power, but are required for engineering more efficient products. This project will explore the use of the innovative Dataflow Computing paradigm, pioneered by Maxeler Technologies with their Dataflow Engines, to significantly increase the performance of CFD simulation, while improving on the energy efficiency of the whole simulation process. The main objective is therefore to map an engineering CFD code onto Maxeler's Dataflow Engines and demonstrate through the running of typical turbomachinery testcases the improvements in energy consumption of the simulation while affording a step-change in computational performance. The innovative aspects of the project are (1) the use of Dataflow computing programming paradigm for CFD; (2) the deployment of Dataflow Engines in an industrial strength engineering simulation application.