Abstracting the hardware: Assembly algorithms for numerical weather prediction on emerging massively parallel architectures

天气预报和气候模拟都建立在求解描述大气中流动的称为偏微分方程组或PDE的大型方程组的基础上。到目前为止，解决PDE的软件，包括现有的Met Office统一模型，一直是由必须是他们建模的科学和编程方面的专家的人为特定类型的硬件编写的。然而，现在计算机硬件正在发生巨大而迅速的变化。图形处理单元(GPU)和多核CPU系统等新的大规模并行平台的出现要求对低级编程采用非常不同的方法，更重要的是，需要针对不同的硬件平台采用不同的方法。它还需要对这些平台的最佳优化策略进行新的研究。目前编写科学软件的方法不会在现有的工业和政府资金资源范围内提供所需的变化，也不会跟上不断变化的硬件平台。该项目将通过使用一种新的方法来测试统一模型核心的现有和候选新的离散化，该方法将数值计算的各个工作项的规范与这些工作项如何在并行计算机上分配分开。这将使人们能够决定应该如何编写新的模型。特别是，它将使我们能够区分那些在高并行度下不能很好地工作的算法和那些需要以不同的方式实现才能在非常并行的环境中工作的算法。它还将使相同的算法能够在不同平台的不同实现中进行测试，以建立算法、实现和平台的最佳组合。通过这种方式，它还将为新的统一模型提供一些面向未来的支持，因为可以进行低级更改以反映新类型的并行硬件，而无需为每个新的计算机平台重写整个模型。

Weather forecasting and climate simulation are both founded on solving large systems of equations, called partial differential equations or PDEs which describe the flows in the atmosphere. Hitherto, the software which solves PDEs, including the existing Met Office Unified Model, has been written for specific sorts of hardware by people who had to be experts both in the science they were modelling and in programming. However, large and rapid changes are now occurring in computer hardware. The emergence of new massively parallel platforms, such as graphical processing units (GPUs) and multicore CPU systems is requiring very different approaches to low-level programming and, importantly, different approaches for different hardware platforms. It also requires new research into the best optimisation strategies for these platforms. The current approach to writing scientific software will not deliver the changes that are required within the industrial and government funding resources available nor will it keep up with changing hardware platforms. This project will test the existing and candidate new discretisations for the Unified Model core by using a new approach which separates the specification of individual work items of numerical computation from how those work items are shared out over a parallel computer. This will enable decisions about how a new model should be written. In particular, it will enable us to distinguish between those algorithms which just don't work very well at high levels of parallelism and those which need to be implemented differently to work in very parallel contexts. It will also enable the same algorithm to be tested in different implementations for different platforms to establish the best combinations of algorithm, implementation and platform. In this way it will also provide some future-proofing to a new Unified Model as low-level changes to reflect new types of parallel hardware will be possible without rewriting the whole model for each new computer platform.