Parallel Paradigms for Numerical Weather Prediction

天气预报和气候模拟需要专用的高性能超级计算机来运行。超级计算机能力的进步带来了以更高的分辨率(即更详细)模拟大气的可能性，而不必等待更长时间的答案。一直以来，大气模式的分辨率越高，天气预报和气候模拟就越准确。然而，获得能够充分利用最先进的超级计算机的模型是非常具有挑战性的。英国气象局正在安装一台新的克雷XC40超级计算机，该计算机将通过使用4800000个单独的处理器同时(并行)计算来提供16千万亿次(每秒16万亿次算术运算)的峰值处理能力。在接下来的几十年里，预计超级计算机将通过使用越来越多的处理器来提供越来越强的计算能力。在这些大规模并行的超级计算机上，减慢计算速度的主要原因是处理器之间的数据通信。不幸的是，大气物理意味着一个地方的天气与地球上所有其他地方的天气本质上是联系在一起的；这意味着处理器之间需要大量的数据通信。开发大气模型的科学家们目前正在努力解决这样一个事实，即我们在分辨率和模拟速度方面接近可能的极限，因为用于求解预测天气如何随时间演变的方程的数学算法的通信要求。目前，这些算法使用的是地理上的并行性：地球被分成几个重叠的部分，每个部分都被分配给不同的处理器，处理器必须将数据传递给共享重叠区域上地理位置的处理器。为了提高模型的速度，我们需要在越来越小的区域上使用越来越多的处理器。当有如此多的重叠区域，以至于整个地球都被重叠覆盖时，这种加速最终是有限的，并且模型花费了所有的时间通信。这意味着，是时候发明能够更好地利用并行计算机的新的数学算法了。在这个项目中，我们将开发时间并行和地理并行的算法。这些方法不是一步一步地向前推进模式的预报，而是在下一步产生几种不同的天气估计，然后将它们结合在一起，做出更准确的解决方案。这些不同的估算中的每一个都可以独立计算，这在模型中引入了额外的并行计算。该项目与英国气象局密切合作。如果成功，这些算法将导致气象局更快、更高分辨率的天气预报和气候预报模式，为政府、行业和普通公众带来更准确的预报。英国气象局为整个运输部门的客户提供预报，特别是航空规划(以便飞机可以避开逆风并利用顺风)和对火山灰云运动的预报。它还为零售和休闲、保险公司、国防部和环境局(包括洪水预报)提供预报。更准确的预测将使所有这些商业组织能够进一步规划未来，避免风险和不必要的成本。

Weather forecasts and climate simulations require dedicated highperformance supercomputers to run. Advances in the power ofsupercomputers bring the possibility of simulating the atmosphere athigher resolution (i.e. with more detail) without having to waitlonger for the answer. It has been consistently shown that increasingthe resolution of atmosphere models results in more accurate weatherforecasts and climate simulations. However, getting models that canmake full use of state-of-the-art supercomputers is very challenging.The Met Office is in the process of installing a new Cray XC40supercomputer which which will deliver 16 petaflops (16 quadrillionarithmetic operations per second)peak processingpower by using 4800000 individual processors computingtogether at the same time (in parallel). In the next few decadessupercomputers are expected to deliver more and more computing power, by using more and more processors. The main thing that slows downcomputations on these massively parallel supercomputers iscommunicating data between processors. Unfortunately, the physics of theatmosphere means that the weather in one location is intrinsicallylinked with the weather at all other locations on the globe; thismeans that a lot of data communication between processors is required.Scientists who develop atmosphere models are currently grappling withthe fact that we are close to the limit of what is possible in termsof resolution and simulation speed, due to the communicationrequirements of the mathematical algorithms that are used to solve theequations that predict how the weather evolves in time. At the moment,these algorithms use geographic parallelism: the globe is divided upinto overlapping pieces and each piece is given to a differentprocessor, which must communicate data to processors that sharegeographic locations on the overlaps. To speed up a model, we need touse more and more processors on smaller and smaller regions. Thespeed-up is eventually limited when there are so many overlapping regionsthat all of the globe iscovered by overlaps, and the model spends all of the timecommunicating.This means that it is time to invent new mathematical algorithms thatcan make better use of the parallel computer. In this project we will developalgorithms that are time-parallel as well asgeographic-parallel. Instead of advancing the forecast of the modelforwards step by step in time, these methods produce several differentestimates of the weather at the next step, before combining themtogether to make a more accurate solution. Each of these differentestimates can be independently calculated, which introduces additionalparallel computation into the model.This project is in close partnership with the Met Office. Ifsuccessful, these algorithms will lead to faster and higher resolutionweather forecast and climate prediction models at the Met Office,leading to more accurate forecasts for government, industry and thegeneral public. The Met Office provides forecasts for customers acrossthe transport sector, particularly for aviation planning (so thataeroplanes can avoid headwinds and make use of tailwinds) andpredictions of the motion of volcanic ash clouds. It also providesforecasts for retail and leisure, insurers, the Ministry of Defence, and theEnvironment Agency (including flood forecasting). More accurateforecasts will allow all of these business organisations to plan furtherinto the future, avoiding risks and unnecessary costs.