EPSRC Centre for Doctoral Training in Next Generation Computational Modelling

现代研究的成果及其从理论到应用的快速发展越来越多地得到计算的支持。计算方法经常被誉为科学的新第三支柱--除了经验和理论工作。虽然它的广度使计算几乎像数学一样无处不在，成为科学和工程中的关键工具，但它是一门年轻得多的学科，将极大地受益于能力的建设和朝着一体化、标准化和专业化方向的努力。计算新思想和技术的发展极其迅速，这些突破带来的进步是巨大的，它们对社会的影响是巨大的：没有计算机模拟，就不可能开发从空中客车380、核磁共振扫描到智能手机CPU的现代技术；从气候变化到天文学的重大科学问题的进展是由计算模型的结果推动的；重大投资决策是由计算模型支撑的。此外，在生物医学和金融等经历数据革命的领域中，模拟建模正在成为一个关键工具。这一进步是通过计算能力的快速增加而实现的，并且过去是基于处理器中计算指令的执行速度的提高。然而，这个时钟频率不能进一步提高，在最近的计算架构(如GPU、Intel Phi)中，现在通过在同一单元中拥有数百个计算核心(数量级)来提供额外的计算能力。这带来了新的数量级性能改进的潜力，但需要额外的并行编程和计算方法方面的专业培训，以便能够利用和利用这种机会。计算方面的进步是由新的硬件、算法、数值方法和模拟技术的创新以及科学计算建模中最佳实践的应用所推动的。通过结合、链接和同时利用硬件、软件、方法和技能方面的步骤变化，可以获得最有效的进展和最大的影响。然而，良好的计算科学培训是稀缺的，特别是在研究生水平。下一代计算建模博士培训中心将培养55名以上的研究生来解决这一技能差距。作为未来的计算建模领导者，他们将形成一个跨越学科界限的计算模型师社区的核心，不断致力于将最新的计算进展转移到相关领域。通过处理来自计算工程、先进材料、自主系统和健康等领域的尖端研究，同时交流他们的进步并与世界领先的学术和工业计算模型师团队合作，学生们将为在未来几十年推动先进计算做好完美的准备。

The achievements of modern research and their rapid progress from theory to application are increasingly underpinned by computation. Computational approaches are often hailed as a new third pillar of science - in addition to empirical and theoretical work. While its breadth makes computation almost as ubiquitous as mathematics as a key tool in science and engineering, it is a much younger discipline and stands to benefit enormously from building increased capacity and increased efforts towards integration, standardization, and professionalism.The development of new ideas and techniques in computing is extremely rapid, the progress enabled by these breakthroughs is enormous, and their impact on society is substantial: modern technologies ranging from the Airbus 380, MRI scans and smartphone CPUs could not have been developed without computer simulation; progress on major scientific questions from climate change to astronomy are driven by the results from computational models; major investment decisions are underwritten by computational modelling. Furthermore, simulation modelling is emerging as a key tool within domains experiencing a data revolution such as biomedicine and finance.This progress has been enabled through the rapid increase of computational power, and was based in the past on an increased rate at which computing instructions in the processor can be carried out. However, this clock rate cannot be increased much further and in recent computational architectures (such as GPU, Intel Phi) additional computational power is now provided through having (of the order of) hundreds of computational cores in the same unit. This opens up potential for new order of magnitude performance improvements but requires additional specialist training in parallel programming and computational methods to be able to tap into and exploit this opportunity.Computational advances are enabled by new hardware, and innovations in algorithms, numerical methods and simulation techniques, and application of best practice in scientific computational modelling. The most effective progress and highest impact can be obtained by combining, linking and simultaneously exploiting step changes in hardware, software, methods and skills. However, good computational science training is scarce, especially at post-graduate level.The Centre for Doctoral Training in Next Generation Computational Modelling will develop 55+ graduate students to address this skills gap. Trained as future leaders in Computational Modelling, they will form the core of a community of computational modellers crossing disciplinary boundaries, constantly working to transfer the latest computational advances to related fields. By tackling cutting-edge research from fields such as Computational Engineering, Advanced Materials, Autonomous Systems and Health, whilst communicating their advances and working together with a world-leading group of academic and industrial computational modellers, the students will be perfectly equipped to drive advanced computing over the coming decades.