RSE training in algorithms for exascale simulations

百亿亿次模拟算法的 RSE 培训

• 批准号: EP/W035782/1
• 负责人: Jemma Shipton
• 金额: $ 4.47万
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FW035782%2F1
• 关键词: RSE; training; algorithms; exascale; simulations

The exascale computing landscape in the UK is at an exciting stage,with funding being allocated to novel architectures, new softwareframeworks and innovative algorithms. Through training RSEs we have anopportunity to embed the progress made in these areas into the core ofacademic research and industrial applications, positioning the UK asan international leader in exascale simulations. To grasp thisopportunity is essential that RSEs are trained in algorithms sothat they can take an active part in research in this area. In orderto make informed and creative design choices when writing andoptimising software, RSEs need to have core knowledge of algorithms sothat they can confidently innovate and avoid the common pitfalls thatacademics and industrial partners are already aware of through theirresearch and experience. If this core knowledge is not passed on toRSEs and shared throughout the RSE community, advances made throughthe ExCALIBUR programme research projects risk failing to achievecrucial impact in academic and industrial applications.As described in section 7.3 of the RSE Knowledge Integration LandscapeReview, it is crucial that RSEs have the potential to be activelyinvolved in research. This is one of the key attractions of the jobfor skilled postgraduate students and is essential for retainingskilled RSEs in the role. The Landscape Review acknowledges thatdesign of new algorithms is a research field in itself and requires`strong domain specific knowledge'. We propose to provide training inthis area, alongside opportunities for knowledge exchange andnetworking between academic researchers, postgraduate students, RSEsand industrial partners.We propose to run two three-day workshops and a Summer School toprovide training in state of the art algorithms and core knowledge ofthe underlying foundational mathematical and numerical analysis onwhich they are based. The materials developed in advance of, andduring, these events will be curated and shared online to either beused as stand alone material for individual training or to form thebasis of future summer schools.

英国的Exascale计算景观处于令人兴奋的阶段，资金分配给了新颖的架构，新的软件框架和创新算法。通过培训RSE，我们可以将这些领域取得的进展嵌入到核心研究和工业应用中，从而将英国Asan International Prinide嵌入了Exascale模拟中的核心。要掌握这种企业是至关重要的，必须对RSE进行训练，以示算法，他们可以积极参与该领域的研究。为了在编写和优化软件时做出明智的创意设计选择，RSE需要对算法具有核心知识，他们可以自信地创新，并避免通过他们的研究和经验来了解Academics和Industrial Partners的常见陷阱。如果该核心知识未传递到整个RSE社区中，则通过Excalibur计划研究项目的进步风险未能在学术和工业应用中实现影响。如RSE知识整合第7.3节所述，RSE的RSE具有至关重要的RSE具有在研究中的潜在研究至关重要的。这是熟练的研究生工作人员的关键景点之一，对于保留该职位的RSE至关重要。景观审查承认，新算法的设计本身就是一个研究领域，并且需要“特定领域的知识”。我们建议在这个领域提供培训，以及学术研究人员，研究生，RSES和工业合作伙伴之间的知识交流和网络的机会。我们建议在艺术算法和基于基于基础的基于基础的基础数学和数字分析的艺术算法和核心知识的三天工作室和一个暑期学校的Toprovide培训。这些事件将在并在线共享之前开发的材料，以将其作为单独培训的独立材料，或者形成未来暑期学校的基础。