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Peta-5: A National Facility for Petascale Data Intensive Computation and Analytics

Peta-5: A National Facility for Petascale Data Intensive Computation and Analytics
Peta-5:千万亿级数据密集型计算和分析的国家设施
批准号:
EP/P020259/1
负责人:
Paul Alexander
金额:
$637.13万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --

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中文摘要
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英文摘要
The Peta-5 proposal from the University of Cambridge brings together 15 world-leading HPC system and application experts from 10 different institutions to lead the creation of a breakthrough HPC and data analytics capability that will deliver significant National impact to the UK research, industry and health sectors.Peta-5 aims to make a significant contribution towards the establishment and sustainability of a new EPSRC Tier 2 HPC network. The Cambridge Tier 2 Centre working in collaboration with other Tier 1, Tier 2 and Tier 3 stakeholders aims to form a coherent, coordinated and productive National e-Infrastructure (Ne-I) ecosystem. This greatly strengthened computational research support capability will enable a significant increase in computational and data centric research outputs, driving growth in both academic research discovery and the wider UK knowledge economy. The Peta-5 system will be one of the largest heterogeneous data intensive HPC systems available to EPSRC research in the UK. In order to create the critical mass in terms of system capability and capacity needed to make an impact at National level Cambridge have pooled funding and equipment resources from the University, STFC DiRAC and this EPSRC Tier 2 proposal to create a total capital equipment value of £11.5M; the request to EPSRC is £5M. The University will guarantee to cover all operational costs of the system for 4 years from the service start date, with the option to run for a fifth year to be discussed. Cambridge will ensure that 80% of the EPSRC funded element of Peta-5 is deployed on EPSRC research projects, with 65% of the EPSRC funded element of Peta-5 being made available to any UK EPSRC funded project free of charge by use of a light weight resource allocation committee, 15% going to Cambridge EPSRC research and 20% being sold to UK industry to drive the UK knowledge economy. The Peta-5 system will be the most capable HPC system in operation in the UK when it enters service in May 2017. In total Peta-5 will provide 3 petaflops (PF) of sustained performance derived from 3 heterogeneous compute elements, 1PF Intel X86, 1PF Intel KNL and 1PF NIVIDIA Pascal GPU (Peta-1) connected via a Pb/s HPC fabric (Peta-2) to an extreme I/O solid state storage pool (Peta-3), a petascale data analytics (Machine Learning + Hadoop) pool (Peta-4) and a large 15 PB tiered storage solution (Peta-5), all under a single execution environment. This creates a new HPC capability in the UK specifically designed to meet the requirements of both affordable petascale simulation and data intensive workloads combined with complex data analytics. It is the combination of these features which unlocks a new generation of computational science research.The core science justification for the Peta-5 service is based on three broad science themes: Materials Science and Computational Chemistry; Computational Engineering and Smart Cities; Health Informatics. These themes were chosen as they represent significant EPSRC research areas, which demonstrate large benefit from the data intensive HPC capability of Peta-5. The service will clearly be valuable for many other areas of heterogeneous computing and Data Intensive science. Hence a fourth horizontal thematic of "Heterogeneous - Data Intensive Science" is included. Initial theme allocation in the RAC will be: Materials 30%, Engineering 30%, Health, 20%, Heterogeneous - Data Intensive 20%. The Peta-5 facility will drive research discovery and impact at national level, creating the largest and most cost effective petascale HPC resource in the UK, bringing petascale simulation within the reach of a wide range of research projects and UK companies. Also Peta-5 is the first UK HPC system specifically designed for large scale machine learning and data analytics, combining the areas of HPC and Big Data, promising to unlock both knowledge and economic benefit from the Big Data revolution.
期刊论文(10)
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会议论文
DOI: 10.1017/jfm.2019.41
发表时间: 2019
期刊: Journal of Fluid Mechanics
影响因子: 3.7
作者: [Abderrahaman-Elena N]
通讯作者: Abderrahaman-Elena N
DOI: 10.1103/physrevb.104.155109
发表时间: 2021-10-05
期刊: PHYSICAL REVIEW B
影响因子: 3.7
作者: [Acharya, Swagata, Pashov, Dimitar, Katsnelson, Mikhail, I]
通讯作者: Katsnelson, Mikhail, I
DOI: 10.3390/sym13020169
发表时间: 2019-08
期刊: Symmetry
影响因子: --
作者: [Swagata Acharya;D. Pashov;François Jamet;M. Schilfgaarde]
通讯作者: Swagata Acharya;D. Pashov;François Jamet;M. Schilfgaarde
Numerical investigation of full helicopter with and without the ground effect
考虑和不考虑地面效应的全直升机数值研究
DOI: 10.1016/j.ast.2022.107401
发表时间: 2022
期刊: Aerospace Science and Technology
影响因子: 5.6
作者: [A.S.F. Silva P]
通讯作者: A.S.F. Silva P
7
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    • 批准号:
      ST/X00046X/1
    • 项目类别:
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    • 资助金额:
      $23.92万
    • 财政年份:
      2022
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    • 项目类别:
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    • 资助金额:
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      2020
    • 负责人:
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    • 批准号:
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    • 项目类别:
      Research Grant
    • 资助金额:
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    • 财政年份:
      2019
    • 负责人:
      Paul Alexander
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      ST/R001529/1
    • 项目类别:
      Research Grant
    • 资助金额:
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    • 财政年份:
      2018
    • 负责人:
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