CC* Storage: Implementation of a Distributed, Shareable, and Parallel Storage Resource at San Diego State University to Facilitate High-Performance Computing for Climate Science

CC* 存储：在圣地亚哥州立大学实施分布式、可共享和并行存储资源，以促进气候科学的高性能计算

• 批准号: 1659169
• 负责人: Christopher Paolini
• 金额: $ 20万
• 依托单位: San Diego State University Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-01 至 2020-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1659169&HistoricalAwards=false
• 关键词: CC; Storage; Implementation; Distributed; Shareable

This project develops a high-capacity, high-performing storage system closely matched to the identified needs of climate science, but also of interest to a wide range of research and engineering fields such as brain and behavior research, high-energy physics, renewable energy, genomics, bioinformatics, computational chemistry, and the study of dark matter. The two-tiered design of the storage system is consistent with best practices and would maximize research capacity and utilization.The effort would create a distributed, shareable and parallel cluster running the BeeGFS file system (a European development), delivering about 1.8 PB (usable) storage and capable of up to 5GB/sec of streaming performance. The project would support twelve science, technology, engineering and mathematics (STEM) projects in a broad range of disciplines; co-investigators in mechanical, environmental, civil and aerospace engineering, computer science, and biology are participating. The results would improve input-output operations associated with a number of research and engineering computation bottlenecks: parallel sequential writing during distributed-parallel geochemical, computational fluid dynamics, and structural mechanics simulations; new file creation during real-time data acquisition; and random read operations during post-processing and visualization.

该项目开发了一个高容量，高性能的存储系统，与气候科学的需求密切匹配，但也对广泛的研究和工程领域感兴趣，如大脑和行为研究，高能物理，可再生能源，基因组学，生物信息学，计算化学和暗物质的研究。 存储系统的两层设计符合最佳实践，将最大限度地提高研究容量和利用率。这项工作将创建一个分布式、可共享和并行的集群，运行BeeGFS文件系统（欧洲开发），提供约1.8 PB（可用）存储空间，并能够实现高达5GB/秒的流性能。 该项目将支持12个科学，技术，工程和数学（STEM）项目，涉及广泛的学科;机械，环境，土木和航空航天工程，计算机科学和生物学的共同研究人员正在参与。 这些结果将改善与许多研究和工程计算瓶颈相关的输入输出操作：分布式并行地球化学，计算流体动力学和结构力学模拟期间的并行顺序写入;实时数据采集期间的新文件创建;以及后处理和可视化期间的随机读取操作。

项目成果

Laying the Groundwork for Automated Computation of Surrogate Safety Measures (SSM) for Skateboarders and Pedestrians using Artificial Intelligence

为利用人工智能自动计算滑板运动员和行人的替代安全措施 (SSM) 奠定基础

• DOI: 10.1109/ai4i49448.2020.00011
• 发表时间: 2020
• 期刊: 2020 Third International Conference on Artificial Intelligence for Industries (AI4I
• 作者: Shourov, Erfan Chowdhury;Paolini, Christopher
• 通讯作者: Paolini, Christopher

Solving Poisson equation with Robin boundary condition on a curvilinear mesh using high order mimetic discretization methods

使用高阶模拟离散化方法求解曲线网格上具有 Robin 边界条件的泊松方程

• DOI: 10.1016/j.matcom.2014.10.004
• 发表时间: 2017
• 期刊: Mathematics and Computers in Simulation
• 影响因子: 4.6
• 作者: Abouali, Mohammad;Castillo, Jose E.
• 通讯作者: Castillo, Jose E.

Solving the linear inviscid shallow water equations in one dimension, with variable depth, using a recursion formula

使用递归公式求解可变深度的一维线性无粘浅水方程

• DOI: 10.1088/1361-6404/aa864b
• 发表时间: 2017
• 期刊: European Journal of Physics
• 影响因子: 0.7
• 作者: Hernandez-Walls, R;Martín-Atienza, B;Salinas-Matus, M;Castillo, J
• 通讯作者: Castillo, J

High-order mimetic finite differences for anisotropic elliptic equations

各向异性椭圆方程的高阶模拟有限差异

• DOI: 10.1016/j.compfluid.2020.104746
• 发表时间: 2020
• 期刊: Computers & Fluids
• 影响因子: 2.8
• 作者: Boada, Angel;Paolini, Christopher;Castillo, Jose E.
• 通讯作者: Castillo, Jose E.

SC16 student cluster competition challenge: Investigating the reproducibility of results for the ParConnect application

SC16 学生集群竞赛挑战：调查 ParConnect 应用程序结果的可重复性

• DOI: 10.1016/j.parco.2017.07.010
• 发表时间: 2017
• 期刊: Parallel Computing
• 影响因子: 1.4
• 作者: Williams, G.R.;Behm, G.P.;Nguyen, T.;Esparza, A.;Haka, V.G.;Ramos, A.;Wright, B.;Otto, J.C.;Paolini, C.P.;Thomas, M.P.
• 通讯作者: Thomas, M.P.