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CC* Data Storage: Cost-effective Attached Storage for High throughput computing using Homo- geneous IT (CASH HIT) supporting Penn State Science, the Open Science Grid and LIGO

CC* Data Storage: Cost-effective Attached Storage for High throughput computing using Homo- geneous IT (CASH HIT) supporting Penn State Science, the Open Science Grid and LIGO
CC* 数据存储:使用同质 IT (CASH HIT) 实现高吞吐量计算的经济高效附加存储,支持宾夕法尼亚州立大学科学学院、开放科学网格和 LIGO
批准号:
2346596
负责人:
Chad Hanna
金额:
$48.92万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2024
资助国家:
美国
项目状态:
未结题
起止时间:
2024-04-01 至 2026-03-31

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中文摘要
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英文摘要
Scientific computing needs continue to grow at an exponential rate driven by an exponential growth in data that often outpaces available resources. High performance, cost effective, data storage is a critical component of scientific workflows that produce and analyze large datasets. Penn State is providing cost-effective data storage to researchers across many scientific domains including physics, astronomy, biology and materials science. This work supports science at various scales from local Penn State researchers to researchers across the country. Much of the storage is available to external communities through the Open Science Grid, which allows US researchers to gain free access to computing resources. The project team is exploring several important scientific topics with storage including searching for ripples in space caused by black holes, searching for planets outside of our solar system that could support life, and studying gene regulation.Project goals include developing relationships with national cyberinfrastructure efforts such as the Partnership to Advance Throughput computing; building a workforce that is able to leverage cost-effective, open source storage; and enabling research that otherwise would not be possible with existing storage resources and budgetary constraints. The project aims to provide 7.8 petabytes (PB) of storage. 2.9 PB of the storage (37%) will be available to external communities while the remaining 4.9 PB will be used internally. Among the externally allocated storage, 2 PB will be used for Open Science Data Federation (OSDF) applications and 900 TB will support a new regional initiative to provide storage for underserved institutions in Pennsylvania.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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会议论文
Discovering Neutron Stars and Black Holes with LIGO
CC* Compute: An Open Science Grid shared computing platform at Penn State
Framework: An A+ Framework for Multimessenger Astrophysics Discoveries through Real-Time Gravitational Wave Detection
CC* Team: Research Innovation with Scientists and Engineers (RISE)
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位:
基于Linked Open Data的Web服务语义互操作关键技术
  • 批准号:
    61373035
  • 项目类别:
    面上项目
  • 资助金额:
    77.0万元
  • 批准年份:
    2013
  • 负责人:
    冯志勇
  • 依托单位: