REU Site: Collaborative Research: BigDataX: From theory to practice in Big Data computing at eXtreme scales
REU 网站:协作研究:BigDataX:极限规模大数据计算从理论到实践
基本信息
- 批准号:1757970
- 负责人:
- 金额:$ 3.5万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-02-15 至 2022-01-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This award extends the BigDataX program, a Research Experiences for Undergraduates (REU) site at Illinois Institute of Technology (IIT) and the University of Chicago (UChicago). The BigDataX site focuses on undergraduate research in both the theory and practice of big data computing at extreme scales. BigDataX includes a diverse group of 10 undergraduate students, who will conduct research over a 10 week period, in the area of big data and how it will impact the design, analysis, and implementation of run-time systems and storage systems to support big data applications. This research will make extreme scale computing more tractable, touching every branch of computing in high-end computing and datacenters. These advancements will impact scientific discovery and economic development at the national level, and they will strengthen a wide range of research activities enabling efficient access, processing, storage, and sharing of valuable scientific data from many disciplines. The proposed work will place students in the middle of a technological revolution which will revolutionize the computing domain. The primary objective of this proposal is to promote a data-centric view of scientific and technical computing, at the intersection of distributed systems theory and practice. This proposal includes 6 mentors, with a variety of complementing expertise from theory to systems, distributed systems, storage management, and data science. The mentors have extensive experience in mentoring undergraduate students, collectively having worked with over one hundred students in research activities, publishing dozens peer-reviewed workshop/conference/journal papers at top venues together with undergraduate students. The students that will be part of the BigDataX program will be exposed to big data applications, large data sets, and various distributed systems such as the Mystic reconfigurable testbed at IIT, Chameleon cloud and Theta supercomputer at Argonne National Laboratory, the XSEDE national cyberinfrastructure, and the Amazon Web Services cloud.
该奖项扩展了BigDataX项目,这是伊利诺伊理工学院(IIT)和芝加哥大学(UChicago)的本科生研究经验(REU)项目。BigDataX网站的重点是本科生在极端规模下的大数据计算理论和实践方面的研究。BigDataX包括一个由10名本科生组成的多元化小组,他们将在10周的时间内进行大数据领域的研究,以及大数据将如何影响运行时系统和存储系统的设计、分析和实现,以支持大数据应用。这项研究将使极端规模计算更易于处理,触及高端计算和数据中心的每个计算分支。这些进步将影响国家一级的科学发现和经济发展,它们将加强广泛的研究活动,使来自许多学科的有价值的科学数据能够有效地获取、处理、存储和共享。这项被提议的工作将把学生置于一场技术革命的中心,这场革命将彻底改变计算领域。本提案的主要目标是在分布式系统理论和实践的交叉点上,促进以数据为中心的科学和技术计算观点。该提案包括6名导师,他们拥有从理论到系统、分布式系统、存储管理和数据科学的各种互补专业知识。导师们在指导本科生方面有着丰富的经验,共指导过一百多名学生进行研究活动,与本科生一起在顶级场所发表了数十篇同行评议的研讨会/会议/期刊论文。参加BigDataX项目的学生将接触大数据应用、大数据集和各种分布式系统,如印度理工学院的Mystic可重构试验台、阿贡国家实验室的变色龙云和Theta超级计算机、XSEDE国家网络基础设施和亚马逊网络服务云。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Kyle Chard其他文献
Walking the cost-accuracy tightrope: balancing trade-offs in data-intensive genomics
走成本准确性钢丝:平衡数据密集型基因组学的权衡
- DOI:
- 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
K. Leung;M. Kimball;Jason Pitt;A. Woodard;Kyle Chard - 通讯作者:
Kyle Chard
GreenFaaS: Maximizing Energy Efficiency of HPC Workloads with FaaS
GreenFaaS:利用 FaaS 最大限度提高 HPC 工作负载的能源效率
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Alok V. Kamatar;Valerie Hayot;Y. Babuji;André Bauer;Gourav Rattihalli;Ninad Hogade;D. Milojicic;Kyle Chard;Ian Foster - 通讯作者:
Ian Foster
Enabling real-time multi-messenger astrophysics discoveries with deep learning
利用深度学习实现实时多信使天体物理学发现
- DOI:
10.1038/s42254-019-0097-4 - 发表时间:
2019-10-03 - 期刊:
- 影响因子:39.500
- 作者:
E. A. Huerta;Gabrielle Allen;Igor Andreoni;Javier M. Antelis;Etienne Bachelet;G. Bruce Berriman;Federica B. Bianco;Rahul Biswas;Matias Carrasco Kind;Kyle Chard;Minsik Cho;Philip S. Cowperthwaite;Zachariah B. Etienne;Maya Fishbach;Francisco Forster;Daniel George;Tom Gibbs;Matthew Graham;William Gropp;Robert Gruendl;Anushri Gupta;Roland Haas;Sarah Habib;Elise Jennings;Margaret W. G. Johnson;Erik Katsavounidis;Daniel S. Katz;Asad Khan;Volodymyr Kindratenko;William T. C. Kramer;Xin Liu;Ashish Mahabal;Zsuzsa Marka;Kenton McHenry;J. M. Miller;Claudia Moreno;M. S. Neubauer;Steve Oberlin;Alexander R. Olivas;Donald Petravick;Adam Rebei;Shawn Rosofsky;Milton Ruiz;Aaron Saxton;Bernard F. Schutz;Alex Schwing;Ed Seidel;Stuart L. Shapiro;Hongyu Shen;Yue Shen;Leo P. Singer;Brigitta M. Sipocz;Lunan Sun;John Towns;Antonios Tsokaros;Wei Wei;Jack Wells;Timothy J. Williams;Jinjun Xiong;Zhizhen Zhao - 通讯作者:
Zhizhen Zhao
Unveiling Temporal Performance Deviation: Leveraging Clustering in Microservices Performance Analysis
揭示时间性能偏差:在微服务性能分析中利用集群
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
André Bauer;Timo Dittus;Martin Straesser;Alok V. Kamatar;Matt Baughman;Lukas Beierlieb;Marius Hadry;Daniel Grillmeyer;Yannik Lubas;Samuel Kounev;Ian Foster;Kyle Chard - 通讯作者:
Kyle Chard
A terminology for scientific workflow systems
科学工作流系统的术语
- DOI:
10.1016/j.future.2025.107974 - 发表时间:
2026-01-01 - 期刊:
- 影响因子:6.100
- 作者:
Frédéric Suter;Tainã Coleman;İlkay Altintaş;Rosa M. Badia;Bartosz Balis;Kyle Chard;Iacopo Colonnelli;Ewa Deelman;Paolo Di Tommaso;Thomas Fahringer;Carole Goble;Shantenu Jha;Daniel S. Katz;Johannes Köster;Ulf Leser;Kshitij Mehta;Hilary Oliver;J.-Luc Peterson;Giovanni Pizzi;Loïc Pottier;Rafael Ferreira da Silva - 通讯作者:
Rafael Ferreira da Silva
Kyle Chard的其他文献
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{{ truncateString('Kyle Chard', 18)}}的其他基金
Collaborative Research: Frameworks: Diamond: Democratizing Large Neural Network Model Training for Science
合作研究:框架:钻石:科学大型神经网络模型训练的民主化
- 批准号:
2311769 - 财政年份:2023
- 资助金额:
$ 3.5万 - 项目类别:
Standard Grant
Collaborative Research: REU Site: BigDataX: From theory to practice in Big Data computing at eXtreme scales
合作研究:REU 网站:BigDataX:极限规模大数据计算从理论到实践
- 批准号:
2150501 - 财政年份:2022
- 资助金额:
$ 3.5万 - 项目类别:
Standard Grant
Collaborative Research: Sustainability: A Community-Centered Approach for Supporting and Sustaining Parsl
合作研究:可持续性:以社区为中心的支持和维持 Parsl 的方法
- 批准号:
2209919 - 财政年份:2022
- 资助金额:
$ 3.5万 - 项目类别:
Standard Grant
Frameworks: Collaborative Research: ChronoLog: A High-Performance Storage Infrastructure for Activity and Log Workloads
框架:协作研究:ChronoLog:用于活动和日志工作负载的高性能存储基础架构
- 批准号:
2104008 - 财政年份:2021
- 资助金额:
$ 3.5万 - 项目类别:
Standard Grant
Collaborative Research: OAC Core: Enabling Extremely Fine-grained Parallelism on Modern Many-core Architectures
合作研究:OAC Core:在现代多核架构上实现极其细粒度的并行性
- 批准号:
2107283 - 财政年份:2021
- 资助金额:
$ 3.5万 - 项目类别:
Standard Grant
CCRI: Planning: Collaborative Research: Infrastructure for Enabling Systematic Development and Research of Scientific Workflow Management Systems
CCRI:规划:协作研究:支持科学工作流程管理系统系统开发和研究的基础设施
- 批准号:
2016682 - 财政年份:2020
- 资助金额:
$ 3.5万 - 项目类别:
Standard Grant
CSR: Small: Cost-Aware Cloud Profiling, Prediction, and Provisioning as a Service
CSR:小:具有成本意识的云分析、预测和配置即服务
- 批准号:
1816611 - 财政年份:2018
- 资助金额:
$ 3.5万 - 项目类别:
Standard Grant
Collaborative Research: SI2-SSI: Swift/E: Integrating Parallel Scripted Workflow into the Scientific Software Ecosystem
协作研究:SI2-SSI:Swift/E:将并行脚本工作流程集成到科学软件生态系统中
- 批准号:
1550588 - 财政年份:2016
- 资助金额:
$ 3.5万 - 项目类别:
Standard Grant
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