CCRI: ENS: Cognitive Hardware and Software Ecosystem Community Infrastructure (CHASE-CI)
CCRI: ENS: Cognitive Hardware and Software Ecosystem Community Infrastructure (CHASE-CI)
批准号:
2120019
负责人:
Thomas DeFanti
金额:
$180.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-10-01 至 2025-09-30
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Machine learning (ML) is a rapidly expanding field. Computationally intensive workflows train neural nets and then use the results in smartphones, robots, drones, self-driving vehicles, and to run the Internet of Things. Access to graphics processing units (GPUs) is provided through CHASE-CI’s Nautilus, a highly distributed but centrally managed on-demand computer cluster designed for ML and Computational Media (CM). CHASE-CI provides over 20 campuses the scaffold for adding on-premises compute cycles and fast data handling and it offers researcher-focused support and training. Using CHASE-CI’s detailed measurements of performance, researchers learn to become experts in optimization of their computational resources.CHASE-CI is a community-building effort that sustains a growing community of ML/CM researchers using a purpose-built continuously enhanced nationally distributed computing and data storage infrastructure. Researchers explore combinations of algorithms and architectures optimized with the help of graphed performance metrics. Researchers benefit from extensive shared workflows and open-source software. They use CHASE-CI’s on-line social media platform to receive and give support and share techniques. Community use of CHASE-CI informs computer architecture discussions about future national cyberinfrastructure research and instructional lab needs. CHASE-CI forms a national on-line community that is easy to join, designed for sharing code, data, and results.The hardware, software, and socio-technical approaches developed by CHASE-CI have provided a roadmap for broader research uses and student training in ML/CM technologies. Researchers get expanded access to hundreds of GPUs for developing algorithms and software to train sensing devices and visualize results thus engaging the students who will soon join the essential workforce for the ongoing massive expansion of mobile platforms such as robots, drones, and self-driving cars. CHASE-CI impacts social diversity in computer science, broadening participation among Minority-Serving Institutions and underserved states. CHASE-CI thoroughly measures and monitors data access by applications over the regional and national R&E networks. The repository for the project may be found at prp.ucsd.edu, to be maintained for the length of the project at a minimum. It is the anchor website containing pointers to all the research efforts that build upon the Pacific Research Platform. It contains code repositories, presentations, references like publications, presentations, and recorded lectures, and it maintains and archives an active social media channel. CHASE-CI is led by UC San Diego, partnering with investigators at UC Santa Cruz, The University of Nebraska-Lincoln, Florida Agricultural and Mechanical University, New York University, The University of Illinois at Chicago, and San Diego State University.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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DOI:
10.1128/msystems.01378-21
发表时间:
2022-04-26
期刊:
mSystems
影响因子:
6.4
作者:
[]
通讯作者:
HyperSpikeASIC: Accelerating Event-based Workloads with HyperDimensional Computing and Spiking Neural Networks
HyperSpikeASIC:利用超维计算和尖峰神经网络加速基于事件的工作负载
DOI:
10.1109/tcad.2023.3264167
发表时间:
2023
期刊:
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
影响因子:
2.9
作者:
[Zhang, T., Morris, J., Stewart, K., Lui, H.W., Khaleghi, B., Thomas, A., Goncalves-Marback, T., Aksanli, B., Neftci, E.O., Rosing, T.]
通讯作者:
Rosing, T.
DOI:
10.1016/j.compind.2022.103660
发表时间:
2022-09
期刊:
Comput. Ind.
影响因子:
--
作者:
[Onat Güngör;Tajana Simunic;Baris Aksanli]
通讯作者:
Onat Güngör;Tajana Simunic;Baris Aksanli
DOI:
10.1109/wacv56688.2023.00087
发表时间:
2022-07
期刊:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
影响因子:
--
作者:
[Kai-En Lin;Yen-Chen Lin;Wei-Sheng Lai;Tsung-Yi Lin;Yichang Shih;R. Ramamoorthi]
通讯作者:
Kai-En Lin;Yen-Chen Lin;Wei-Sheng Lai;Tsung-Yi Lin;Yichang Shih;R. Ramamoorthi
OverlaPIM: Overlap Optimization for Processing In-Memory Neural Network Acceleration
OverlaPIM:处理内存中神经网络加速的重叠优化
DOI:
10.23919/date56975.2023.10137223
发表时间:
2023
期刊:
Automation & Test in Europe Conference & Exhibition (DATE
影响因子:
--
作者:
[Zhou, Minxuan, Wang, Xuan, Rosing, Tajana]
通讯作者:
Rosing, Tajana
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MRI: Development of Instrumentation for AGAVE: The Access Grid Autostereo Virtual Environment
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Development of Instrumentation for Shared Virtual Prototyping: The ImmersaDesk and the NII/Wall
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Quantitative Assessment of Transfer of Training in the CAVE Virtual Environment and its Relevance to the National Information Infrastructure
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