Conference: Workshop on Sparse Tensor Computations

会议:稀疏张量计算研讨会

基本信息

项目摘要

The Workshop on Sparse Tensor Computations will be held October 18-19, 2023, in Chicago, IL at the Discovery Partners Institute, a satellite location of the University of Illinois Urbana-Champaign. The workshop will consist of approximately 20 talks over one and a half days, and it will include a poster session. We expect to attract approximately 80 participants, mostly from the United States. The project will financially support 20-30 students or junior researchers from academic institutions in the United States to attend and present at the workshop. In addition to providing broad dissemination of recent advances in sparse tensor computations, the workshop promotes vertical integration by emphasizing the contributions of young scientists. The broad range of domains that develop and utilize sparse tensor computations is reflected in the attendees of the workshop, which will lure participants into exploring questions outside their immediate areas of interest. The Workshop on Sparse Tensor Computations will help society by promoting the careers of talented students and early career scientists, encouraging their future scientific pursuits and pushing the boundaries of computational problems that can be solved effectively and efficiently.Tensors provide a data abstraction of high-order interactions and act as an interface between applications, mathematical models, and computation. They have proved effective across a variety of application areas, including scientific computing domains and partial differential equation models, unsupervised machine learning problem involving multi-parameter observations, and many others. Across a number of application domains as well as in fields of applied mathematics and computer science, research on tensor methods has been particularly active and continues to grow. The workshop is organized to facilitate transfer of ideas among researchers in tensor computations from various fields, including scientific and machine learning applications, algorithms, software, compilers, and architectures. Graduate students, postdoctoral researches, junior faculty, and senior faculty will present work to one another, attend talks together, and interact closely during a poster session. The conference website is located at https://solomonik.cs.illinois.edu/tensor_workshop/index.html.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.
稀疏张量计算研讨会将于2023年10月18日至19日在伊利诺伊州芝加哥的Discovery Partners研究所举行,该研究所是伊利诺伊大学厄巴纳-香槟分校的卫星位置。研讨会将在一天半的时间里举行约20场演讲,并将包括一场海报展示会。我们预计将吸引大约80名与会者,其中大部分来自美国。该项目将资助来自美国学术机构的20-30名学生或初级研究人员参加讲习班。 除了广泛传播稀疏张量计算的最新进展外,研讨会还通过强调年轻科学家的贡献来促进垂直整合。 开发和利用稀疏张量计算的广泛领域反映在研讨会的与会者中,这将吸引与会者探索他们感兴趣的直接领域之外的问题。稀疏张量计算研讨会将通过促进有才华的学生和早期职业科学家的职业生涯、鼓励他们未来的科学追求并突破可以有效解决的计算问题的界限来帮助社会。张量提供了高阶交互的数据抽象并充当应用程序、数学模型和计算之间的接口。 它们在各种应用领域都被证明是有效的,包括科学计算领域和偏微分方程模型,涉及多参数观测的无监督机器学习问题等等。 在许多应用领域以及应用数学和计算机科学领域,张量方法的研究一直特别活跃,并继续增长。该研讨会旨在促进来自各个领域的张量计算研究人员之间的思想交流,包括科学和机器学习应用,算法,软件,编译器和架构。研究生,博士后研究,初级教师和高级教师将相互介绍工作,一起参加会谈,并在海报会议期间密切互动。 会议网站位于https://solomonik.cs.illinois.edu/tensor_workshop/index.html.This奖项反映了NSF的法定使命,并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

项目成果

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Edgar Solomonik其他文献

Accelerating the Galerkin Reduced-Order Model with the Tensor Decomposition for Turbulent Flows
用湍流张量分解加速伽辽金降阶模型
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Ping;Paul Fischer;Edgar Solomonik
  • 通讯作者:
    Edgar Solomonik
Communication-Avoiding Parallel Algorithms for Solving Triangular Systems of Linear Equations
求解线性方程组三角系统的避免通信并行算法
Highly scalable parallel sorting
高度可扩展的并行排序
Histogram Sort with Sampling
带采样的直方图排序
Improving communication performance in dense linear algebra via topology aware collectives
通过拓扑感知集体提高密集线性代数的通信性能

Edgar Solomonik的其他文献

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{{ truncateString('Edgar Solomonik', 18)}}的其他基金

CAREER: Next-Generation Infrastructure for Tensor Computations
职业:用于张量计算的下一代基础设施
  • 批准号:
    1942995
  • 财政年份:
    2020
  • 资助金额:
    $ 4.35万
  • 项目类别:
    Continuing Grant
Collaborative Research: Frameworks: Scalable Modular Software and Methods for High-Accuracy Materials and Condensed Phase Chemistry Simulation
合作研究:框架:用于高精度材料和凝聚相化学模拟的可扩展模块化软件和方法
  • 批准号:
    1931258
  • 财政年份:
    2019
  • 资助金额:
    $ 4.35万
  • 项目类别:
    Standard Grant

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