Projects
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Goal. The overarching goal of this Abisko project is to develop an energy-efficient spiking neural net-work (SNN) computing architecture and software system capable of…
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Goal. The overarching goal of this Bluestone project is to enable new levels of performance portability of high-performance computing (HPC) and artificial intelligence (AI)…
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Video introduction to VISTA. The VISTA laboratory is an engine for connecting scientists and engineers with complicated data to the tools and techniques that allow them to visualize, re-use, and explore… This visualization shows the edge-localized structures that emerge due to turbulence in a… One of VISTA's notable community-building activities is the monthly VISTA online seminar series. This series is for sharing ideas, experiences, and opportunities from one… Visualization and data analysis are essential components of the scientific discovery process. Presented by Dave Pugmire from ORNL’s…
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Principal Investigator: Guannan Zhang (CSMD, ORNL) Senior Investigators: Jiaxin Zhang (CSMD, ORNL), Hoang Tran (CSMD, ORNL), Miroslav Stoyanov (CSMD, ORNL), Sirui… In Dec. 2020, Jiaxin Zhang gave a presentation on Bayesian experimental design at… Publications: Y. Teng, Z. Wang, L. Ju, A. Gruber, and G. Zhang, Level set learning with pseudo-reversible neural networks for nonlinear dimension reduction in function… Activities: In May 2021, Pei Zhang gave a presentation on our work "A prediction interval method for uncertainty quantification of regression models", at the ICLR…
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Principal Investigator: Guannan Zhang (CSMD, ORNL) Senior Investigators: , Jiaxin Zhang (CSMD, ORNL), Hoang Tran (CSMD, ORNL), Dan Lu (CSED, … In Dec. 2020, Jiaxin Zhang gave a presentation on our DGS gradient optimization method… Publications: H. Tran and G. Zhang, An adaptive nonlocal gradient descent method for high-dimensional black-box optimization, SIAM Journal on Scientific Computing,… Activities: In October 2022, H. Tran presented our work on “Exploiting the local parabolic landscapes of adversarial losses to accelerate black-box adversarial attack” at…
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Principal Investigator: Guannan Zhang (CSMD, ORNL) Senior Investigators: , Jiaxin Zhang (CSMD, ORNL), Hoang Tran (CSMD, ORNL), Dan Lu (CSED, … In Dec. 2020, Jiaxin Zhang gave a presentation on our DGS gradient optimization method… Publications: H. Tran and G. Zhang, An adaptive nonlocal gradient descent method for high-dimensional black-box optimization, SIAM Journal on Scientific Computing,… Activities: In October 2022, H. Tran presented our work on “Exploiting the local parabolic landscapes of adversarial losses to accelerate black-box adversarial attack” at…
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Searching for researcher information
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Participants Oak Ridge National Laboratory: Jeffrey S. Vetter (PI), Joel E. Denny, Jungwon Kim, and Seyong Lee University of Oregon: Allen D. Malony (Co-PI), Sameer Shende…
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Cosmic Castle Architectural Overview Integrated Cosmic Castle workflow for design, analysis, and execution including the innovative Performance Functional Unity (PFU)… Sponsor This research is supported by the Defense Advanced Research Projects Agency (DARPA) Broad Agency Announcement (BAA) HR001117S0055 titled, “Electronics Resurgence…
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Description Clacc is developing open-source, production-quality, standard-conforming OpenACC compiler, runtime, and profiling support by extending Clang and LLVM. OpenACC…
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Motivation Non-Volatile Memory (NVM) is any solid-state memory technology whose data is persistent across power loss. The primary NVM technology used today is flash in the…
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Overview Papyrus allows the programmers to exploit large aggregate NVM space in the system without handling complex communication, synchronization, replication, and…
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Motivation Directive-based GPU programming models are gaining momentum since they transparently relieve programmers from dealing with complex language syntax of low-level… Built on top of the Cetus compiler infrastructure, OpenARC's program representation inherits several of its predecessor's salient features. OpenARC's IR is… The overall tuning process is as follows: The search space pruner analyzes an input OpenARC program plus optional user settings, which exist as annotations in the input… Publications To cite OpenARC, please use the following papers (you can download bibtex files from each link): Seyong Lee and Jeffrey S. Vetter, OpenARC: Open Accelerator…
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Simulation, Modeling, Measurement Memory systems are the next major technical challenge in emerging HPC architectures Performance, Capacity, Heterogeneity, Cost, Power New device technology emerging…
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The Oak Ridge National Laboratory (ORNL) Center for Infrastructure Security Analysis (CISA) Program was founded in 2007 to support the U.S. Department of Homeland Security’s…
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Dream Module DiffeRential Evolution Adaptive Metropolis (DREAM) is an algorithm for sampling from a general probability density when only the probability density function is…
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What is EQUINOX? EQUINOX is a multi-institutional ASCR funded effort to to establish a modern mathematical and statistical foundation that will enable next-generation,…
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During the two-year span of this project, we will focus on seven different problems to demonstrate the ability of ACUMEN to solve the specific mathematical challenges at…
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Deep Learning is a sub-field of machine learning that focuses on learning features from data through multiple layers of abstraction. These features are learned with little…
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The objective of this research is to design and evaluate a new distributed data storage paradigm that unifies the traditionally distinct application views of memory- and file-…
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The Programming Models and Languages team is focused on developing the OpenSHMEM programming model for extreme scale systems. Towards this goal, the team conducts…
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Software Links: Project ADIOS 1.x ADIOS2 Github ADIOS 1.x ADIOS2 Documentation ADIOS2 The Adaptable IO System (ADIOS) provides a simple, flexible…
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SOLLVE project primarily aims at scaling OpenMP by leveraging LLVM for exascale performance and portability of applications. The OpenMP standard and implementations evolve at…
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The CODAR project is lead by Ian Foster of Argonne National Laboratory. The management team includes Todd Munson (ANL), Scott Klasky (ORNL), and Kerstin Kleese Van Dam (BNL…
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The objective of this project is to develop, and integrate, high-performance simulation tools capable of predicting plasma facing component (PFC) operating lifetime and the…
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About the DOE Early Career Program The program, started in 2009, supports the development of individual research programs of outstanding scientists early in their careers and…
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SharP is a data-centric programming paradigm for extreme-scale systems with hierarchical heterogenous memory.
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Visualization of the flux surface within a fusion tokamak device from a WDM simulation.
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This project intends to deliver an operating system and runtime (OS/R) environment for extreme-scale scientific computing. With application composition as the fundamental…
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This project is focused on the development of polynomial approximation methods for data from physical experiments and numerical simulations. The need for efficient…
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This project is focused on the development of hybrid, hierarchical, and multilevel algorithms for the simulation of complex many‐particle systems. Such systems are key…
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The objective of this project is to develop novel software tools for increasing the efficiency and usability of codes on extreme‐scale computing systems. The research will…