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Stability Analysis and Performance Evaluation of Additive Mixed-Precision Runge-Kutta Methods

Communications on Applied Mathematics and Computation 2024年第1期6卷 705-738页

作者： Ben Burnett Sigal Gottlieb Zachary J.Grant Center for Scientific Computing and Data Science Research UMass DartmouthNorth DartmouthMassachusettsUSA CSME Michigan State UniversityEast LansingMichiganUSA

Additive Runge-Kutta methods designed for preserving highly accurate solutions in mixed-precision computation were previously proposed and *** specially designed methods use reduced precision for the implicit computations and full precision for the explicit *** this work,we analyze the stability properties of these methods and their sensitivity to the low-precision rounding errors,and demonstrate their performance in terms of accuracy and *** develop codes in FORTRAN and Julia to solve nonlinear systems of ODEs and PDEs using the mixed-precision additive Runge-Kutta(MP-ARK)*** convergence,accuracy,and runtime of these methods are *** show that for a given level of accuracy,suitably chosen MP-ARK methods may provide significant reductions in runtime.

关键词： Mixed precision Runge-Kutta methods Additive methods Accuracy

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Solving key challenges in collider physics with foundation models

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Physical Review D 2025年第5期111卷 L051504-L051504页

作者： Vinicius Mikuni Benjamin Nachman National Energy Research Scientific Computing Center Berkeley Lab Berkeley California 94720 USA Physics Division Lawrence Berkeley National Laboratory Berkeley California 94720 USA Berkeley Institute for Data Science University of California Berkeley California 94720 USA

Foundation models are neural networks that are capable of simultaneously solving many problems. Large language foundation models like ChatGPT have revolutionized many aspects of daily life, but their impact for science is not yet clear. In this paper, we use a new foundation model for hadronic jets to solve three key challenges in collider physics. In particular, we show how experiments can (1) save significant computing power when developing reconstruction algorithms, (2) perform a complete uncertainty quantification for high-dimensional measurements, and (3) search for new physics with model agnostic methods using low-level inputs. In each case, there are significant computational or methodological challenges with current methods that limit the science potential of deep learning algorithms. By solving each problem, we take jet foundation models beyond proof-of-principle studies and into the toolkit of practitioners.

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Toward exponentially-convergent simulations of extreme-mass-ratio inspirals: A time-domain solver for the scalar Teukolsky equation with singular source terms

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Physical Review D 2024年第10期110卷 104009页

作者： Manas Vishal Scott E. Field Katie Rink Sigal Gottlieb Gaurav Khanna Department of Mathematics Center for Scientific Computing and Data Science Research Department of Physics Center for Gravitational Physics Department of Physics and Center for Computational Research

Gravitational wave signals from extreme mass ratio inspirals are a key target for upcoming, space-based gravitational wave detectors. These systems are typically modeled as a distributionally forced Teukolsky equation, where the smaller black hole is treated as a Dirac delta distribution (i.e., a point-particle). Time-domain solvers often use regularization approaches that approximate the Dirac distribution. Unfortunately, such approaches often introduce small length scales (e.g., when the approximation is by a narrow Gaussian) and are a source of systematic error, especially near the smaller black hole. We describe a multidomain discontinuous Galerkin (DG) method for solving the distributionally forced s=0 Teukolsky equation that describes scalar fields evolving on a Kerr spacetime. To handle the Dirac delta, we expand the solution in spherical harmonics and recast the sourced Teukolsky equation as a first-order, one-dimensional symmetric hyperbolic system. This allows us to derive the method’s numerical flux to correctly account for the Dirac delta. As a result, our method achieves global spectral accuracy even at the source’s location. To connect the near field to future null infinity, we use the hyperboloidal layer method, allowing us to supply trivial outer boundary conditions and providing direct access to the far-field waveform. We document several numerical experiments where we test our method, including convergence tests against exact solutions, energy luminosities for circular orbits, the scheme’s superconvergence properties at future null infinity, and the late-time tail behavior of the scalar field. We also compare two systems that arise from different choices of the first-order reduction variables, finding that certain reasonable choices are numerically problematic in practice. The methods developed here may be beneficial when computing gravitational self-force effects, where the regularization procedure has been developed for the spherical harmonic mod

关键词： General relativity Numerical relativity Numerical simulations in gravitation & astrophysics

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Real-Time Food Simulation Using Real Hand Gesture for Malaysia Cultural Heritage 1

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3rd International Conference on Advanced computing and Intelligent Technologies, ICACIT 2023

作者： Ismail, Anita Fairos Ismail, Ajune Wanis Fadzli, Fazliaty Edora Shuib, Norhaida Mohd Mixed and Virtual Reality Research Lab ViCubeLab Faculty of Computing Universiti Teknologi Malaysia Johor81310 Malaysia UTM Big Data Center Ibnu Sina Institute of Scientific and Industrial Research Universiti Teknologi Malaysia Johor81310 Malaysia

ISBN: (数字)9789819719617

ISBN: (纸本)9789819719600

Virtual Reality (VR) thrives on interactivity, and recent strides in this domain emphasize the role of gesture interaction. This study delves into the immersive realm of hand gestures, designed to liberate VR users from conventional controllers like mice or keyboards. The primary aim is to explore the application of these gestures in preserving and perpetuating the traditional culinary heritage of Pulut Panggang, a revered dish in Malaysian culture. Pulut Panggang, considered intangible heritage, holds cultural significance that transcends generations, particularly among the youth. The study meticulously examines hand gesture movements tailored to emulate the traditional cooking techniques associated with Pulut Panggang. This includes gestures for spatula control, forward and backward motions simulating the rolling of rice, and lateral movements replicating the use of a bamboo fan for grilling the rice rolls. Emphasizing authenticity, the simulation adheres to traditional methodologies, employing customary tools and materials. This approach serves as a poignant means of preserving the essence of traditional cooking methods within the VR environment. By seamlessly integrating hand gesture controls into the simulation, users are guided through the six crucial steps involved in crafting Pulut Panggang. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Virtual reality

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Review of Model-Based Techniques in Augmented Reality Occlusion Handling 1st

Review of Model-Based Techniques in Augmented Reality Occlus...

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1st International Conference on Expert Clouds and Applications, ICOECA 2023

作者： Ahmad, Muhammad Anwar Suaib, Norhaida Mohd Ismail, Ajune Wanis ViCubeLab Faculty of Computing Universiti Teknologi Malaysia Johor81310 Malaysia UTM Big Data Center Ibnu Sina Institute of Scientific and Industrial Research Universiti Teknologi Malaysia Johor81310 Malaysia

ISBN: (纸本)9789819917440

This paper reviews a model-based method in occlusion handling. The common methods of handling occlusion in Augmented Reality (AR) can be generally classified as depth-based or model-based. This paper presents a review of model-based methods in order to gain understanding of the current state-of-the-art literature and challenges in this field. After searching and filtering in SCOPUS database, 7 papers ranging from 2015 to 2022 were selected for this review and analyzed. From the review, the main conclusion that can be drawn is the trend evolved from researching and developing on the Kinect device to handheld devices. The main challenges are improving the lighting interaction between real and virtual objects and also reducing misalignment due to reprojection errors. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Augmented reality

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A Variational Approach to Personalized Federated Learning and Its Improvement 20th

A Variational Approach to Personalized Federated Learning a...

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20th Principle and Practice of data and Knowledge Acquisition Workshop, PKAW 2024, held in conjunction with the 21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Wu, Huiwen Zhang, Shuo Research Center for Data Hub and Security Zhejiang Laboratory Hangzhou310000 China LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and System Sciences Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9789819600250

Federated learning (FL) is a new approach that allows clients from different locations to work together on a global model without sharing raw data. However, training one standard model is not optimal for local optimization due to heterogeneity. Thus, personalized federated learning (PFL) paradigms aim to combine local and global information while preserving diversity among local clients. However, these methods require more theoretical motivation. This paper formalizes the unfired analysis form by defining a linear mapping on the server’s aggregation step for a deeper understanding of the implementation design and to improve existing methods further. Moreover, we show that the existing FL and PFL methods are specific cases in our framework with selected mapping matrices, including FedAvg, FedMTL, FedProx, MAML, and pure local training. Based on that, we propose a novel data-driven graph Laplacian-induced PFL scheme named GLIP-FL to address statistical heterogeneity issues and improve computation efficiency. We implement evaluation experiments of the proposed method on four popular data sets with five FL baselines in three data partitions, both homogeneous and heterogeneous, and the comprehensive experiments show the great potential of our method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

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Novel signal-consistency test for gravitational-wave searches of generic black hole binaries

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Physical Review D 2024年第2期110卷 023042-023042页

作者： Stefano Schmidt Sarah Caudill Science Park 105 1098 XG Amsterdam The Netherlands Institute for Gravitational and Subatomic Physics (GRASP) Department of Physics Center for Scientific Computing and Data Science Research

We propose a novel signal-consistency test applicable to a broad search for gravitational waves emitted by generic binary black hole (BBH) systems. The test generalizes the time domain ξ2 signal-consistency test currently utilized by the gstlal pipeline, which quantifies the discrepancy between the expected signal-to-noise ratio time series with the measured one. While the traditional test is restricted to aligned-spin circular orbits and does not account for higher-order modes (HMs), our test does not make any assumption on the nature of the signal. After addressing the mathematical details of the new test, we quantify its advantages in the context of searching for precessing BBHs and/or BBHs with HM content. Our results reveal that, for precessing signals, the new test is optimal and has the potential to reduce the values of the ξ2 statistics by up to 2 orders of magnitude when compared to the standard test. However, in the case of signals with HM content, only a modest enhancement is observed. Recognizing the computational burden associated with the new test, we also derive an approximated signal-consistency test. This approximation maintains the same computational cost as the standard test and can be easily implemented in any matched-filtering pipeline with minimal changes, sacrificing only a few percent of accuracy in the low-SNR regime. However, in the high-SNR regime, the approximated signal-consistency test does not bring any improvement as compared to the “standard” one. By introducing our new test and its approximation and understanding their validity and limitation, this work will benefit any matched-filtering pipeline aimed at searching for BBH signals with strong precession and/or HM content.

关键词： Gravitational waves data analysis

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A Review of Three-Dimensional Medical Image Visualization

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Health data Science 2022年第1期2022卷 83-101页

作者： Liang Zhou Mengjie Fan Charles Hansen Chris R.Johnson Daniel Weiskopf National Institute of Health Data Science Peking UniversityBeijingChina Scientific Computing and Imaging Institute University of UtahSalt Lake CityUSA Visualization Research Center(VISUS) University of StuttgartStuttgartGermany

Importance. Medical images are essential for modern medicine and an important research subject in visualization. However,medical experts are often not aware of the many advanced three-dimensional (3D) medical image visualization techniques thatcould increase their capabilities in data analysis and assist the decision-making process for specific medical problems. Ourpaper provides a review of 3D visualization techniques for medical images, intending to bridge the gap between medicalexperts and visualization researchers. Highlights. Fundamental visualization techniques are revisited for various medicalimaging modalities, from computational tomography to diffusion tensor imaging, featuring techniques that enhance spatialperception, which is critical for medical practices. The state-of-the-art of medical visualization is reviewed based on aprocedure-oriented classification of medical problems for studies of individuals and populations. This paper summarizes freesoftware tools for different modalities of medical images designed for various purposes, including visualization, analysis, andsegmentation, and it provides respective Internet links. Conclusions. Visualization techniques are a useful tool for medicalexperts to tackle specific medical problems in their daily work. Our review provides a quick reference to such techniques giventhe medical problem and modalities of associated medical images. We summarize fundamental techniques and readily availablevisualization tools to help medical experts to better understand and utilize medical imaging data. This paper could contributeto the joint effort of the medical and visualization communities to advance precision medicine.

关键词： Image utilize Medical

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Fast waveform generation for gravitational waves using evolutionary algorithms

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Physical Review D 2024年第4期110卷 043035页

作者： Quirijn Meijer Sarah Caudill Institute for Gravitational and Subatomic Physics (GRASP) Department of Physics Science Park 105 1098XG Amsterdam The Netherlands Department of Physics Center for Scientific Computing and Data Science Research

Gravitational-wave analyses depend heavily on waveforms that model the evolution of compact binary coalescences as seen by observing detectors. In many cases these waveforms are given by waveform approximants, models that approximate the amplitude and phase of the waveform at a set of frequencies. Because of their omnipresence, improving the speed at which approximants can generate waveforms is crucial to accelerating the overall analysis of gravitational-wave detections. An optimization algorithm is proposed that can select at which frequencies in the spectrum an approximant should compute the power of a waveform, and at which frequencies the power can be safely interpolated at a minor loss in accuracy. The algorithm used is an evolutionary algorithm modeled after the principle of natural selection, iterating frequency arrays that perform better at every iteration. As an application, the candidates proposed by the algorithm are used to reconstruct signal-to-noise ratios. It is shown that the imrphenomxphm approximant can be sped up by at least 30% at a loss of at most 2.87% on the drawn samples, measured by the accuracy of the reconstruction of signal-to-noise ratios. The behavior of the algorithm as well as lower bounds on both speedup and error are explored, leading to a proposed proof of concept candidate that obtains a speedup of 46% with a maximum error of 0.5% on a sample of the parameter space used.

关键词： General relativity Gravitational waves

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Fault-Tolerant LOBPCG for Nuclear CI Calculations 23

Fault-Tolerant LOBPCG for Nuclear CI Calculations

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6th International Conference on High Performance computing in Asia-Pacific Region, HPC Asia 2023

作者： Shao, Meiyue Oryspayev, Dossay Yang, Chao Maris, Pieter Cook, Brandon School of Data Science Fudan University China Computational Science Initiative Brookhaven National Laboratory United States Department of Physics and Astronomy Iowa State University United States National Energy Research Scientific Computing Center Lawrence Berkeley National Laboratory United States

ISBN: (纸本)9781450398060

Exascale computing platforms with millions of compute units and with thousands of nodes are predicted to experience frequent faults which interrupt applications' execution. In this context resilience against faults becomes important. We examine user and software level fault mitigation strategies in a distributed LOBPCG algorithm targeting nuclear CI calculations. In particular, we present and evaluate one strategy that keeps the total number of fault-Tolerant LOBPCG iterations close to that of the standard LOBPCG algorithm ran on a fault-free machine. © 2023 ACM.

关键词： Fault tolerance

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