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Physical data layout is an important performance factor for modern databases. Clustering, i.e., storing similar values in proximity, can lead to performance gains in several ways. We present an automated model to determine beneficial…

Databases · Computer Science 2021-03-30 Alexander Löser

We discuss the state of art of Lattice Boltzmann (LB) computing, with special focus on prospective LB schemes capable of meeting the forthcoming Exascale challenge. After reviewing the basic notions of LB computing, we discuss current…

Computational Physics · Physics 2020-06-14 Sauro Succi , Giorgio Amati , Massimo Bernaschi , Giacomo Falcucci , Marco Lauricella , Andrea Montessori

Containers improve the efficiency in application deployment and thus have been widely utilised on Cloud and lately in High Performance Computing (HPC) environments. Containers encapsulate complex programs with their dependencies in isolated…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-12-20 Naweiluo Zhou , Huan Zhou , Dennis Hoppe

High dimensional integrals are abundant in many fields of research including quantum physics. The aim of this paper is to develop efficient recursive strategies to tackle a class of high dimensional integrals having a special product…

Numerical Analysis · Mathematics 2021-07-28 Tobias Hartung , Karl Jansen , Frances Y. Kuo , Hernan Leövey , Dirk Nuyens , Ian H. Sloan

A new algorithm for simulating compact U(1) lattice gauge theory in three dimensions is presented which is based on global changes in the configuration space. We show that this algorithm provides an effective way to extract partition…

High Energy Physics - Lattice · Physics 2009-11-10 F. Alet , B. Lucini , M. Vettorazzo

Performing analytic of household load curves (LCs) has significant value in predicting individual electricity consumption patterns, and hence facilitate developing demand-response strategy, and finally achieve energy efficiency improvement…

Data Structures and Algorithms · Computer Science 2018-11-27 Yunyou Huang , Jianfeng Zhan , Nana Wang , Chunjie Luo , Lei Wang , Rui Ren

Recent breakthroughs in Large-scale language models (LLMs) have demonstrated impressive performance on various tasks. The immense sizes of LLMs have led to very high resource demand and cost for running the models. Though the models are…

Machine Learning · Computer Science 2024-03-05 Juntao Zhao , Borui Wan , Yanghua Peng , Haibin Lin , Chuan Wu

Finite mixture models have become a popular tool for clustering. Amongst other uses, they have been applied for clustering longitudinal data and clustering high-dimensional data. In the latter case, a latent Gaussian mixture model is…

Methodology · Statistics 2018-04-17 Vanessa S. E. Bierling , Paul D. McNicholas

Optimizing resource utilization in high-performance computing (HPC) clusters is essential for maximizing both system efficiency and user satisfaction. However, traditional rigid job scheduling often results in underutilized resources and…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-20 Patrick Zojer , Jonas Posner , Taylan Özden

We present a comparison study between a cluster and factor graph representation of LDPC codes. In probabilistic graphical models, cluster graphs retain useful dependence between random variables during inference, which are advantageous in…

Information Theory · Computer Science 2023-10-03 J du Toit , J du Preez , R Wolhuter

Simulating quantum circuits (QC) on high-performance computing (HPC) systems has become an essential method to benchmark algorithms and probe the potential of large-scale quantum computation despite the limitations of current quantum…

The concrete schemes to realize three types of basic quantum logical gates using linear quadripartite cluster states of optical continuous variables are proposed. The influences of noises and finite squeezing on the computation precision…

Quantum Physics · Physics 2015-05-13 Aihong Tan , Changde Xie , Kunchi Peng

We review recent progress on lattice calculations of nucleon spin structure, including the parton distribution functions, form factors, generalization parton distributions, and recent developments in lattice techniques.

High Energy Physics - Lattice · Physics 2009-08-24 Huey-Wen Lin

One of the ultimate missions of lattice QCD is to simulate atomic nuclei from the first principle of the strong interaction. This is an extremely hard task for the current computational technology, but might be reachable in coming quantum…

High Energy Physics - Lattice · Physics 2024-03-19 Arata Yamamoto , Takumi Doi

Cluster analysis is widely used in the areas of machine learning and data mining. Fuzzy clustering is a particular method that considers that a data point can belong to more than one cluster. Fuzzy clustering helps obtain flexible clusters,…

Machine Learning · Computer Science 2018-06-06 Aybükë Oztürk , Stéphane Lallich , Jérôme Darmont

Grid Computing is an idea of a new kind of network technology in which research work in progress. There is a great deal of hype in this technology based area for that reason it is getting a great deal of attention of the computing…

Networking and Internet Architecture · Computer Science 2019-03-19 Robail Yasrab

In this work, we aim to solve a practical use-case of unsupervised clustering which has applications in predictive maintenance in the energy operations sector using quantum computers. Using only cloud access to quantum computers, we…

Quantum Physics · Physics 2022-09-13 Stephen DiAdamo , Corey O'Meara , Giorgio Cortiana , Juan Bernabé-Moreno

We discuss the implementation of lattice gauge theories on digital quantum computers, focusing primarily on the number of quantum gates required to simulate their time evolution. We find that to compile quantum circuits, using available…

High Energy Physics - Lattice · Physics 2022-11-23 Edison M. Murairi , Michael J. Cervia , Hersh Kumar , Paulo F. Bedaque , Andrei Alexandru

A novel scheme is presented for fault-tolerant quantum computation based on the cluster model. Some relevant logical cluster states are constructed in concatenation by post-selection through verification, without necessity of recovery…

Quantum Physics · Physics 2010-08-24 Keisuke Fujii , Katsuji Yamamoto

A novel technique using machine learning (ML) to reduce the computational cost of evaluating lattice quantum chromodynamics (QCD) observables is presented. The ML is trained on a subset of background gauge field configurations, called the…

High Energy Physics - Lattice · Physics 2019-07-24 Boram Yoon , Tanmoy Bhattacharya , Rajan Gupta