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In many real-world applications we are interested in approximating costly functions that are analytically unknown, e.g. complex computer codes. An emulator provides a fast approximation of such functions relying on a limited number of…

Methodology · Statistics 2020-10-02 Hossein Mohammadi , Peter Challenor , Marc Goodfellow , Daniel Williamson

Networks of interconnected resistors, springs and beams, or pores are standard models of studying scalar and vector transport processes in heterogeneous materials and media, such as fluid flow in porous media, and conduction, deformations,…

Computational Physics · Physics 2019-08-12 Hassan Dashtian , Muhammad Sahimi

The $\mathcal{F}$-statistic is a detection statistic used widely in searches for continuous gravitational waves with terrestrial, long-baseline interferometers. A new implementation of the $\mathcal{F}$-statistic is presented which…

General Relativity and Quantum Cosmology · Physics 2022-06-14 Liam Dunn , Patrick Clearwater , Andrew Melatos , Karl Wette

There is an urgent and pressing need to optimize usage of Graphical Processing Units (GPUs), which have arguably become one of the most expensive and sought after IT resources. To help with this goal, several of the current generation of…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-09-11 Bekir Turkkan , Pavankumar Murali , Pavithra Harsha , Rohan Arora , Gerard Vanloo , Chandra Narayanaswami

There has been significant amount of excitement and recent work on GPU-based database systems. Previous work has claimed that these systems can perform orders of magnitude better than CPU-based database systems on analytical workloads such…

Databases · Computer Science 2020-03-04 Anil Shanbhag , Samuel Madden , Xiangyao Yu

We introduce a particle-based simulation method for granular material in interactive frame rates. We divide the simulation into two decoupled steps. In the first step, a relatively small number of particles is accurately simulated with a…

Graphics · Computer Science 2023-08-04 Alexander Sommer , Ulrich Schwanecke , Elmar Schömer

The vision of super computer at every desk can be realized by powerful and highly parallel CPUs or GPUs or APUs. Graphics processors once specialized for the graphics applications only, are now used for the highly computational intensive…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-04-16 Chittampally Vasanth Raja , Srinivas Balasubramanian , Prakash S Raghavendra

Image Processing is a specialized area of Digital Signal Processing which contains various mathematical and algebraic operations such as matrix inversion, transpose of matrix, derivative, convolution, Fourier Transform etc. Operations like…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-06-24 Batuhan Hangün , Önder Eyecioğlu

We present a novel, hardware-agnostic implementation strategy for lattice Boltzmann (LB) simulations, which yields massive performance on homogeneous and heterogeneous many-core platforms. Based solely on C++17 Parallel Algorithms, our…

Computational Physics · Physics 2021-05-11 Jonas Latt , Christophe Coreixas , Joël Beny

Design considerations for molecular dynamics algorithms capable of taking advantage of the computational power of a graphics processing unit (GPU) are described. Accommodating the constraints of scalable streaming-multiprocessor hardware…

Computational Physics · Physics 2011-01-27 D. C. Rapaport

Massive data sets have radically changed our understanding of how to design efficient algorithms; the streaming paradigm, whether it in terms of number of passes of an external memory algorithm, or the single pass and limited memory of a…

Graphics · Computer Science 2007-05-23 Suresh Venkatasubramanian

Graphical simulations are a cornerstone of modern media and films. But existing software packages are designed to run on HPC nodes, and perform poorly in the computing cloud. These simulations have complex data access patterns over complex…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-06-08 Omid Mashayekhi , Chinmayee Shah , Hang Qu , Andrew Lim , Philip Levis

Probabilistic breadth-first traversals (BPTs) are used in many network science and graph machine learning applications. In this paper, we are motivated by the application of BPTs in stochastic diffusion-based graph problems such as…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-21 Reece Neff , Mostafa Eghbali Zarch , Marco Minutoli , Mahantesh Halappanavar , Antonino Tumeo , Ananth Kalyanaraman , Michela Becchi

GPU activity prediction is an important and complex problem. This is due to the high level of contention among thousands of parallel threads. This problem was mostly addressed using heuristics. We propose a representation learning approach…

Machine Learning · Computer Science 2017-03-28 Aswin Raghavan , Mohamed Amer , Timothy Shields , David Zhang , Sek Chai

High performance computing (HPC) is a very attractive and relatively new area of research, which gives promising results in many applications. In this paper HPC is used for pricing of American options. Although the American options are very…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-05-02 Verche Cvetanoska , Toni Stojanovski

Graph embedding techniques have attracted growing interest since they convert the graph data into continuous and low-dimensional space. Effective graph analytic provides users a deeper understanding of what is behind the data and thus can…

Machine Learning · Computer Science 2022-01-21 Azita Nouri , Philip E. Davis , Pradeep Subedi , Manish Parashar

Graph analytics techniques based on spectral methods process extremely large sparse matrices with millions or even billions of non-zero values. Behind these algorithms lies the Top-K sparse eigenproblem, the computation of the largest…

Hardware Architecture · Computer Science 2022-01-20 Francesco Sgherzi , Alberto Parravicini , Marco Domenico Santambrogio

A previous study of MD algorithms designed for GPU use is extended to cover more recent developments in GPU architecture. Algorithm modifications are described, together with extensions to more complex systems. New measurements include the…

Computational Physics · Physics 2022-04-13 D C Rapaport

We report results of the performance test of GPUs obtained using the conjugate gradient (CG) algorithm for staggered fermions on the MILC fine lattice ($28^3 \times 96$). We use GPUs of nVIDIA GTX 295 model for the test. When we turn off…

High Energy Physics - Lattice · Physics 2010-10-29 Hyung-Jin Kim , Weonjong Lee

We implemented a GPU based parallel code to perform Monte Carlo simulations of the two dimensional q-state Potts model. The algorithm is based on a checkerboard update scheme and assigns independent random numbers generators to each thread.…

Statistical Mechanics · Physics 2012-03-12 Ezequiel E. Ferrero , Juan Pablo De Francesco , Nicolás Wolovick , Sergio A. Cannas