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Driven by artificial intelligence, data science, and high-resolution simulations, I/O workloads and hardware on high-performance computing (HPC) systems have become increasingly complex. This complexity can lead to large I/O overheads and…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-01-03 Hammad Ather , Jean Luca Bez , Chen Wang , Hank Childs , Allen D. Malony , Suren Byna

Computed Tomography (CT) is a key 3D imaging technology that fundamentally relies on the compute-intense back-projection operation to generate 3D volumes. GPUs are typically used for back-projection in production CT devices. However, with…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-04-28 Peng Chen , Mohamed Wahib , Xiao Wang , Shinichiro Takizawa , Takahiro Hirofuchi , Hirotaka Ogawa , Satoshi Matsuoka

Subverting the flow of instructions (e.g., by use of code-reuse attacks) still poses a serious threat to the security of today's systems. Various control flow integrity (CFI) schemes have been proposed as a powerful technique to detect and…

Hardware Architecture · Computer Science 2021-03-09 Mario Telesklav , Stefan Tauner

Image convolution is widely used for sharpening, blurring and edge detection. In this paper, we review two common algorithms for convolving a 2D image by a separable kernel (filter). After optimising the naive codes using loop unrolling and…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-28 Ashkan Tousimojarad , Wim Vanderbauwhede , W Paul Cockshott

Computing on encrypted data is a promising approach to reduce data security and privacy risks, with homomorphic encryption serving as a facilitator in achieving this goal. In this work, we accelerate homomorphic operations using the…

Cryptography and Security · Computer Science 2023-10-04 Harshita Gupta , Mayank Kabra , Juan Gómez-Luna , Konstantinos Kanellopoulos , Onur Mutlu

This paper investigates the multi-GPU performance of a 3D buoyancy driven cavity solver using MPI and OpenACC directives on different platforms. The paper shows that decomposing the total problem in different dimensions affects the strong…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-06-10 Weicheng Xue , Christopher J. Roy

Asynchronous tasks, when created with over-decomposition, enable automatic computation-communication overlap which can substantially improve performance and scalability. This is not only applicable to traditional CPU-based systems, but also…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-03-23 Jaemin Choi , David F. Richards , Laxmikant V. Kale

B-spline based orbital representations are widely used in Quantum Monte Carlo (QMC) simulations of solids, historically taking as much as 50% of the total run time. Random accesses to a large four-dimensional array make it challenging to…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-08-10 Amrita Mathuriya , Ye Luo , Anouar Benali , Luke Shulenburger , Jeongnim Kim

In many Multimedia content analytics frameworks feature likelihood maps represented as histograms play a critical role in the overall algorithm. Integral histograms provide an efficient computational framework for extracting multi-scale…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-07 Mahdieh Poostchi , Kannappan Palaniappan , Da Li , Michela Becchi , Filiz Bunyak , Guna Seetharaman

Limits on power dissipation have pushed CPUs to grow in parallel processing capabilities rather than clock rate, leading to the rise of "manycore" or GPU-like processors. In order to achieve the best performance, applications must be able…

On modern architectures, the performance of 32-bit operations is often at least twice as fast as the performance of 64-bit operations. By using a combination of 32-bit and 64-bit floating point arithmetic, the performance of many dense and…

Mathematical Software · Computer Science 2015-05-13 Marc Baboulin , Alfredo Buttari , Jack Dongarra , Jakub Kurzak , Julie Langou , Julien Langou , Piotr Luszczek , Stanimire Tomov

Large-scale parallel numerical simulations are essential for a wide range of engineering problems that involve complex, coupled physical processes interacting across a broad range of spatial and temporal scales. The data structures involved…

Mathematical Software · Computer Science 2018-10-11 Fande Kong , Roy H. Stogner , Derek R. Gaston , John W. Peterson , Cody J. Permann , Andrew E. Slaughter , Richard C. Martineau

This paper is focused on improving multi-GPU performance of a research CFD code on structured grids. MPI and OpenACC directives are used to scale the code up to 16 GPUs. This paper shows that using 16 P100 GPUs and 16 V100 GPUs can be…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-06-10 Weicheng Xue , Charles W. Jackson , Christoper J. Roy

We provide a preliminary study on utilizing GPU (Graphics Processing Unit) to accelerate computation for three simulation optimization tasks with either first-order or second-order algorithms. Compared to the implementation using only CPU…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-04-19 Jinghai He , Haoyu Liu , Yuhang Wu , Zeyu Zheng , Tingyu Zhu

There are two distinct approaches to speeding up large parallel computers. The older method is the General Purpose Graphics Processing Units (GPGPU). The newer is the Many Integrated Core (MIC) technology . Here we attempt to focus on the…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-18 Janusz Kowalik , Piotr Arłukowicz , Erika Parsons

Many popular machine learning models scale poorly when deployed on CPUs. In this paper we explore the reasons why and propose a simple, yet effective approach based on the well-known Divide-and-Conquer Principle to tackle this problem of…

Machine Learning · Computer Science 2023-03-03 Alex Kogan

In this paper we implemented the algorithm we developed in [1] called 3DPIFCM in a parallel environment by using CUDA on a GPU. In our previous work we introduced 3DPIFCM which performs segmentation of images in noisy conditions and uses…

Computer Vision and Pattern Recognition · Computer Science 2020-02-07 Arie Agranonik , Maya Herman , Mark Last

Multiple applications executing concurrently on a multicore system interfere with each other at different shared resources such as main memory and shared caches. Such inter-application interference, if uncontrolled, results in high system…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-08-14 Lavanya Subramanian

Searching for sources of electromagnetic emission in spectral-line radio astronomy interferometric data is a computationally intensive process. Parallel programming techniques and High Performance Computing hardware may be used to improve…

Instrumentation and Methods for Astrophysics · Physics 2015-07-20 Stefan Westerlund , Christopher Harris

To define and identify a region-of-interest (ROI) in a digital image, the shape descriptor of the ROI has to be described in terms of its boundary characteristics. To address the generic issues of contour tracking, the yConvex Hypergraph…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-07-10 Saurabh Jha , Tejaswi Agarwal , B. Rajesh Kanna
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