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Matrix languages, including MATLAB and Octave, are established standards for applications in science and engineering. They provide interactive programming environments that are easy to use due to their scripting languages with matrix data…

Programming Languages · Computer Science 2009-11-15 Raymes Khoury , Bernd Burgstaller , Bernhard Scholz

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

Intel Xeon Phi many-integrated-core (MIC) architectures usher in a new era of terascale integration. Among emerging killer applications, parallel graph processing has been a critical technique to analyze connected data. In this paper, we…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-26 Lei Jiang , Langshi Chen , Judy Qiu

The Intel Xeon Phi manycore processor is designed to provide high performance matrix computations of the type often performed in data analysis. Common data analysis environments include Matlab, GNU Octave, Julia, Python, and R. Achieving…

We explore the use of the Cell Broadband Engine (Cell/BE for short) for combinatorial optimization applications: we present a parallel version of a constraint-based local search algorithm that has been implemented on a multiprocessor…

Artificial Intelligence · Computer Science 2009-10-08 Salvator Abreu , Daniel Diaz , Philippe Codognet

Modern computer systems typically conbine multicore CPUs with accelerators like GPUs for inproved performance and energy efficiency. However, these sys- tems suffer from poor performance portability, code tuned for one device must be…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-05-23 Thomas L. Falch , Anne C. Elster

In this work, we make use of the OpenCL framework to accelerate an EMRI modeling application using the hardware accelerators -- Cell BE and Tesla CUDA GPU. We describe these compute technologies and our parallelization approach in detail,…

General Relativity and Quantum Cosmology · Physics 2011-10-05 Gaurav Khanna , Justin McKennon

We describe different optimization techniques to perform the assembly of finite element matrices in Matlab and Octave, from the standard approach to recent vectorized ones, without any low level language used. We finally obtain a simple and…

Numerical Analysis · Computer Science 2013-05-15 François Cuvelier , Caroline Japhet , Gilles Scarella

To overcome the well-known memory bottleneck of AI chips, 3D stacked architectures that employ advanced packaging technology with high-density through-silicon vias (TSVs) pins have proven to be a promising solution. The 3D-stacked AI chip…

Hardware Architecture · Computer Science 2026-04-30 Yiqi Liu , Noelle Crawford , Michael Wang , Jilong Xue , Jian Huang

Over recent years heterogeneous systems have become more prevalent across HPC systems, with over 100 supercomputers in the TOP500 incorporating GPUs or other accelerators. These hardware platforms have different performance characteristics…

Performance · Computer Science 2019-04-11 John Lawson , Mehdi Goli , Duncan McBain , Daniel Soutar , Louis Sugy

When considering different hardware platforms, not just the time-to-solution can be of importance but also the energy necessary to reach it. This is not only the case with battery powered and mobile devices but also with high-performance…

Performance · Computer Science 2020-06-30 Philip Heinisch , Katharina Ostaszewski , Hendrik Ranocha

Interconnection is crucial for computing systems. However, the current interconnection performance between processors and devices, such as memory devices and accelerators, significantly lags behind their computing performance, severely…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-02-21 Chen Chen , Xinkui Zhao , Guanjie Cheng , Yuesheng Xu , Shuiguang Deng , Jianwei Yin

This paper presents a comparison of OpenMP and OpenCL based on the parallel implementation of algorithms from various fields of computer applications. The focus of our study is on the performance of benchmark comparing OpenMP and OpenCL. We…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-11-12 Krishnahari Thouti , S. R. Sathe

The trend toward specialized processing devices such as TPUs, DPUs, GPUs, and FPGAs has exposed the weaknesses of PCIe in interconnecting these devices and their hosts. Several attempts have been proposed to improve, augment, or downright…

Databases · Computer Science 2024-09-04 Alberto Lerner , Gustavo Alonso

Dense linear algebra kernels are critical for wireless applications, and the oncoming proliferation of 5G only amplifies their importance. Many such matrix algorithms are inductive, and exhibit ample amounts of fine-grain ordered…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-05-16 Jian Weng , Vidushi Dadu , Tony Nowatzki

Automatic compiler phase selection/ordering has traditionally been focused on CPUs and, to a lesser extent, FPGAs. We present experiments regarding compiler phase ordering specialization of OpenCL kernels targeting a GPU. We use iterative…

Performance · Computer Science 2018-10-25 Ricardo Nobre , Luís Reis , João M. P. Cardoso

For reasons of both performance and energy efficiency, high-performance computing (HPC) hardware is becoming increasingly heterogeneous. The OpenCL framework supports portable programming across a wide range of computing devices and is…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-11-01 Beau Johnston , Josh Milthorpe

We evaluate the second-generation Intel Xeon Phi coprocessor based on the Intel Many Integrated Core (MIC) architecture, aka the Knights Landing or KNL, for simulating neutrino oscillations in (core-collapse) supernovae. For this purpose we…

Computational Physics · Physics 2019-12-24 Vahid Noormofidi , Susan R. Atlas , Huaiyu Duan

A current trend in HPC systems is the utilization of architectures with SIMD or vector extensions to exploit data parallelism. There are several ways to take advantage of such modern vector architectures, each with a different impact on the…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-11-05 Marc Blancafort , Roger Ferrer , Guillaume Houzeaux , Marta Garcia-Gasulla , Filippo Mantovani

The introduction of Intel(R) Xeon Phi(TM) coprocessors opened up new possibilities in development of highly parallel applications. The familiarity and flexibility of the architecture together with compiler support integrated into the Intel…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-11-26 Jiri Dokulil , Enes Bajrovic , Siegfried Benkner , Sabri Pllana , Martin Sandrieser , Beverly Bachmayer