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Related papers: Performance Engineering for a Medical Imaging Appl…

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With the ease-of-programming, flexibility and yet efficiency, MapReduce has become one of the most popular frameworks for building big-data applications. MapReduce was originally designed for distributed-computing, and has been extended to…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-09-03 Mian Lu , Lei Zhang , Huynh Phung Huynh , Zhongliang Ong , Yun Liang , Bingsheng He , Rick Siow Mong Goh , Richard Huynh

With the increasing size and complexity of data produced by large scale numerical simulations, it is of primary importance for scientists to be able to exploit all available hardware in heterogenous High Performance Computing environments…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-06-15 Timothy Dykes , Claudio Gheller , Marzia Rivi , Mel Krokos

We carry out a comparative performance study of multi-core CPUs, GPUs and Intel Xeon Phi (Many Integrated Core - MIC) with a microscopy image analysis application. We experimentally evaluate the performance of computing devices on core…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-05-15 George Teodoro , Tahsin Kurc , Guilherme Andrade , Jun Kong , Renato Ferreira , Joel Saltz

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

We investigate and characterize the performance of an important class of operations on GPUs and Many Integrated Core (MIC) architectures. Our work is motivated by applications that analyze low-dimensional spatial datasets captured by high…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-11-05 George Teodoro , Tahsin Kurc , Jun Kong , Lee Cooper , Joel Saltz

With at least 50 cores, Intel Xeon Phi is a true many-core architecture. Featuring fairly powerful cores, two cache levels, and very fast interconnections, the Xeon Phi can get a theoretical peak of 1000 GFLOPs and over 240 GB/s. These…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-12-23 Jianbin Fang , Ana Lucia Varbanescu , Henk Sips , Lilun Zhang , Yonggang Che , Chuanfu Xu

Intel Xeon Phi is a recently released high-performance coprocessor which features 61 cores each supporting 4 hardware threads with 512-bit wide SIMD registers achieving a peak theoretical performance of 1Tflop/s in double precision. Many…

Performance · Computer Science 2013-02-06 Erik Saule , Kamer Kaya , Umit V. Catalyurek

In the push for exascale computing, energy efficiency is of utmost concern. System architectures often adopt accelerators to hasten application execution at the cost of power. The Intel Xeon Phi co-processor is unique accelerator that…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-05-26 Gary Lawson , Masha Sosonkina , Yuzhong Shen

In 2013 Intel introduced the Xeon Phi, a new parallel co-processor board. The Xeon Phi is a cache-coherent many-core shared memory architecture claiming CPU-like versatility, programmability, high performance, and power efficiency. The…

Performance · Computer Science 2014-11-10 S. Ali Mirsoleimani , Aske Plaat , Jos Vermaseren , Jaap van den Herik

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

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

Many-core accelerators, as represented by the XeonPhi coprocessors and GPGPUs, allow software to exploit spatial and temporal sharing of computing resources to improve the overall system performance. To unlock this performance potential…

Performance · Computer Science 2018-02-09 Peng Zhang , Jianbin Fang , Tao Tang , Canqun Yang , Zheng Wang

This work describes the challenges presented by porting parts ofthe Gysela code to the Intel Xeon Phi coprocessor, as well as techniques used for optimization, vectorization and tuning that can be applied to other applications. We evaluate…

Computational Physics · Physics 2015-08-04 G. Latu , M. Haefele , J. Bigot , V. Grandgirard , T. Cartier-Michaud , F. Rozar

The efficient execution of image processing algorithms is an active area of Bioinformatics. In image processing, one of the classes of algorithms or computing pattern that works with irregular data structures is the Irregular Wavefront…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-05-04 Jeremias Gomes , George Teodoro

The paper presents investigations on the implementation and performance of the finite element numerical integration algorithm for first order approximations and three processor architectures, popular in scientific computing, classical CPU,…

Mathematical Software · Computer Science 2016-05-25 Krzysztof Banaś , Filip Krużel , Jan Bielański

Many complex problems, such as natural language processing or visual object detection, are solved using deep learning. However, efficient training of complex deep convolutional neural networks for large data sets is computationally…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-06-06 Andre Viebke , Sabri Pllana , Suejb Memeti , Joanna Kolodziej

With the rapidly growing demand for computing power new accelerator based architectures have entered the world of high performance computing since around 5 years. In particular GPGPUs have recently become very popular, however programming…

Performance · Computer Science 2013-08-16 Volker Weinberg , Momme Allalen

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…

This paper concerns development of a high-performance implementation of the Particle-in-Cell method for plasma simulation on Intel Xeon Phi coprocessors. We discuss suitability of the method for Xeon Phi architecture and present our…

Computational Physics · Physics 2016-08-05 I. A. Surmin , S. I. Bastrakov , E. S. Efimenko , A. A. Gonoskov , A. V. Korzhimanov , I. B. Meyerov
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