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A model-driven approach for predicting and analysing the execution efficiency of multi-core processing

INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING 2017年第2期14卷 105-125页

作者： Hasan, Khondker S. Antonio, John K. Radhakrishnan, Sridhar UHCL Coll Sci & Engn Houston TX 77058 USA Univ Oklahoma Sch Comp Sci 210 W Boyd St Norman OK 73019 USA Univ Oklahoma Sch Comp Sci 110 W Boyd St Norman OK 73019 USA

Techniques for predicting the efficiency of multi-core processing associated with a set of tasks with varied CPU and main memory requirements are introduced. Prediction of CPU and memory availability is important in the context of making process assignment, load balancing, and scheduling decisions in distributed systems. Given a set of tasks each with varied CPU and main memory requirements, and a multi-core system (which generally has fewer cores than the number of tasks), we provide upper-and lower-bound models (formulas) for the efficiency with which the tasks are executed. In addition, a model for average CPU availability is introduced from the empirical study for applications that require a single predicted value instead of bounds. To facilitate scientific and controlled empirical evaluation, real-world benchmark programs with dynamic behaviour (CPU and memory requirements change in a short interval of time) are employed on UNIX systems that are parameterised by their CPU usage factor and memory requirement.

关键词： composite prediction model CPU availability concurrent threads memory model modelling and prediction multi-core processing performance evaluation

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The Application and Research of multi-core processing in Avionics System 10th

The Application and Research of Multi-core Processing in Avi...

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10th Chinese Society of Aeronautics and Astronautics Youth Forum, 2022

作者： Wentao, Zhan Wei, Niu Ji, Yuan Xiaobo, Wang Liu, Yang School of Civil Aviation Northwestern Polytechnical University Xi’an China Xi’an Aeronautics Computing Technique Research Institute Xi’an China

ISBN: (纸本)9789811976513

multi-core processing is widely used for its high performance, but in avionics system, there are some time behavior interferences caused by cache sharing and bus sharing etc. To address application aspects of multi-core processing in avionics system, this paper made tests and analyses, which showed that dual-core processor can get doubled performance in some specified situations. Gathering service experience of multi-core processing in less critical system is also a usable way towards critical system. Then this paper presents a scheduling configuration of SMP mode multi-core AVIC OS to meet the needs of mixed critical applications. This envisioned that multi-core processing will support the development of next-generation avionics systems. © 2023, Chinese Aeronautical Society.

关键词： Application mode multi-core processing Sharing interference

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Resolution of an inverse thermal problem using parallel processing on shared-memory multiprocessor architectures

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INVERSE PROBLEMS IN SCIENCE AND ENGINEERING 2015年第2期23卷 351-375页

作者： Ansoni, J. L. Brandi, A. C. Seleghim, P., Jr. Univ Sao Paulo Dept Mech Engn Engn Sch Sao Carlos Sao Carlos SP Brazil

Advances in multi-cores CPUs and in Graphics Processors Units (GPUs) are attracting a lot of attention of the scientific community due to their parallel processing power in conjunction with their low cost. In recent years the resolution of inverse thermal problems (ITP) is gaining increasing importance and attention in simulation-based applied science and engineering. However, the resolutions of these problems are very sensitive to random errors and the computer cost is high. In an attempt to improve the computational performance to solve an ITP, the computational power of multi-core architectures was used and analysed;mainly those offered by the GPU via Compute Unified Device Architecture (CUDA) and multi-cores CPUs via Pthreads. Also, we developed the implementation of the Preconditioned Conjugate Gradient method as a kernel on GPU to solve several sparse linear systems. Our CUDA and Pthreads-based systems are, respectively, two and four times faster than the serial version, while maintaining comparable convergence behaviour.

关键词： inverse thermal problem preconditioned conjugate gradient method parallel computation multi-core processing graphics processing units

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Optimization of Image processing Algorithms on Mobile Platforms

Optimization of Image Processing Algorithms on Mobile Platfo...

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Conference on Real-Time Image and Video processing 2011

作者： Poudel, Pramod Shirvaikar, Mukul Univ Texas Tyler Dept Elect Engn Tyler TX 75799 USA

ISBN: (纸本)9780819484086

This work presents a technique to optimize popular image processing algorithms on mobile platforms such as cell phones, net-books and personal digital assistants (PDAs). The increasing demand for video applications like context-aware computing on mobile embedded systems requires the use of computationally intensive image processing algorithms. The system engineer has a mandate to optimize them so as to meet real-time deadlines. A methodology to take advantage of the asymmetric dual-core processor, which includes an ARM and a DSP core supported by shared memory, is presented with implementation details. The target platform chosen is the popular OMAP 3530 processor for embedded media systems. It has an asymmetric dual-core architecture with an ARM Cortex-A8 and a TMS320C64x Digital Signal Processor (DSP). The development platform was the BeagleBoard with 256 MB of NAND RAM and 256 MB SDRAM memory. The basic image correlation algorithm is chosen for benchmarking as it finds widespread application for various template matching tasks such as face-recognition. The basic algorithm prototypes conform to OpenCV, a popular computer vision library. OpenCV algorithms can be easily ported to the ARM core which runs a popular operating system such as Linux or Windows CE. However, the DSP is architecturally more efficient at handling DFT algorithms. The algorithms are tested on a variety of images and performance results are presented measuring the speedup obtained due to dual-core implementation. A major advantage of this approach is that it allows the ARM processor to perform important real-time tasks, while the DSP addresses performance-hungry algorithms.

关键词： OMAP 3530 BeagleBoard OpenCV Image processing Computer vision Real-time systems multi-core processing

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The Design and Implementation of Remote Sensing Algorithms Visual Workflow Editing and processing Platform

The Design and Implementation of Remote Sensing Algorithms V...

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International Workshop on Information and Electronics Engineering (IWIEE) / International Conference on Information, Computing and Telecommunications (ICICT)

作者： Lai Jibao Lv Tianran Yu Tao Zheng Fengbin Li Jiaguo Meng Yuan Henan Univ Sch Comp & Informat Engn Kaifeng 475004 HeNan Peoples R China

The visual workflow operate-mode can greatly improve the programming efficiency. Visual workflow technology which is brought into the design of remote sensing algorithms can not only control the processing of remote sensing algorithms flexibly, but also greatly improve the reusability of remote sensing algorithms. The principle of remote sensing algorithms visualization lies in the decomposition of remote sensing algorithms. By means of packaging the decomposed algorithms and showing them visually, the algorithm can be processing more efficient. In addition, through the visual platform, the decomposed algorithms can be restructured into new algorithm flow which is composed by a certain number of refined algorithms. Therefore, the composed algorithm can be accelerated through the parallel processing method. Currently, multi-core processors programming is popular. multi-core processing has been becoming an emerging and high efficient computer technology. The platform will accelerate the processing of the algorithm flow further by using multi-core processing technology. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Harbin University of Science and Technology.

关键词： Visual Programming multi-core processing Parallel processing Schedule monitoring

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2D operators on topographic and non-topographic architectures-implementation, efficiency analysis, and architecture selection methodology

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INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS 2011年第10期39卷 983-1005页

作者： Zarandy, Akos Rekeczky, Csaba Hungarian Acad Sci Comp & Automat Res Inst Budapest Hungary Eutecus Inc Berkeley CA USA

Topographic and non-topographic image processing architectures and chips, developed within the CNN community recently, are analyzed and compared. It is achieved on a way that the 2D operators are collected to classes according to their implementation methods on the different architectures, and the main implementation parameters of the different operator classes are compared. Based on the results, an efficient architecture selection methodology is formalized. Copyright (C) 2010 John Wiley & Sons, Ltd.

关键词： multi-core processing image processing low power topographic processor arrays non-topographic processor arrays

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Efficient simulation and analysis of mid-sized networks

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COMPUTERS & INDUSTRIAL ENGINEERING 2018年 119卷 273-288页

作者： Castro, Luis E. Dong, Xu Shaikh, Nazrul, I Univ Miami Dept Ind Engn 283 McArthur Engn Bldg1251 Mem Dr Coral Gables FL 33146 USA

There is growing interest in developing the abilities to simulate realistic social networks and analyze data generated from existing online social networks such as Facebook and Twitter. Amongst other things, researchers and practitioners need these abilities to study how opinions and information diffuse over networks and identify the influential agents in networks. However, the sizes of the social networks that need to be simulated and the amount of user generated data that needs to be analyzed is growing at a faster rate than the computational power of most of the modern day computers. This paper presents a memory efficient network representation and computational resource allocation algorithm that yields a scale-up of about 400;thus, given a constraint on the availability of computational resources, researchers can now use the proposed algorithm to simulate and analyze networks that are more than 100 times larger than what they could simulate otherwise. The proposed network representation is conducive to multi-core processing and random node sampling. Algorithms for computationally efficient execution of three random-node-sampling-based methods to estimate network metrics such as the network diameter and average path length are also presented in the paper. These algorithms yield a speed-up of about 40 even when the researcher requires a precision of more than 98%. The scale-up and speed-up numbers are based on a detailed performance analysis of the proposed algorithms that was conducted on synthetic networks of sizes ranging from 1000 to 1,000,000 nodes. The observed scale-up and speed-up performance of the proposed algorithms has been validated against the algorithms used in igraph and statnet-two popular network data analysis software package, and these results are also presented in this paper.

关键词： Network simulation Computational efficiency Egocentric networks Vectorization multi-core processing Node sampling

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Modular Design and Optimization of Biomedical Applications for Ultralow Power Heterogeneous Platforms

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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 2020年第11期39卷 3821-3832页

作者： De Giovanni, Elisabetta Montagna, Fabio Denkinger, Benoit W. Machetti, Simone Peon-Quiros, Miguel Benatti, Simone Rossi, Davide Benini, Luca Atienza, David Ecole Polytech Fed Lausanne Embedded Syst Lab CH-1015 Lausanne Switzerland Univ Bologna Dept Comp Sci & Engn I-40126 Bologna Italy Univ Bologna Dept Elect Elect & Informat Engn I-40126 Bologna Italy Swiss Fed Inst Technol Integrated Syst Lab CH-8092 Zurich Switzerland

In the last years, remote health monitoring is becoming an essential branch of health care with the rapid development of wearable sensors technology. To meet the demand of new more complex applications and ensuring adequate battery lifetime, wearable sensors have evolved into multicore systems with advanced power-saving capabilities and additional heterogeneous components. In this article, we present an approach that applies optimization and parallelization techniques uncovered by modern ultralow power (ULP) platforms in the SW layers with the goal of improving the mapping and reducing the energy consumption of biomedical applications. Additionally, we investigate the benefit of integrating domain-specific accelerators to further reduce the energy consumption of the most computationally expensive kernels. Using 30-s excerpts of signals from two public databases, we apply the proposed optimization techniques on well-known modules of biomedical benchmarks from the state-of-the-art and two complete applications. We observe speed-ups of 5.17x and energy savings of 41.6% for the multicore implementation using a cluster of 8 cores with respect to single-core wearable sensor designs when processing a standard 12-lead electrocardiogram (ECG) signal analysis. Additionally, we conclude that the minimum workload required to take advantage of parallelization for a heartbeat classifier corresponds to the processing of 3-lead ECG signals, with a speed-up of 2.96x and energy savings of 19.3%. Moreover, we observe additional energy savings of up to 7.75% and 16.8% by applying power management and memory scaling to the multicore implementation of the 3-lead beat classifier and 12-lead ECG analysis, respectively. Finally, by integrating hardware (HW) acceleration we observe overall energy savings of up to 51.3% for the 12-lead ECG analysis.

关键词： Accelerator architectures biomedical monitoring edge computing memory management multi-core processing wearable sensors

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Computing Optimised Parallel Speeded-Up Robust Features (P-SURF) on multi-core Processors

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INTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING 2010年第2期38卷 138-158页

作者： Zhang, Nan Xian Jiaotong Liverpool Univ Dept Comp Sci & Software Engn Suzhou Peoples R China

This article presents a novel CPU-based parallel algorithm (P-SURF) that computes the Speeded-Up Robust Features (SURF), a local descriptor that is able to find point correspondences between images in spite of scaling and rotation. The algorithm presented here parallelises all the seven major steps found in the original serial computation. The task in each of the steps is decomposed and the fractions are assigned to running threads bound onto distinctive processors. The implementation of the algorithm was tested using randomly selected images in regard to performance, scalability and stability. The results showed that its performance on mid-level Intel core Duo processors was comparable to that of some fast GPU-based SURF implementations. For example, on a testing system equipped with an Intel core Duo P8600 at 2.4 GHz, P-SURF was able to extract and represent features from a 640 x 480 image at a rate of 33 frames per second. The experimental results also revealed that, instead of leaving the threads to the kernel for processor assignment, assigning hard processor affinity by the algorithm produced better performance and stability.

关键词： Parallel computing multi-threaded programming multi-core processing Image feature extraction Image local descriptor

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A GPU domain decomposition solution for spectral stochastic finite element method

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COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2017年 327卷 392-410页

作者： Stavroulakis, G. Giovanis, D. G. Papadopoulos, V. Papadrakakis, M. Natl Tech Univ Athens Inst Struct Anal & Antiseism Res Athens Greece

In intrusive methods for the stochastic analysis of engineering systems, the solution of the stochastic partial differential equations leads to an augmented algebraic system of equations, with respect to the corresponding deterministic problem. The solution of this augmented system can become quite challenging or even impossible due to the increased computational resources and effort required, especially in large-scale problems with large parameter variability. Recent developments in computer hardware regarding graphics processing units (GPU)-accelerated computing have been proven very promising due to their advanced capabilities and have been used in a number of scientific fields in order to enhance the solution of computationally high demanding problems. In this work, the benefits achieved with the exploitation of the GPU capabilities are demonstrated, in addressing intrusive stochastic mechanics problems where the solution of the resulting finite element algebraic equations is performed with the dual domain decomposition method, implementing specifically tailored preconditioners. The results show a significant enhancement of the spectral stochastic finite element method in terms of computational performance as well as of the consumed energy efficiency when applying the proposed methodology. (C) 2017 Published by Elsevier B.V.

关键词： Spectral stochastic finite element method multi-core processing Graphics processing units Domain decomposition methods

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