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Architecture-Aware Mapping and Optimization on a 1600-Core GPU

Architecture-Aware Mapping and Optimization on a 1600-Core G...

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International conference on parallel and distributed Systems (ICPADS)

作者： Mayank Daga Thomas Scogland Wu-chun Feng Department of Computer Science Virginia Tech USA USA

The graphics processing unit (GPU) continues to make in-roads as a computational accelerator for high-performance computing (HPC). However, despite its increasing popularity, mapping and optimizing GPU code remains a difficult task, it is a multi-dimensional problem that requires deep technical knowledge of GPU architecture. Although substantial literature exists on how to map and optimize GPU performance on the more mature NVIDIA CUDA architecture, the converse is true for OpenCL on an AMD GPU, such as the 1600-core AMD Radeon HD 5870 GPU. Consequently, we present and evaluate architecture-aware mapping and optimizations for the AMD GPU. The most prominent of which include (i) explicit use of registers, (ii) use of vector types, (iii) removal of branches, and (iv) use of image memory for global data. We demonstrate the efficacy of our AMD GPU mapping and optimizations by applying each in isolation as well as in concert to a large-scale, molecular modeling application called GEM. Via these AMD-specific GPU optimizations, our optimized OpenCL implementation on an AMD Radeon HD 5870 delivers more than a four-fold improvement in performance over the basic OpenCL implementation. In addition, it outperforms our optimized CUDA version on an NVIDIA GTX280 by 12%. Overall, we achieve a speedup of 371-fold over a serial but hand-tuned SSE version of our molecular modeling application, and in turn, a 46-fold speedup over an ideal scaling on an 8-core CPU.

关键词： Graphics processing unit Optimization Kernel Instruction sets Computer architecture Vectors Registers

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parallel biomedical image processing with GPGPUs in cancer research

Parallel biomedical image processing with GPGPUs in cancer r...

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International Symposium on Logistics and Industrial Informatics, LINDI

作者： Attila Reményi Sándor Szénási István Bándi Zoltán Vámossy Gábor Valcz Pál Bogdanov Szabolcs Sergyán Miklos Kozlovszky John von Neumann Faculty of Informatics Óbuda University Budapest Hungary 2nd Department of Internal Medicine Semmelweiss University Budapest Hungary Laboratory of Parallel and Distributed Computing MTA SZTAKI Budapest Hungary

The main aim of this work is to show, how GPGPUs can facilitate certain type of image processing methods. The software used in this paper is used to detect special tissue part, the nuclei on (HE - hematoxilin eosin) stained colon tissue sample images. Since pathologists are working with large number of high resolution images - thus require significant storage space -, one feasible way to achieve reasonable processing time is the usage of GPGPUs. The CUDA software development kit was used to develop processing algorithms to NVIDIA type GPUs. Our work focuses on how to achieve better performance with coalesced global memory access when working with three-channel RGB tissue images, and how to use the on-die shared memory efficiently.

关键词： Graphics processing unit Instruction sets image processing Memory management Optimization Kernel Colon

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C++ Compiler Supports for Embedded Multicore DSP Systems

C++ Compiler Supports for Embedded Multicore DSP Systems

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International conference on parallel processing Workshops (ICPPW)

作者： Chi-Bang Kuan Jia-Jhe Li Chung-Kai Chen Jenq Kuen Lee Department of Computer Science National Tsing Hua University Taiwan Realtek Semiconductor Corporation Hsinchu Taiwan

The development of embedded systems has moved toward multicore in recent years. As processor numbers continue growing in embedded multicore systems, how to provide efficient programming models and tailored compiler supports becomes a critical issue in developing embedded multicore applications. Though C still dominates embedded computing so far, C++ is gaining importance and popularity in DSP systems for its power and flexibility. In addition, current C++ compilers are able to produce efficient and compact code as C compilers. This increases the practical use of C++ technologies in embedded systems. In this paper, we address issues in supporting C++ compilers and present methods to leverage C++ in embedded multicore computing. Since embedded systems are usually limited by tight resource, code size issues are addressed when supporting C++ libraries. Code size of standard C++ library is analyzed and a library layering technique is provided to guide reasonable library use in embedded applications. Our methods to leverage C++ include enhancing programming models with high-level abstraction and incorporating the programming models with parallel patterns to simplify program parallelization. In our experiments, PAC multi-DSP systems, composed of one MPU and two VLIW DSPs, are used to evaluate the proposed methods. parallelization results on stereo-vision and image-blurring applications are presented with key components of the systems, including SIMD and DMAs, incorporated to pursue maximal performance. The result shows our approaches with C++ compilers can deliver performance improvements of 61% and 174% for the stereo-vision and image-blurring applications, respectively.

关键词： Libraries Multicore processing Digital signal processing Programming Servers Computational modeling Object oriented modeling

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Modeling Unconnectable Peers in Private BitTorrent Communities

Modeling Unconnectable Peers in Private BitTorrent Communiti...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Kornel Csernai Mark Jelasity Johan Pouwelse Tamas Vinko Department of Informatics University of Szeged Hungary Department of Computer Science Delft University of Technnology Netherlands

In a typical BitTorrent swarm, a large proportion of the peers are behind firewalls or NATs. These peers are called unconnectable. When developing P2P applications, a main requirement is to handle unconnectable peers appropriately. One important aspect of this problem, which has not been emphasized so far, is understanding the difference between the attributes of unconnectable peers and peers in the open Internet. For example, if unconnectable peers spend much less time online, or if they download significantly more, exploiting these facts helps to optimize the implementation, and ignoring these facts can even lead to severe performance problems. Comparing open and unconnectable peers is not easy because most traces contain no information about connect ability. Here we study two large traces collected in two private BitTorrent communities: *** and ***, both of which contain the connect ability attribute. From these traces we extract several attributes of individual online sessions, swarms, and users. We compare the distributions of these attributes over unconnectable and open peers. We find that there are some potentially important differences, e.g., unconnectable users tend to have a lot more sessions, and they tend to spend slightly more time online. Some of our findings are in contradiction with previous results that were based on a different trace collection methodology.

关键词： Databases Cleaning Communities Peer to peer computing Protocols Approximation methods HTML

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Multi-GPU Compositeless parallel Rendering Algorithm

Multi-GPU Compositeless Parallel Rendering Algorithm

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IEEE International conference on Computer-Aided Design and Computer Graphics

作者： Pan Wang Huahai Liu Sikun Li Liang Zeng Xun Cai

Due to its high performance/cost ratio, a single PC equipped with multi-GPU is an attractive platform for large scale scene rendering and visualization. In this paper, we present a compositeless parallel rendering algorithm on shared memory multi-GPU system. Our algorithm is based on hybrid sort-first and sort-last render mode. By utilizing the DMA asynchronous transfer in modern video cards, we implement asynchronous image read back and implicit image compositing. Using the compositeless algorithm, we totally remove image compositing stage in parallel rendering contrasting with the traditional parallel rendering methods. The theoretical analysis and experiments demonstrate that our algorithm is practical and scalable for large scale scene rendering and high-resolution display.

关键词： Rendering (computer graphics) Graphics processing unit Tiles Algorithm design and analysis Scalability Layout

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A Naive-Bayesian Methodology to Classify Echo Cardiographic images through SQL

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5th International conference on Knowledge, Information, and Creativity Support Systems

作者： Nandagopalan, S. Adiga, B. S. Sudarshan, T. S. B. Dhanalakshmi, C. Manjunath, C. N. Amrita Sch Engn Dept Comp Sci Si Engn Amrita Vishwa Vidyapeetham Bangalore Karnataka India Tata Consult Serv Parallel Comp Div Bangalore Karnataka India Amrita Sch Engn Dept Comp Sci & Engn Amrita Vishwa Vidyapeetham Bangalore Karnataka India Sri Jayadeva Inst Cardiovasc Sci & Res Dept Echocardiog Bangalore Karnataka India Sri Jayadeva Inst Cardiovasc Sci & Res Bangalore Karnataka India

ISBN: (纸本)9783642247873

Generally patient data in healthcare environments exist in relational databases. Classification of echocardiographic images is an important data mining task that helps hospitals without transferring the data in any form. This paper proposes a novel method to accomplish this task using naive Bayesian model via SQL. The proposed method has two phases. The first phase builds a knowledge base using many normal and abnormal subjects and the second phase uses this knowledge to categorize an unseen subject into appropriate class. The image features such as cardiac chamber dimensions (specifically Left Ventricle - LV), Ejection Fraction, Mitral valve (MV) orifice area, etc., are computed by first segmenting the image by employing advanced image processing techniques. For instance, to segment echo images we employ an efficient SQL based Fast K-Means algorithm combined with a greedy active contour algorithm for accurate boundary detection. Additional features such as textural, statistical, and histogram are computed and added to the classifier model by analyzing color Doppler echo images to strengthen the classifier accuracy. Our SQL based naive Bayesian classifier model is built with 7 schema, simple yet efficient SQL queries and thus providing an accurate classification of patients as normal or abnormal. The model is trained with 112 patient data and we believe that the clinical decision is simplified and can happen on-the-fly. Experimental results presented in this paper show an increased accuracy of 87.48% against the other state-of-the art segmentation and classification methods reported.

关键词： Echocardiographic image Naive-Bayseian Classification K-Means Segmentation SQL Active Contour

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parallel Outlier Detection Using KD-Tree Based on MapReduce

Parallel Outlier Detection Using KD-Tree Based on MapReduce

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IEEE International conference on Cloud Computing Technology and Science (CloudCom)

作者： Qing He Yunlong Ma Qun Wang Fuzhen Zhuang Zhongzhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing China Chinese Academy of Sciences Beijing China

distributed and parallel algorithms have attracted a vast amount of interest and research in recent decades, to handle large-scale data set in real-world applications. In this paper, we focus on a parallel implementation of KD-Tree based outlier detection method to deal with large-scale data set. As one of the state-of-the-art outlier detection methods, KD-Tree based has been approved to be an effective algorithm. However, it still cannot process large-scale data set efficiently due to its serial implementation. Based on the current and powerful parallel programming framework -- MapReduce, we propose to implement the parallel KD-Tree based outlier detection algorithm (e.g., PKDTree for short). Experimental results demonstrate the efficiency of PKDTree according to the evaluation criterions of scale up, speedup and size up.

关键词： Smoothing methods parallel algorithms Computers Arrays Detection algorithms Algorithm design and analysis Runtime

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distributed TARGET DETECTION IN CENTRALIZED WIRELESS SENSOR NETWORKS WITH COMMUNICATION CONSTRAINTS

DISTRIBUTED TARGET DETECTION IN CENTRALIZED WIRELESS SENSOR ...

引用

European Signal processing conference

作者： Jose Luis Barbosa David Luengo EXPAL S.A. Dpto. de Teoria de la Senal y Comunicaciones Universidad Carlos III de Madrid

distributed inference is an important and challenging problem in wireless sensor networks (WSNs). In this paper we consider distributed detection of a target in centralized WSNs (i.e. WSNs with a fusion centre) subject to communication constraints. We focus on the parallel network topology, where the sensors can only exchange information with the fusion centre, and consider conditionally dependent observations. We develop two types of local decision rules for the sensors (binary and binary with abstention), based on the Neyman-Pearson criterion, and a fusion rule based on a support vector machine (SVM). Under these circumstances we show empirically that, even when individual sensors with very poor performance are used, both local configurations are able to provide very good detection rates as the number of nodes increases.

关键词： Wireless sensor networks Support vector machines Sensor fusion Noise Training Approximation methods

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Combined compressed sensing and parallel mri compared for uniform and random cartesian undersampling of K-space

Combined compressed sensing and parallel mri compared for un...

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International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Daniel S. Weller Jonathan R. Polimeni Leo Grady Lawrence L. Wald Elfar Adalsteinsson Vivek K Goyal Department of EECS Massachusetts Institute of Technology Cambridge MA USA Department of Radiology Harvard Medical School Boston MA USA A. A. Martinos Center Department of Radiology Massachusetts General Hospital Charlestown MA USA Department of Image Analytics and Informatics Siemens AG Corporate Research and Development Princeton NJ USA

Both compressed sensing (CS) and parallel imaging effectively reconstruct magnetic resonance images from undersampled data. Combining both methods enables imaging with greater undersampling than accomplished previously. This paper investigates the choice of a suitable sampling pattern to accommodate both CS and parallel imaging. A combined method named SpRING is described and extended to handle random undersampling, and both GRAPPA and SpRING are evaluated for uniform and random undersampling using both simulated and real data. For the simulated data, when the undersampling factor is large, SpRING performs better with random undersampling. However, random undersampling is not as beneficial to SpRING for real data with approximate sparsity.

关键词： Coils Springs Kernel image reconstruction Noise Imaging Compressed sensing

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Multivariate texture retrieval using the geodesic distance between elliptically distributed random variables

Multivariate texture retrieval using the geodesic distance b...

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IEEE International conference on image processing

作者： Lionel Bombrun Yannick Berthoumieu Nour-Eddine Lasmar Geert Verdoolaege Laboratoire IMS UMR 5218 Groupe Signal et Image 351 cours de la libération Université de Bordeaux 1 Talence France Department of Applied Physics Ghent University Belgium

This paper presents a new texture retrieval algorithm based on elliptical distributions for the modeling of wavelet sub- bands. For measuring similarity between two texture images, the geodesic distance (GD) is considered. A closed form for fixed shape parameters and an approximation when assuming the geodesic coordinate functions as straight lines are given. Taken into various elliptical choices, the multivariate Laplace and G 0 distributions are introduced for modeling respectively the color cue and spatial dependencies of the wavelet coefficients. A multi-model classification approach is then proposed to combine the similarity measures. A comparative study between some multivariate models on the VisTex image database is conducted and reveals that the combination of the multivariate Laplace modeling for the color dependency and the multivariate G 0 modeling for spatial one achieves higher recognition rates than other approaches.

关键词： image color analysis Shape Vectors Covariance matrix conferences Approximation methods

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