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GPU based implementation of 3DTV system

GPU based implementation of 3DTV system

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international conference on Image and Graphics

作者： Wang, Liang-Hao Zhang, Jing Yao, Shao-Jun Li, Dong-Xiao Zhang, Ming Institute of Information and Communication Engineering Zhejiang University Hangzhou 310027 China Zhejiang Provincial Key Laboratory of Information Network Technology Hangzhou 310027 China

ISBN: (纸本)9780769545417

this paper focuses on the near real-time implementation of end-to-end 3DTV System. It is specially designed for the generation of high-quality disparity map and depth-image-based rendering (DIBR) on the graphics processing unit (GPU) through CUDA (Compute Unified Device Architecture) API. We propose our novel methods including a kind of stereo matching with adaptive windows and an asymmetric edge adaptive filter (AEAF) for industrial application. these algorithms are structured in a way that exposes as much data parallelism as possible and the power of shared memory and data parallel programming in GPU is exploited. We evaluate our proposed methods and implementation based on the benchmark Middlebury and the experiment results show that our method is suitable for application on the trade-off among accuracy and execution speed. Running on an NVIDIA Quadro FX4800 graphics card, for each 480x375 stereo images with 60 disparity levels, the proposed system reaches about 146ms for stereo matching and reaches the speed of DIBR 5.7ms for rendering 1 view or 14ms for rendering 8 views. © 2011 IEEE.

关键词： Graphics processing unit

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Optimize or Wait? Using llc Fast-Prototyping Tool to Evaluate CUDA Optimizations

Optimize or Wait? Using llc Fast-Prototyping Tool to Evaluat...

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Euromicro conference on parallel, Distributed and Network-Based processing

作者： Ruyman Reyes Francisco de Sande Department de EIO y Computación Universidad de La Laguna La Laguna Spain

Over the last few years, we have witnessed the proliferation of GPU devices on HPC environments. Manufacturers produce new versions of their devices every few years, though, posing a new problem for scientists and engineers using their technology: is it worth the time and effort spent optimizing the codes for the current version? Or it is better to wait until a new architecture appears? In this paper, we present a comparison of various CUDA versions, in order to compare their architectures, and optimize codes for each version. this work would require a tremendous coding effort if done manually. However, using fast prototyping tools, like llCoMP, this is an effortless process. Applying loop optimization techniques, we evaluate three different algorithms. With each one, we apply a set of optimization techniques, showing the performance benefit or penalty, in three CUDA architecture versions, including Fermi. the results of these techniques will guide developers on the right path towards efficient code optimization. Preliminary results show that some optimizations recommended for older CUDA architectures may not be useful in Fermi.

关键词： Graphics processing unit Computer architecture Optimization Kernel Performance evaluation Computational modeling Instruction sets

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theoretical analysis of parallel combinatory spread-spectrum communication system for optical wireless communications

Theoretical analysis of parallel combinatory spread-spectrum...

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international conference on Information, Communications and Signal processing

作者： Yusuke Kozawa Hiromasa Habuchi Graduate School of Science and Engineering Ibaraki University Hitachi Japan Department of Computer and Information Science Faculty of Engineering Ibaraki University Hitachi Japan

ISBN: (纸本)9781457700293

In this paper, an N-CSK (N parallel Codes Shift Keying) using modified pseudo orthogonal M-sequence sets (MPOMS) for applying the parallel combinatory spread-spectrum (PC/SS) communication system to the optical communication is presented. Moreover, the bit error rate (BER) performance and the data transmission rate of the proposed system are evaluated through theoretical analysis by taking into account the scintillation, background-noise, avalanche photodiode (APD) noise, thermal noise, and signal dependence noise. Also, the performance comparison between the proposed system and the conventional systems (OOK/CDM, SIK/CDM, and N-CSK/CDM) are presented. Consequently, the proposed system can realize high data rate optical wireless communication because the data transmission rate of the proposed system is better than those of the conventional systems, and can achieve more than 1.0 [bit/chip].

关键词： Optical transmitters Data communication Bit error rate Wireless communication Noise Integrated optics Optical receivers

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Spread spectrum for chaotic compressed sensing techniques in parallel magnetic resonance imaging

Spread spectrum for chaotic compressed sensing techniques in...

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international conference on Information, Communications and Signal processing

作者： Tran Duc Tan Le Vu-Ha Nguyen Linh Trung University of Engineering and Technology Vietnam National University Hanoi Vietnam

ISBN: (纸本)9781457700293

We consider the fast acquisition problem in magnetic resonance imaging (MRI). Often, fast acquisition is achieved using parallel imaging (pMRI) techniques. It has been shown recently that compressed sensing (CS), which enables exact reconstruction of sparse or compressible signals from a small number of random measurements, can accelerate the speed of MRI acquisition because the number of measurements was small. Recently, the spread spectrum (SS) has been utilized to enhance the quality of reconstructed CS image. Also recently, chaotic CS approach potentially offers simpler hardware implementation. In this paper, we combine chaotic CS and spread spectrum technique in order to obtain a fast acquisition in MRI with enhanced quality of reconstructed image. the performance of the proposed method is analyzed using numerical simulation.

关键词： Magnetic resonance imaging Image reconstruction Coils Compressed sensing Chaos Sensitivity

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High Performance Matrix Inversion on a Multi-core Platform with Several GPUs

High Performance Matrix Inversion on a Multi-core Platform w...

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Euromicro conference on parallel, Distributed and Network-Based processing

作者： Pablo Ezzatti Enrique S. Quintana-Ortí Alfredo Remon Centro de Cálculo Universidad de la República Montevideo Uruguay Uruguay Depto. de Ingeniería y Universidad Jaume I Castellón Spain

Inversion of large-scale matrices appears in a few scientific applications like model reduction or optimal control. Matrix inversion requires an important computational effort and, therefore, the application of high performance computing techniques and architectures for matrices with dimension in the order of thousands. Following the recent uprise of graphics processors (GPUs), we present and evaluate high performance codes for matrix inversion, based on Gauss-Jordan elimination with partial pivoting, which off-load the main computational kernels to one or more GPUs while performing fine-grain operations on the general-purpose processor. the target architecture consists of a multi-core processor connected to several GPUs. parallelism is extracted from parallel implementations of BLAS and from the concurrent execution of operations in the available computational units. Numerical experiments on a system with two Intel QuadCore processors and four NVIDIA cl060 GPUs illustrate the efficiency and the scalability of the different implementations, which deliver over 1.2 x 10 12 floating point operations per second.

关键词： Graphics processing unit Multicore processing Partitioning algorithms parallel processing Electronic mail

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A nested superdirective generalized sidelobe canceller for speech enhancement

A nested superdirective generalized sidelobe canceller for s...

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international conference on Information, Communications and Signal processing

作者： Parinaz Khayeri Hamid Reza Abutalebi Vahid Abootalebi Speech Processing Research Laboratory Electrical and Computer Engineering Department Yazd University Yazd Iran Electrical and Computer Engineering Department Yazd University Yazd Iran

this paper deals with the problem of microphone array speech enhancement using a hybrid Generalized Sidelobe Canceller (GSC) and Super-Directive Beamformer (SDB). While GSC is one of the most practical architectures for reducing the directional noises, SDB is a superior choice in the case of diffuse noise fields. In this research, we have combined these two structures to improve the performance of speech enhancement system in realistic noisy conditions. Furthermore, we have employed a Linear Constrained Minimum Variance (LCMV) beamformer instead of blocking matrix (in GSC) to generalize the good performance of the system for different arrival directions of desired speech. Finally, we have proposed nested sub-array implementation of the hybrid system to take advantages of the subband processing of wideband speech signal. Our experiments show the effectiveness of the proposed modifications in different input SNR values. the comparative evaluations demonstrate the superiority of the proposed system in noise reduction from speech in real-life conditions (where diffuse, incoherent, and directional noises are present, simultaneously).

关键词： Noise Microphones Arrays Speech Speech enhancement Array signal processing Vectors

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Reducing communication overhead under parallel list processing in multicore clusters

Reducing communication overhead under parallel list processi...

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international conference on Electrical Engineering, Computing Science and Automatic Control (CCE)

作者： Jorge Buenabad-Chávez Miguel Alfonso Castro-García José Luis Quiroz-Fabián Edgar F. Hernández-Ventura Graciela Román-Alonso Daniel M. Yellin Manuel Aguilar-Cornejo Departamento de Computación CINVESTAV-IPN Distrito Federal Mexico Departamento de Ingeniería Eléctrica UAM-Iztapalapa Distrito Federal Mexico Departamento de Computacion CINVESTAV-IPN Distrito Federal Mexico IBM Israel Software Lab Israel

ISBN: (纸本)9781457710117

the Data List Management Library (DLML) processes data lists in parallel, balancing the workload transparently to programmers. Its first design was targeted at clusters of uniprocessor nodes, and based on multiprocess parallelism and on message-passing communication. this paper presents a multithreaded design of DLML aimed at clusters of multicore nodes to better capitalise on intra-node parallelism. On applications tested, MultiCore DLML runs twice as fast as DLML when message-passing communication is not excessive. Good performance was achieved only after addressing issues relating to MPI communication overhead, cache locality and memory consumption.

关键词： Multicore processing Message systems parallel processing Message passing Instruction sets Libraries Switches

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Mapping of BLASTP Algorithm onto GPU Clusters

Mapping of BLASTP Algorithm onto GPU Clusters

引用

international conference on parallel and Distributed Systems (ICPADS)

作者： Weiguo Liu Bertil Schmidt Yongchao Liu Gerrit Voss Wolfgang Mueller-Wittig Fraunhofer IDM@NTU Nanyang Technological University Singapore Institut für Informatik Johannes Gutenberg University Mainz Germany School of Computer Engineering Nanyang Technological University Singapore Nanyang Technological University Singapore Singapore SG

Searching protein sequence database is a fundamental and often repeated task in computational biology and bioinformatics. However, the high computational cost and long runtime of many database scanning algorithms on sequential architectures heavily restrict their applications for large-scale protein databases, such as GenBank. the continuing exponential growth of sequence databases and the high rate of newly generated queries further deteriorate the situation and establish a strong requirement for time-efficient scalable database searching algorithms. In this paper, we demonstrate how GPU clusters, powered by the Compute Unified Device Architecture (CUDA), OpenMP, and MPI parallel programming models can be used as an efficient computational platform to accelerate the popular BLASTP algorithm. Compared to GPU-BLAST 1.0-2.2.24, our implementation achieves speedups up to 1.6 on a single GPU and up to 6.6 on the 6 GPUs of a Tesla S1060 quad-GPU computing system. the source code is available at: http://***/site/liuweiguohome/mpicuda-blastp.

关键词： Databases Graphics processing unit Message systems Kernel Runtime Clustering algorithms Arrays

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Fast Community Detection Algorithm with GPUs and Multicore architectures

Fast Community Detection Algorithm with GPUs and Multicore A...

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international Symposium on parallel and Distributed processing (IPDPS)

作者： Jyothish Soman Ankur Narang IBM Research India New Delhi India

In this paper, we present the design of a novel scalable parallel algorithm for community detection optimized for multi-core and GPU architectures. Our algorithm is based on label propagation, which works solely on local information, thus giving it the scalability advantage over conventional approaches. We also show that weighted label propagation can overcome typical quality issues in communities detected with label propagation. Experimental results on well known massive scale graphs such as Wikipedia (100M edges) and also on RMAT graphs with 10M 40M edges, demonstrate the superior performance and scalability of our algorithm compared to the well known approaches for community detection. On the hep-th graph (352K edges) and the wikipedia graph (100M edges), using Power 6 architecture with 32 cores, our algorithm achieves one to two orders of magnitude better performance compared to the best known prior results on parallel architectures with similar number of CPUs. Further, our GPGPU based algorithm achieves 8× improvement over the Power 6 performance on 40M edge R-MAT graph. Alongside, we achieve high quality (modularity) of communities detected, with experimental evidence from well-known graphs such as Zachary karate club, Dolphin network and Football club, where we achieve modularity that is close to the best known alternatives. To the best of our knowledge these are best known results for community detection on massive graphs (100M edges) in terms of performance and also quality vs. performance trade-off. this is also a unique work on community detection on GPGPUs with scalable performance.

关键词： Communities Image edge detection Algorithm design and analysis Detection algorithms Graphics processing unit Clustering algorithms Partitioning algorithms

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Efficient GPGPU-Based parallel Packet Classification

Efficient GPGPU-Based Parallel Packet Classification

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IEEE international conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Che-Lun Hung Hsiao-Hsi Wang Shih-Wei Guo Yaw-Ling Lin Kuan-Ching Li Department of Computer Science and Communication Engineering Providence University Taichung Taiwan Department of Computer Science and Information Engineering Providence University Taichung Taiwan Department of Computer Science and Information Management Providence University Taichung Taiwan

With the rapid growth of network technologies, many new web services have been developed to provide various applications and computing functions. these services rely deeply on the internet. therefore, packet classification is an important issue of network security that typically adopts a flexible packet filtering system to classify each processed packet. Traditional packet classification requires hung computing time to process large amount of internet packets. Hence, we propose a GPGPU-based parallel packet classification method to decrease the computational cost. We also evaluate the performance of the proposed method with implementation on various memory architectures of CUDA device. the experiment results demonstrate that the proposed method can achieve significant speed up over the sequential packet classification algorithms on single CPU.

关键词： Graphics processing unit Registers Instruction sets Filtering algorithms Classification algorithms Band pass filters Memory architecture

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