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Multi-BSP vs. BSP: A Case of Study for Dell AMD Multicores 26

Multi-BSP vs. BSP: A Case of Study for Dell AMD Multicores

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26th Euromicro international conference on parallel, Distributed, and Network-Based processing (PDP)

作者： Trabes, Guillermo Gil-Costa, Veronica Printista, Marcela Marin, Mauricio Univ Nacl San Luis Dept Informat LIDIC San Luis Argentina Univ Nacl San Luis San Luis Argentina CCT San Luis CONICET San Luis Argentina Univ Santiago Chile CeBiB Santiago Chile

ISBN: (纸本)9781538649756

Computer models have been used as a bridge between parallel algorithms and hardware architectures. the Bulk-Synchronous parallel (BSP) is a well-known computing model originally devised for distributed algorithms running on clusters of single-core processors. the Multi-BSP model, that extends the classic BSP model, was recently proposed for multi-core processors. However, this model - implemented through the MulticoreBSP-for-C library-presents some restrictions such as the explicit synchronizations between the cores, introducing some challenges on which the hardware characteristics should be taken into account to properly model the parallel algorithms. therefore, we explore the suitability of these models for the Dell multi-core architecture. the objectives of this contribution are twofold. First, we model two different multi-core Dell architectures. Second, we show that a simple model with few parameters can be easily adapted to each Dell platform rather than complex models which tends to use tricky hardware parameters.

关键词： parallel computing models bulk-synchronous parallel - BSP Multi-BSP Dell multi-cores

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An Empirical Comparison of k-Shortest Simple Path algorithms on Multicores 18

An Empirical Comparison of <i>k</i>-Shortest Simple Path Alg...

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47th international conference on parallel processing (ICPP)

作者： Ajwani, Deepak Duriakova, Erika Hurley, Neil Meyer, Ulrich Schickedanz, Alexander Nokia Bell Labs Dublin Ireland Univ Coll Dublin Sch Comp Sci Insight Ctr Data Analyt Dublin Ireland Goethe Univ Frankfurt Germany

ISBN: (纸本)9781450365109

We consider the loop less k-shortest path (KSP) problem. Although this problem has been studied in the sequential setting for at least the last two decades, no good parallel implementations are known. In this paper, we provide (i) a first systematic empirical comparison of various KSP algorithms and heuristic optimisations, (ii) carefully engineer various parallel implementations of these sequential algorithms and (iii) perform an extensive study of these parallel implementations on a range of graph classes and multicore architectures to determine the best algorithm and parallelization strategy for different graph classes. We find that even though the worst-case complexity of the best undirected KSP algorithm O (k (m + n log n)) is significantly better than that of the popular and considerably simpler directed KSP algorithm O(kn(m + n log n)), the two algorithms are fairly competitive in terms of their empirical performance on small diameter graphs. Furthermore, we show that a few simple optimisations help to bridge the gap between these KSP algorithms even more. However, on moderate to large diameter graphs, the undirected KSP algorithm is considerably faster than the directed algorithms, both in sequential and parallel settings. In terms of the parallelisation strategy, simply replacing the shortest path subroutine by parallel A-stepping algorithm can provide a good speed-up for many KSP algorithms on random graphs. In contrast, for graphs with skewed degree distribution, a more complex strategy of parallelizing the different deviations and then parallelizing the shortest path computation inside the deviations with the remaining threads, provides a better performance.

关键词： Algorithm Engineering parallel k-Shortest Path parallel Graph algorithms parallel Single Source Shortest Path

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An Axiomatization for BSP algorithms 1

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18th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Marquer, Yoann Gava, Frederic Univ Paris East Lab Algorithms Complex & Log LACL Creteil France

ISBN: (数字)9783030050573

ISBN: (纸本)9783030050573;9783030050566

the Gurevich's thesis stipulates that sequential abstract state machines (ASMS) capture the essence of sequential algorithms. On another hand, the bulk-synchronous parallel (BSP) bridging model is a well known model for HPC algorithm design. It provides a conceptual bridge between the physical implementation of the machine and the abstraction available to a programmer of that machine. the assumptions of the BSP model are thus provide portable and scalable performance predictions on most HPC systems. We follow Gurevich's thesis and extend the sequential postulates in order to intuitively and realistically capture BSP algorithms.

关键词： BSP ASM parallel algorithm HPC Postulates Cost model

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A Post-processing Approach in Moving Objects Detection via Feature Pyramid Networks 9

A Post-Processing Approach in Moving Objects Detection via F...

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9th international conference on parallel architectures, algorithms and Programming (PAAP)

作者： Lin, Li Wang, Bin Gu, Yinjuan Shanghai Univ Shanghai Inst Adv Commun & Data Sci Shanghai Peoples R China Shanghai Univ Sch Commun & Informat Engn Shanghai Peoples R China

ISBN: (纸本)9781538694039

Recent work has shown that Convolutional Neural Networks (CNNs) have great ability to deal with classification problems in pattern recognition field. Moving objects detection, regarding as a classification process, labels every pixel as a foreground pixel or a background pixel. In this paper, we proposed an effective post-processing approach, Residual Background Networks (ResBGNets), to improve the accuracy of moving objects detection in video sequences. Instead of learning the ground truth directly, our model learns the residual pictures between the results of existing methods and the ground truth. It benefits to understand the hidden character of each algorithm and correct the misclassification. Inside ResBGNets, we build Feature Pyramid Networks (FPN) to combine spatial information of the low-resolution level with semantical features of high-level of the high-resolution level. Evaluation performed on the 2014 CDnet dataset reveals that through our approach, most of the existing background subtraction methods can get better detection results and a significant higher FM score.

关键词： Moving objects detection convolutional neural networks background subtraction residual pictures feature pyramids

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A parallel Multi-keyword Top-k Search Scheme over Encrypted Cloud Data 16th

A Parallel Multi-keyword Top-k Search Scheme over Encrypted ...

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16th IFIP WG 10.3 international conference on Network and parallel Computing, NPC 2019

作者： Yang, Maohu Dai, Hua Bao, Jingjing Yi, Xun Yang, Geng Nanjing University of Posts and Telecommunications Nanjing210023 China Jiangsu Security and Intelligent Processing Lab of Big Data Nanjing210023 China Royal Melbourne Institute of Technology University Melbourne3001 Australia

ISBN: (纸本)9783030307080

With searchable encryptions in the cloud computing, users can outsource their sensitive data in ciphertext to the cloud that provides efficient and privacy-preserving multi-keyword top-k searches. However, most existing top-k search schemes over encrypted cloud data are the centralize schemes which are limited in large scale data environment. To support scalable searches, we propose a parallel multi-keyword top-k search scheme over encrypted cloud data. In this scheme, the fragment-based encrypted inverted index is designed, which is indistinguishable and can be used for parallel searching. On the basis of such indexes, a Map-Reduce-based distributed computing framework is adopted to implement the parallel multi-keyword top-k search algorithms. Security analysis and experiment evaluation show that the proposed scheme is privacy-preserving, efficient and scalable. © 2019, IFIP international Federation for Information processing.

关键词： Cloud computing

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DDP-B: A Distributed Dynamic parallel Framework for Meta-genomics Binary Similarity 16th

DDP-B: A Distributed Dynamic Parallel Framework for Meta-gen...

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16th IFIP WG 10.3 international conference on Network and parallel Computing, NPC 2019

作者： Chi, Mengxian Jin, Xu Li, Feng An, Hong University of Science and Technology of China Hefei China

ISBN: (纸本)9783030307080

Great efforts have been made on meta-genomics in the field of new species exploration in the past decades. With the development of next-generation sequencing technology, meta-genomics datasets have been produced as large as dozens of hundreds of gigabytes or even several terabytes, which brings a severe challenge to data analysis. Besides, conventional meta-genomics comparing algorithms may not take full advantage of powerful computing capacity from parallel computing techniques due to lack of parallelism. In this paper, we propose DDP-B, a distributed dynamic parallel framework for meta-genomics binary similarity analysis, to overcome these limitations. In this framework, we introduce a binary distance algorithm for meta-genomics similarity measurement and develop different levels of parallel granularity of the algorithm utilizing MPI, OpenMP, and SIMD techniques. Moreover, we establish a dynamic scheduling method to deliver asynchronous parallel computing tasks and design a distributed cluster to deploy the dynamic parallel system, which completes 2.97K pairs of meta-genomics vectors comparison per second and achieves an 134.79x speedup versus the baseline in the optimal condition. Our framework shows stable scalability when assigned larger workloads. © 2019, IFIP international Federation for Information processing.

关键词： Genome

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Fast and parallel Computation of the Discrete Periodic Radon Transform on GPUs, multi-core CPUs and FPGAs 25

Fast and Parallel Computation of the Discrete Periodic Radon...

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25th IEEE international conference on Image processing (ICIP)

作者： Carranza, Cesar Pattichis, Marios Llamocca, Daniel Pontificia Univ Catolica Peru Secc Elect & Elect Lima 32 Peru Univ New Mexico Dept Elect & Comp Engn Albuquerque NM 87131 USA Oakland Univ Dept Elect & Comp Engn Rochester MI 48063 USA

ISBN: (纸本)9781479970612

the Discrete Periodic Radon Transform (DPRT) has many important applications in reconstructing images from their projections and has recently been used in fast and scalable architectures for computing 2D convolutions. Unfortunately, the direct computation of the DPRT involves O(N-3) additions and memory accesses that can be very costly in single-core architectures. the current paper presents new and efficient algorithms for computing the DPRT and its inverse on multi-core CPUs and GPUs. the results are compared against specialized hardware implementations (FPGAs/ASICs). the results provide significant evidence of the success of the new algorithms. On an 8-core CPU (Intel Xeon), with support for two threads per core, FastDirDPRT and FastDirInvDPRT achieve a speedup of approximately 10x (up to 12:83x) over the single-core CPU implementation. On a 2048-core GPU (GTX 980), FastRayDPRT and FastRayInvDPRT achieve speedups in the range of 526 (for 127 x 127) to 873 (for 1021 x 1021), which approximate ideal speedups of what can be achieved. the DPRT can be computed exactly and in real-time (30 frames per second) for 1471x1471 images using FastRayDPRT on the GPU. Furthermore, the GPU algorithms approximate the performance of an efficient FPGA implementation using 2N parallel cores at 100MHz.

关键词： Discrete Periodic Radon Transform parallel Architecture Multi-core CPU GPU FPGA

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Transfer Learning for Airport Detection Based on Saliency Fusion of parallel Lines and Regions of Interest

Transfer Learning for Airport Detection Based on Saliency Fu...

引用

international conference on Computer Science and Network Technology (ICCSNT)

作者： Weihua Huang Jing Xia Mingdi Xu Jinzhou Huang AI Research Center Wuhan Digital Engineering Institute Wuhan China

ISBN: (纸本)9781728133003

Most existing airport detection methods for remote sensing image utilizes linear features of the airport runway insufficiently, and the computational complexity is high due to multi-scale anchor matching and global searching within full image. To solve this problem, an airport detection method based on saliency fusion of parallel lines and regions of interest is presented in this paper. Firstly the parallelism feature of the airport runway is extracted based on the prior knowledge of airport, and then regions of interest (ROI) is obtained according to the improved graph based visual saliency (GBVS). the airport is then located through the saliency fusion of parallel lines and regions of interest. Finally airport detection is achieved by transfer learning. the experimental results demonstrate that the proposed method is more advantageous than the comparison algorithms in terms of detection accuracy, processing speed, and false alarm rate. Moreover, the method only requires a small amount of samples for model training.

关键词： Airports Feature extraction Image segmentation Remote sensing Visualization Atmospheric modeling Computational modeling

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15th international Symposium on Applied Reconfigurable Computing, ARC 2019

15th International Symposium on Applied Reconfigurable Compu...

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15th international Symposium on Applied Reconfigurable Computing, ARC 2019

ISBN: (纸本)9783030172268

the proceedings contain 28 papers. the special focus in this conference is on Applied Reconfigurable Computing. the topics include: Proof-Carrying Hardware Versus the Stealthy Malicious LUT Hardware Trojan;secure Local Configuration of Intellectual Property Without a Trusted third Party;HiFlipVX: An Open Source High-Level Synthesis FPGA Library for Image processing;Real-Time FPGA Implementation of Connected Component Labelling for a 4K Video Stream;A Scalable FPGA-Based Architecture for Depth Estimation in SLAM;Evaluating LULESH Kernels on OpenCL FPGA;the TaPaSCo Open-Source Toolflow for the Automated Composition of Task-Based parallel Reconfigurable Computing Systems;Graph-Based Code Restructuring Targeting HLS for FPGAs;UltraSynth: Integration of a CGRA into a Control Engineering Environment;exploiting Reconfigurable Vector processing for Energy-Efficient Computation in 3D-Stacked Memories;Optimizing CNN-Based Hyperspectral Image Classification on FPGAs;Automatic Toolflow for VCGRA Generation to Enable CGRA Evaluation for Arithmetic algorithms;reM: A Reconfigurable Multipotent Cell for New Distributed Reconfigurable architectures;Update or Invalidate: Influence of Coherence Protocols on Configurable HW Accelerators;hybrid Prototyping for Manycore Design and Validation;Evaluation of FPGA Partitioning Schemes for Time and Space Sharing of Heterogeneous Tasks;third Party CAD Tools for FPGA Design—A Survey of the Current Landscape;Filter-Wise Pruning Approach to FPGA Implementation of Fully Convolutional Network for Semantic Segmentation;Exploring Data Size to Run Convolutional Neural Networks in Low Density FPGAs;Faster Convolutional Neural Networks in Low Density FPGAs Using Block Pruning;Supporting Columnar In-memory Formats on FPGA: the Hardware Design of Fletcher for Apache Arrow;A Novel Encoder for TDCs.

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Fixed-Order Scheduling on parallel Machines 1

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20th international conference on Integer Programming and Combinatorial Optimization (IPCO)

作者： Bosman, thomas Frascaria, Dario Olver, Neil Sitters, Rene Stougie, Leen Vrije Univ Amsterdam Dept Econometr & Operat Res Amsterdam Netherlands CWI Amsterdam Netherlands

ISBN: (数字)9783030179533

ISBN: (纸本)9783030179533;9783030179526

We consider the following natural scheduling problem: Given a sequence of jobs with weights and processing times, one needs to assign each job to one of m identical machines in order to minimize the sum of weighted completion times. the twist is that for machine the jobs assigned to it must obey the order of the input sequence, as is the case in multi-server queuing systems. We establish a constant factor approximation algorithm for this (strongly NP-hard) problem. Our approach is necessarily very different from what has been used for similar scheduling problems without the fixed-order assumption. We also give a QPTAS for the special case of unit processing times.

关键词： Approximation algorithms

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