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共 511 条记录，以下是401-410 订阅

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Design and evaluation of an environment APE for automatic parallelization of programs

Design and evaluation of an environment APE for automatic pa...

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international symposium on parallel architectures, algorithms and Networks (ISPAN)

作者： V. Chaudhary Chengzhong Xu S. Roy Jialin Ju V. Sinha Laiwu Luo Parallel and Distributed Computing Laboratory Department of Electrical and Computer Engineering Wayne State University MI USA

In this paper, we present the design and evaluation of a compiler system, called APE, for automatic parallelization of scientific and engineering applications on distributed memory computers. APE is built on top of SUIF compiler. It extends SUIF with capabilities in parallelizing loops with non-uniform cross-iteration dependencies, and in handling loops that have indirect access patterns. We have evaluated the effectiveness of SUIF with several CFD test codes, and found that SUIF handles uniform loops over dense and regular data structures very well. For non-uniform loops, an innovative and efficient parallelization approach based on convex theory have been proposed and is being implemented. We have also presented a class of scalable algorithms for parallel distribution and redistribution of unstructured data structures during parallelizing irregular loops.

关键词： Program processors Distributed computing Concurrent computing Computational fluid dynamics Data structures Quantum computing programming profession parallel processing Design engineering Optimizing compilers

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A tensor product formulation of Strassen's matrix multiplication algorithm with memory reduction

A tensor product formulation of Strassen's matrix multiplica...

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international symposium on parallel Processing

作者： B. Kumar C.-H. Huang R.W. Johnson P. Sadayappan Departmentof Computer and Information Science Ohio State Uinversity Columbus OH USA Departmentof Computer Science Cloud State University Saint Cloud MN USA

A programming methodology based on tensor products has been used for designing and implementing block recursive algorithms for parallel and vector multiprocessors. A previous tensor product formulation of Strassen's matrix multiplication algorithm requires working arrays of size O(7/sup n/) for multiplying 2/sup n/*2/sup n/ matrices. The authors present a modified tensor product formulation of Strassen's algorithm in which the size of working arrays can be reduced to O(4/sup n/). The modified formulation exhibits sufficient parallel and vector operations for efficient implementation. Performance results on the Cray Y-MP are presented.< >

关键词： Tensile stress parallel programming Computerized monitoring NIST Algorithm design and analysis Vectors Linear algebra parallel machines Cloud computing Information science

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High-Performance Graph Analytics on Manycore Processors

High-Performance Graph Analytics on Manycore Processors

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international symposium on parallel and Distributed Processing (IPDPS)

作者： George M. Slota Sivasankaran Rajamanickam Kamesh Madduri Computer Science and Engineering The Pennsylvania State University University Park PA Scalable Algorithms Department Sandia National Laboratories Albuquerque NM

The divergence in the computer architecture landscape has resulted in different architectures being considered mainstream at the same time. For application and algorithm developers, a dilemma arises when one must focus on using underlying architectural features to extract the best performance on each of these architectures, while writing portable code at the same time. We focus on this problem with graph analytics as our target application domain. In this paper, we present an abstraction-based methodology for performance-portable graph algorithm design on manicure architectures. We demonstrate our approach by systematically optimizing algorithms for the problems of breadth-first search, color propagation, and strongly connected components. We use Kokkos, a manicure library and programming model, for prototyping our algorithms. Our portable implementation of the strongly connected components algorithm on the NVIDIA Tesla K40M is up to 3.25× faster than a state-of-the-art parallel CPU implementation on a dual-socket Sandy Bridge compute node.

关键词： Instruction sets Silicon Optimization Synchronization Color Arrays parallel processing

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Multi-model Stacking Ensemble Learning for Student Achievement Prediction

Multi-model Stacking Ensemble Learning for Student Achieveme...

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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Tao Fang Sirui Huang Ya Zhou Huibing Zhang Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China

ISBN: (纸本)9781665496407

Educational data mining has always been a direction of big data applications, among which the student achievement prediction is one of the research focuses. The research has two main objects, one is online education, and the other is school education. Due to the prevalence of online education and the relatively easy collection of data, many studies have focused on the prediction of student achievement in online education. At the same time, the differences in teaching methods, student habits, and technical development levels of schools in different regions have led to a slight deviation in the main research areas and research emphasis on student achievement prediction. In China, due to the difficulties of traditional schools in collecting student academic data, relevant research can only use limited grade data and campus card data. This method has limitations that are not easy to promote. This paper uses a more easily collected score data, combined with multi-model stacking ensemble learning (MMSE) model to predict students' achievement. The model mainly includes two parts: data preprocessing and model construction. In the data preprocessing part, the data features are designed using the students' grades and course information. In the model building part, a two-layer integrated learning model is established. In the first layer, 5-fold cross-validation is used to train 5 different basic classifiers. The second layer uses the regression algorithm combined with the prediction results of the first layer to predict student achievement. The results show that using the data combined with appropriate feature engineering to make predictions can get very satisfactory results.

关键词： Education Stacking Data preprocessing Predictive models Prediction algorithms Data models parallel architectures

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Cluster-based Federated Learning Framework for Intrusion Detection

Cluster-based Federated Learning Framework for Intrusion Det...

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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Luxin Cai Naiyue Chen Yuanmeng Wei Huaping Chen Yidong Li School of Computer and Information Technology Beijing Jiaotong University Beijing China Qi’anxin Technology Group Co. Ltd.. Beijing China

ISBN: (纸本)9781665452199

With the rapid development of Industrial Internet, the network intrusion detection has become particularly important. In the Industrial Internet, large-scale data is distributed in the edge nodes caused the joint analysis of network intrusion detection at each edge node has become necessary. Federated learning structure can avoid data out of local nodes to protect user privacy data. However, the data distribution is different for each edge nodes, which limits the effectiveness of federated learning models. We focus on the non-IID data features and propose a new cluster-based federated learning framework for network intrusion detection. In this method, we cluster clients into different communities by data labels, which the clients contain the similar proportion of data labels in the same community. Based on the clustering results, we decompose federated learning model aggregation into cluster aggregation and global aggregation by leveraging similarities both within and between clusters. We conduct extensive experiments based on UNSW_NB15 dataset. The results show that our method has better performance than FedAvg and FedProx. It can work well in scenarios with different distributions of data samples while ensuring data security and privacy protection.

关键词： Data privacy Federated learning Image edge detection Data security Network intrusion detection Distributed databases programming

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parallel Optimization of Computational Fluid Dynamics Application code_saturne Based on Next Generation Sunway Supercomputer

Parallel Optimization of Computational Fluid Dynamics Applic...

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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Anjun Liu Yin Liao Xihao Xu YanYan Chen Hongjun Zhong Jianming Wu Bo Kong Alexander Raikov Meng Guo Jinan Key Laboratory of High Performance Industrial Software Jinan Institute of Supercomputing Technology Jinan China Jinan Supercomputing-Zhejiang Yuansuan Industrial Simulation System Joint Laboratory Zhejiang Yuansuan Technology Co. Ltd Hangzhou China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan ) Qilu University of Technology (Shandong Academy of Sciences) Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

code_saturne is an open-source general large-scale computational fluid dynamics software independently developed by Electricite de France since 1997. Due to its high computing performance, code_saturne has been widely used in the nuclear industry, heavy fuel and biomass combustion, particle tracking and other computational fluid dynamics fields. In this work, we implemented code_saturne on the new generation Sunway supercomputer (SW26010pro) at the first time. By applying the data value-taking technology of double cache, combined with Sunway shared memory technology, we have adapted the data structure and Modular programming of code_saturne conducively to the new generation Sunway supercomputer (SW26010pro) and accelerated the software hotspots the software hotspots by 1–2 times. After optimizing and porting, this software has successfully served in the numerical simulation of the lateral flow of fuel assemblies in the nuclear industry.

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Multi-Modal Virtual-Real Fusion based Transformer for Collaborative Perception

Multi-Modal Virtual-Real Fusion based Transformer for Collab...

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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Hui Zhang Guiyang Luo Yuanzhouhan Cao Yi Jin Yidong Li School of Computer and Information Technology Beijing Jiaotong University Beijing China the State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665452199

Automobile intelligence and networking have become the inevitable trend in the future development of the automotive industry. Existing intelligent and connected vehicles rely on single-agent intelligence to perform the basic perception, which is still weak in dealing with the problem of accurate recognition and positioning in complex traffic scenes such as small and far away objects. To tackle this issue, we propose a multi-model virtual-real fusion Transformer for collaborative perception. Specifically, to possess the complementary information from both RGB images and LiDAR point clouds, we propose the multi-model virtual-real fusion (MVRF) method, which generates virtual points and compensates for the lack of point information on sparse locations. Furthermore, the heterogeneous graph attention network (HGAN) is constructed to capture the inter-agent interaction and adaptively incorporate multiple agents’ features. The HGAN contains a series of encoder layers, each of which has a heterogeneous inter-agent attention module and a multi-scale self-attention module, which motivates to learn different relationships based on various agents’ types and simultaneously capture the global and local spatial attention. Extensive experiments demonstrate that the proposed method gains superior performance as compared with state-of-the-art methods.

关键词： Point cloud compression Industries Connected vehicles Laser radar Collaboration programming Transformers

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Semi-structured portable library for multiprocessor servers

Semi-structured portable library for multiprocessor servers

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international symposium on parallel and Distributed Processing (IPDPS)

作者： G. Tsilikas M. Fleury Electronic Systems Engineering Department Multimedia Architectures Laboratory University of Essex Colchester Essex UK

The MiPPS library supports a hybrid model of parallel programming. The library is targeted at commodity multiprocessors, with support for clusters. The implementation of the concurrency routines reveals discrepancies between popular operating systems. Tests on suitable applications also reveal similar discrepancies in performance across different multiprocessors. The MiPPS library has also been the basis of a parallelization of the Active Chart Parsing algorithm for speech understanding.

关键词： Software libraries Hidden Markov models Object oriented modeling parallel programming Operating systems Message passing Data structures Application software Software algorithms Speech

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Global predicates in rough real time

Global predicates in rough real time

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international symposium on parallel and Distributed Processing (IPDPS)

作者： J. Mayo P. Kearns Department of Computer Science Williamsburg VA USA

Evaluation of predicates on the state of a distributed system is complicated by the lack of either a common clock or common memory. In these systems, message passing is often used to order local events globally. This leads to a partial, causal ordering of system events. Predicate evaluation algorithms based on this causal ordering generally cannot determine if an unstable predicate was true at some instant of real time without freezing the underlying application. They only determine whether or not the predicate could have occurred. This ordering is sufficient for evaluating stable predicates, but algorithms based on it require a good deal of message passing. We present two algorithms which conclusively evaluate both stable and a restricted class of unstable predicates for a given execution. The algorithms are based on the use of roughly synchronized clocks. We present an algorithm for scheduled evaluation as well as a centralized detection algorithm.

关键词： Clocks Message passing Synchronization Computer science Detection algorithms programming Counting circuits

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Data partitioning schemes for the parallel implementation of the revised simplex algorithm for LP problems

Data partitioning schemes for the parallel implementation of...

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international symposium on parallel Processing

作者： U. Sridhar A. Basu Center for Development of Advanced Computing Bangalore India

The parallel implementation of the revised simplex algorithm (RSA) using eta-factorization holds the promise of significant improvement in the execution time by virtue of the existence of a high degree of parallelism in the computation within an iteration of the algorithm. However, the scheme employed to partition key data structures in a distributed memory parallel processor has a great impact on the achievable performance. The paper explores the trade-offs between block-row and block-column partitioning schemes for the matrix of constraint coefficients vis-a-vis the communication overheads and granularity of parallel computations. The results of an approximate analysis of the compute-communication balance are compared with measurements from practical implementation of the partitioning schemes on C-DAC's PARAM 8000 distributed memory parallel processor.< >

关键词： Partitioning algorithms Concurrent computing Costs Data structures Distributed computing Memory management Linear programming Engineering management parallel processing Acceleration

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