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检索条件"任意字段=International Conference on Parallel and Distributed Processing Techniques and Applications"

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Scaling Irregular applications through Data Aggregation and Software Multithreading

Scaling Irregular Applications through Data Aggregation and ...

引用

IEEE 28th international parallel & distributed processing Symposium (IPDPS)

作者： Morani, Alessandro Tumeo, Antonino Chavarria-Miranda, Daniel Villa, Oreste Valero, Mateo Pacific NW Natl Lab Richland WA 99352 USA NVIDA Santa Clara CA USA Univ Politecn Catalanya Barcelona Supercomputing Ctr Barcelona Spain

ISBN: (纸本)9780769552071

Emerging applications in areas such as bioinformatics, data analytics, semantic databases and knowledge discovery employ datasets from tens to hundreds of terabytes. Currently, only distributed memory clusters have enough aggregate space to enable in-memory processing of datasets of this size. However, in addition to large sizes, the data structures used by these new application classes are usually characterized by unpredictable and fine-grained accesses: i.e., they present an irregular behavior. Traditional commodity clusters, instead, exploit cache-based processor and high-bandwidth networks optimized for locality, regular computation and bulk communication. For these reasons, irregular applications are inefficient on these systems, and require custom, hand-coded optimizations to provide scaling in both performance and size. Lightweight software multithreading, which enables tolerating data access latencies by overlapping network communication with computation, and aggregation, which allows reducing overheads and increasing bandwidth utilization by coalescing fine-grained network messages, are key techniques that can speed up the performance of large scale irregular applications on commodity clusters. In this paper we describe GMT (Global Memory and Threading), a runtime system library that couples software multithreading and message aggregation together with a Partitioned Global Address Space (PGAS) data model to enable higher performance and scaling of irregular applications on multi-node systems. We present the architecture of the runtime, explaining how it is designed around these two critical techniques. We show that irregular applications written using our runtime can outperform, even by orders of magnitude, the corresponding applications written using other programming models that do not exploit these techniques.

关键词： Multithreading PGAS aggregation semantic graph databases Multithreading unified retrieval models Runtime Scale formation agglomeration Dataset Data structures Scaling Irregular

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A Three-Level parallel Algorithm For MrBayes 3.2 15

A Three-Level Parallel Algorithm For MrBayes 3.2

引用

15th IEEE international Symposium on parallel and distributed processing with applications (ISPA) / 16th IEEE international conference on Ubiquitous Computing and Communications (IUCC)

作者： Zhao, Mingjie Ren, Qiang Wang, Yilin Deng, Ruikang Ren, Mingming Wang, Gang Liu, Xiaoguang Nankai Univ Nankai Baidu Joint Lab Tianjin Peoples R China

ISBN: (纸本)9781538637906

MrBayes is a popular bioinformatics software that is widely used in phylogenetic analysis. The core algorithm of Mrbayes is Metropolis Coupled Markov Chain Monte Carlo (MC3). However, when dealing with large data sets, MC3 algorithm is too slow to meet researcher's requirements. Although several parallelizations have been proposed for MrBayes, such as MPI (Message Passing Interface) based MrBayes, GPU (Graphics processing Unit) based MrBayes, there is still no efficient parallel algorithm to fully utilize computing power of modern CPU and computer architecture. This paper (a) presents a new three-level hybrid parallel algorithm, include data-level parallelism (DLP), thread-level parallelism (TLP), and process-level parallelism (PLP), which can be used on most modern multi-core computers;(b) compares the performance of different combinations of parallel strategies on real-world protein data sets. The experimental results show that, this hybrid parallel algorithm does convert more computing powers into higher speedup. Furthermore, the proposed algorithm's speedup is near the speedup on one GPU at the same data sets. This algorithm is fit for practical use in phylogenetic inferences.

关键词： MrBayes SIMD hybrid parallel computing

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Graph-based Quantum parallel Teleportation in Quantum Wireless Multi-hop Networks 15

Graph-based Quantum Parallel Teleportation in Quantum Wirele...

引用

15th IEEE international Symposium on parallel and distributed processing with applications (ISPA) / 16th IEEE international conference on Ubiquitous Computing and Communications (IUCC)

作者： Qi, Huamei Xiao, Tailong Guo, Ying Cent S Univ Informat Sci & Engn Changsha Hunan Peoples R China

ISBN: (纸本)9781538637906

Motivated by multi-particle entanglement, we propose a multi-party quantum parallel teleportation scheme in quantum wireless multi-hop networks (QWMNs) investigated with four-vertex graph-based entanglement. We show an arbitrary single-qubit quantum teleportation with graph state between directly connected two-party and an arbitrary two-qubit quantum teleportation based on four-vertex graph state followed by the multi-parity quantum teleportation based on four-vertex graph state where source node do not need share any entangled pairs with destination node but via intermediate nodes' quantum swapping to finish the teleportation. Source node and intermediate nodes conduct von Neumann measurement and transmit their classical outcomes to the destination node independently in a parallel manner. Then destination node applies appropriate unitary operation to recover the source quantum state according to the received outcomes. This graph-based scheme extends the entanglement pattern in quantum teleportation, provides a perfect multi-party teleportation model. The proposed scheme improves the constructing flexibility of the network and reduces the communication delay, which has a wide application in quantum route selection.

关键词： Quantum teleportation Four-vertex graph state Quantum multi-hop communication

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Dystri: A Dynamic Inference based distributed DNN Service Framework on Edge 23

Dystri: A Dynamic Inference based Distributed DNN Service Fr...

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52nd international conference on parallel processing (ICPP)

作者： Hou, Xueyu Guan, Yongjie Han, Tao New Jersey Inst Technol Newark NJ 07102 USA

ISBN: (纸本)9798400708435

Deep neural network (DNN) inference poses unique challenges in serving computational requests due to high request intensity, concurrent multi-user scenarios, and diverse heterogeneous service types. Simultaneously, mobile and edge devices provide users with enhanced computational capabilities, enabling them to utilize local resources for deep inference processing. Moreover, dynamic inference techniques allow content-based computational cost selection per request. This paper presents Dystri, an innovative framework devised to facilitate dynamic inference on distributed edge infrastructure, thereby accommodating multiple heterogeneous users. Dystri offers a broad applicability in practical environments, en-compassing heterogeneous device types, DNN-based applications, and dynamic inference techniques, surpassing the state-of-the-art (SOTA) approaches. With distributed controllers and a global coordinator, Dystri allows per-request, per-user adjustments of qualityof-service, ensuring instantaneous, flexible, and discrete control. The decoupled workflows in Dystri naturally support user heterogeneity and scalability, addressing crucial aspects overlooked by existing SOTA works. Our evaluation involves three multi-user, heterogeneous DNN inference service platforms deployed on distributed edge infrastructure, encompassing seven DNN applications. Results show Dystri achieves near-zero deadline misses and excels in adapting to varying user numbers and request intensities. Dystri outperforms baselines with accuracy improvement up to 95x.

关键词： MLaaS dynamic inference edge computing

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POSTER: Exploiting Approximations for Energy/Quality Tradeoffs in Service-Based applications 26

POSTER: Exploiting Approximations for Energy/Quality Tradeof...

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26th international conference on parallel Architectures and Compilation techniques (PACT)

作者： Liu, Liu Isaacman, Sibren Bhattacharjee, Abhishek Kremer, Ulrich Rutgers State Univ New Brunswick NJ 08901 USA Loyola Univ Maryland Baltimore MD USA

ISBN: (纸本)9781509067640

Approximations and redundancies allow mobile and distributed applications to produce answers or outcomes of lesser quality at lower costs. This paper introduces RAPID, a new programming framework and methodology for service-based applications with approximations and redundancies. Finding the best service configuration under a given resource budget becomes a constrained, dual-weight graph optimization problem.

关键词： Redundancy Training Measurement Brightness Optimization Robots Bars

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Auto-parallelizing stateful distributed streaming applications 12

Auto-parallelizing stateful distributed streaming applicatio...

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21st international conference on parallel Architectures and Compilation techniques, PACT 2012

作者： Schneider, Scott Hirzel, Martin Gedik, Bǔgra G. Wu, Kun-Lung IBM Thomas J. Watson Research Center Hawthorne NY 10532 United States Department of Computer Engineering Bilkent University Bilkent Ankara 06800 Turkey

ISBN: (纸本)9781450311823

Streaming applications transform possibly infinite streams of data and often have both high throughput and low latency requirements. They are comprised of operator graphs that produce and consume data tuples. The streaming programming model naturally exposes task and pipeline parallelism, enabling it to exploit parallel systems of all kinds, including large clusters. However, it does not naturally expose data parallelism, which must instead be extracted from streaming applications. This paper presents a compiler and runtime system that automatically extract data parallelism for distributed stream processing. Our approach guarantees safety, even in the presence of stateful, selective, and userdefined operators. When constructing parallel regions, the compiler ensures safety by considering an operator's selectivity, state, partitioning, and dependencies on other operators in the graph. The distributed runtime system ensures that tuples always exit parallel regions in the same order they would without data parallelism, using the most efficient strategy as identified by the compiler. Our experiments using 100 cores across 14 machines show linear scalability for standard parallel regions, and near linear scalability when tuples are shuffled across parallel regions. Copyright © 2012 by the Association for Computing Machinery, Inc. (ACM).

关键词： Scalability

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Automatic Detection of parallel applications Computation Phases

Automatic Detection of Parallel Applications Computation Pha...

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23rd IEEE international parallel and distributed processing Symposium

作者： Gonzalez, Juan Gimenez, Judit Labarta, Jesus UPC BSC Barcelona Spain

ISBN: (纸本)9781424437511

Analyzing parallel programs has become increasingly difficult due to the immense amount of information collected on large systems. The use of clustering techniques has been proposed to analyze applications. However while the objective of previous works is focused on identifying groups of processes with similar characteristics, we target a much finer granularity in the application behavior. In this paper, we present a tool that automatically characterizes the different computation regions between communication primitives in message-passing applications. This study shows how some of the clustering algorithms which may be applicable at a coarse grain are no longer adequate at this level. Density-based clustering algorithms applied to the performance counters offered by modern processors are more appropriate in this context. This tool automatically generates accurate displays of the structure of the application as well as detailed reports on a broad range of metrics for each individual region detected.

关键词： Message passing

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Performance analysis of the guaranteed bandwidth services for large file transmission

Performance analysis of the guaranteed bandwidth services fo...

引用

international conference on parallel and distributed processing techniques and applications

作者： Kim, K Lee, M Kwak, J Kong, J Byeon, O KISTI High Performance Res Networking Dep Taejon 305600 South Korea

ISBN: (纸本)1892512459

Supercomputer user groups are using the FTP for their large rile transfer. It includes extensive research information such as automobile or airplane design, medicine development, weather forecast and complex mathematical formula that need to be calculated by High-performance Supercomputer. The existing FTP has caused user to discomfort by delay and data loss according to network status. Therefore, it is necessary to efficiently raise transfer performance and minimize data loss. In this research, the auto-tuning is used for large rile transfer, and Quality of Service (QoS) is provided based on network status. As a result of performance enhancement, data loss ratio can be minimized and network becomes more stable, which makes supercomputer users believe that their computational results are precise. This paper focuses on related works about performance enhancement of large file transfer, and then does performance evaluation of the proposed scheme which provides QoS during bulk file transfer phase based on the network status.

关键词： FTP TCP tuning QoS bandwidth estimation techniques

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Multi-level shared state for distributed systems

Multi-level shared state for distributed systems

引用

31st international conference on parallel processing (ICPP 2002)

作者： Chen, DQ Tang, CQ Chen, XC Dwarkadas, S Scott, ML Univ Rochester Dept Comp Sci Rochester NY 14627 USA

ISBN: (纸本)0769516777

As a result of advances in processor and network speeds, more and more applications can productively be spread across geographically distributed machines, In this paper we present a transparent system for memory sharing, InterWeave, developed with such applications in mind. InterWeave can accommodate hardware coherence and consistency within multiprocessors (level-1 sharing), software distributed shared memory (S-DSM) within tightly coupled clusters (level-2 sharing), and version-based coherence and consistency across the Internet (level-3 sharing). InterWeave allows processes written in multiple languages, running on heterogeneous machines, to share arbitrary typed data structures as if they resided in local memory. Application-specific knowledge of minimal coherence requirements is used to minimize communication. Consistency information is maintained in a manner that allows scaling to large amounts of shared data. In C, operations on shared data, including pointers, take precisely the same form as operations on non-shared data. We demonstrate the ease of use and efficiency of the system through an evaluation of several applications. In particular we demonstrate that InterWeave's support for sharing at higher (more distributed) levels does not reduce the performance of sharing at lower (more tightly coupled) levels.

关键词： Application software Bandwidth Coherence Computer science Data mining Data structures Hardware Internet parallel processing Programming profession

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distributed Anomaly Detection Algorithm for Spatio-Temporal Trajectories of Vehicles 15

Distributed Anomaly Detection Algorithm for Spatio-Temporal ...

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15th IEEE international Symposium on parallel and distributed processing with applications (ISPA) / 16th IEEE international conference on Ubiquitous Computing and Communications (IUCC)

作者： Lu, Liping Cheng, Hao Xiong, Shengwu Duan, Pengfei Xiao, Yuan Wuhan Univ Technol Sch Comp Sci & Technol Wuhan 430070 Hubei Peoples R China Wuhan Univ Technol Hubei Key Lab Transportat Internet Things Wuhan 430070 Hubei Peoples R China

ISBN: (纸本)9781538637906

With extensive use of Internet of Vehicle (IoV) technologies in vehicle traffic management, real-time analysis of vehicle behavior trajectories is of great significance to the assessment of traffic conditions and the avoidance of abnormal conditions. This paper presents a solution which can efficiently deal with real-time streaming data of trajectory and excavate temporal and spatial abnormal information. In order to represent the local feature information of the trajectory and solve the problem of large loss of information in the feature point extraction algorithm, a trajectory partitioning strategy based on multi-motion feature and a similarity measure method based on trajectory structure are proposed. And based on the proposed strategy and method, a distributed clustering algorithm is designed for streaming trajectories to improve the efficiency of clustering algorithm. In order to solve the problem of massive calculation of distance and neighborhood density in trajectory anomaly detection algorithm, the data set is pruned by track clustering results, and the efficiency of the algorithm increases the real-time performance of abnormal trajectory detection.

关键词： spatio-temporal trajectory division trajectory similarity measure distributed trajectory clustering

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