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检索条件"任意字段=13th IEEE International Symposium on Parallel and Distributed Processing with Applications"

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A Smartphone-based Online Pedestrian Positioning Approach for Both Structured And Open Indoor Spaces 15

A Smartphone-based Online Pedestrian Positioning Approach fo...

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： Yu, Wenping Xu, Yuwei Zhang, Jianzhong Ma, Chao Xu, Jingdong Nankai Univ Coll Comp & Control Engn Tianjin Peoples R China

ISBN: (纸本)9781538637906

Pedestrian Dead Reckoning (PDR) technique has been extensively studied. However, without site survey, there are still some challenges in providing continuous and accurate online positioning services for indoor environments including both structured and open spaces, due to the lack of reference points. To cope with this problem, in this paper, we propose an online indoor pedestrian positioning approach based on integration of sensors in smartphone, indoor map and wireless access points (AP). In the structured spaces, we realize pedestrian positioning by matching activity sequence to indoor road map of structured spaces using a hidden Markov model. Meanwhile, we use Wi-Fi received signal strength (RSS) values to estimate AP locations. In the open spaces, with these APs location information, our approach applies an extended Kalman filter (EKF) model to integrate PDR and WiFi positioning. We evaluate our approach using smartphones in the first floor of a teaching hall on campus. the results show that positioning errors of the proposed approach are decreased by 81.9 percent in the structured space and 35.9 percent in the open space when compared with PDR.

关键词： PDR AP location estimation HMM EKF

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Dynamic Fine-Grained Workload Partitioning for Irregular applications on Discrete CPU-GPU Systems 19

Dynamic Fine-Grained Workload Partitioning for Irregular App...

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19th ieee international symposium on parallel and distributed processing with applications (ieee ISPA)

作者： Xiao, Chunhua Ran, Wei Lin, Fangzhu Zhang, Lin Chongqing Univ Coll Comp Sci Chongqing Peoples R China

ISBN: (纸本)9781665435741

As the scale of big data continues to grow and the complexity of data analysis algorithms increases, the desire for greater computing power is increasingly evident. A popular approach is to utilize heterogeneous systems for computation. Discrete CPU-GPU system, which has CPU and GPU on different chips connected through a PCI-e bus, is a typical heterogeneous system. there have been a lot of schemes proposed to improve performance on the discrete CPU-GPU system through partitioning. However, most of them are for regular applications and far from ideal in terms of resource utilization and performance for irregular applications. Heterogeneous computing receives much attention due to its performance potential, and many regular applications are greatly benefited from it, but the acceleration of irregular applications is still a problem to be solved. In this paper, we propose a dynamic fine-grained workload partitioning approach for irregular applications that boosts resource utilization to achieve a better load balance on heterogeneous platforms. the approach monitors the kernel execution of the CPU and GPU at runtime, and finely partitions the workload according to their processing speed, assigning relatively regular data to the GPU and the rest to the CPU. Evaluated with various irregular workloads, our scheme achieves up to 20% performance improvement over the state-of-the-art coarse-grained scheme, and the performance gap is less than 5% in most cases compared to oracle-based partitioning.

关键词： heterogeneous system load balancing irregular application workload partitioning

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Leveraging naturally distributed data redundancy to reduce collective I/O replication overhead 29

Leveraging naturally distributed data redundancy to reduce c...

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29th ieee international parallel and distributed processing symposium (IPDPS)

作者： Nicolae, Bogdan IBM Res Dublin Ireland

ISBN: (纸本)9781479986484

Dumping large amounts of related data simultaneously to local storage devices instead of a parallel file system is a frequent I/O pattern of HPC applications running at large scale. Since local storage resources are prone to failures and have limited potential to serve multiple requests in parallel, techniques such as replication are often used to enable resilience and high availability. However, replication introduces overhead, both in terms of network traffic necessary to distribute replicas, as well as extra storage space requirements. To reduce this overhead, state-of-art techniques often apply redundancy elimination (e.g. compression or deduplication) before replication, ignoring the natural redundancy that is already present. By contrast, this paper proposes a novel scheme that treats redundancy elimination and replication as a single co-optimized phase: remotely duplicated data is detected and directly leveraged to maintain a desired replication factor by keeping only as many replicas as needed and adding more if necessary. In this context, we introduce a series of high performance algorithms specifically designed to operate under tight and controllable constrains at large scale. We present how this idea can be leveraged in practice and demonstrate its viability for two real-life HPC applications.

关键词： data resilience high availability data replication deduplication collective I/O scalability redundancy management

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Secure Beamforming Design with Bidirectional Secondary Transmissions in Wireless-Powered Cognitive Radio Networks 15

Secure Beamforming Design with Bidirectional Secondary Trans...

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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： Tang, Kun Shi, Ronghua Luo, Entao Cent S Univ Sch Informat Sci & Engn Changsha Hunan Peoples R China

ISBN: (纸本)9781538637906

In wireless-powered cooperative cognitive radio networks, guaranteeing the secure transmission of the primary's signal is a critical problem. In this paper, we focus on the primary's information security during the transmission phase when some potential eavesdroppers exist in the range of secondary systems. In particular, we consider a new spectrum sharing protocol that multiplexes the secondary transmissions with both the primary and cognitive transmissions. Moreover, we aim to jointly optimize energy harvesting duration and beamforming vectors to maximize the secondary transmission rate while satisfying the secrecy quality-of-service (QoS) requirement of the primary system and power power constraint of the secondary system. To solve this optimization problem, we adopt a two-stage procedure to obtain the optimal solutions. Simulation results show that the proposed scheme can greatly achieve the transmission rate of the secondary system while can provide a higher secure rate for the primary system compared to the zero-forcing (ZF) scheme.

关键词： cognitive radio networks cooperative spectrum sharing wireless energy harvesting secure beamforming

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An Efficient Framework for Target Search with Cooperative UAVs in a FANET 15

An Efficient Framework for Target Search with Cooperative UA...

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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： Li, Xianfeng Chen, Jie Peking Univ Sch Elect & Comp Engn Shenzhen Key Lab Informat Theory & Future Network Shenzhen Peoples R China

ISBN: (纸本)9781538637906

Flying Ad-Hoc Network (FANET) is a special type of Mobile Ad-Hoc Network (MANET) which consists of multiple networked Unmanned Aerial Vehicles (UAVs). Compared to traditional target search using a single UAV, multiple cooperative UAVs within a FANET have the potential to accomplish this work more efficiently, and multi-UAV cooperative target search has attracted increasing research attention in recent years. In this paper, we conduct a comprehensive investigation on efficient and accurate multi-UAV cooperative target search techniques. More specifically, we propose several adaptive mobility models and an innovative information fusion mechanism to improve the search efficiency. Meanwhile, to improve the search accuracy, we introduce a low-overhead decision-making mechanism to reduce chances for false target identifications. the simulation results show that the framework outperforms the baseline framework significantly in terms of both efficiency and accuracy. Our experiments also exhibit how individual mechanisms introduced in our work contribute to the improvements on search efficiency or accuracy, therefore providing more guidance for their adoption in practice.

关键词： Flying Ad-Hoc Network (FANET) Unmanned Aerial Vehicle (UAV) target search mobility model

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Runtime support for parallelization of data-parallel applications on adaptive and nonuniform computational environments

Runtime support for parallelization of data-parallel applica...

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5th ieee international symposium on High Performance distributed Computing

作者： Kaddoura, M Ranka, S SYRACUSE UNIV SCH COMP & INFORMAT SCICTR SCI & TECHNOL 2120SYRACUSENY 13244

ISBN: (纸本)0818675829

In this paper we discuss the runtime support required for the parallelization of unstructured data-parallel applications on nonuniform and adaptive environments. the approach presented is reasonably general and is applicable to a wide variety of regular as well as irregular applications. We present performance results for the solution of an unstructured mesh on a cluster of heterogeneous workstations.

关键词： parallel processing systems

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Electro: Toward QoS-Aware Power Management for Latency-Critical applications 15

Electro: Toward QoS-Aware Power Management for Latency-Criti...

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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, Yanchao Chen, Quan Shen, Yao Guo, Minyi Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai Peoples R China Shanghai Jiao Tong Univ Shanghai Inst Adv Commun & Data Sci Shanghai Peoples R China

ISBN: (纸本)9781538637906

Reducing the energy consumption of datacenters is critical for their scalability, sustainability, and affordability when hosting latency-critical applications. Prior work has focused on single-thread applications with a stable workload. Recently, multi-thread latency-sensitive services are widely used in current datacenters. However, the variability of user queries in these service makes existing schemes ineffective, leading to either QoS violations or higher energy consumption. In order to address this new problem, we propose Electro, a machine learning enhanced dynamic power management system. Electro consists of a query duration predictor and a query consolidating engine. the duration predictor can precisely predict the duration of each user query in different scenarios based on the pre-trained duration models. At runtime, according to the predicted duration, the query consolidating engine consolidates user queries accordingly to maximize the duration of the CPU idle states while guaranteeing the QoS. the longer each idle state is, the deeper low-power sleep states can the CPU enter. Our evaluation results on the latest Intel Xeon V4 CPU show that Electro reduces the energy consumption by 81.8% on average compared with the default OS scheduling, and by 14.4% on average compared with the state-of-the-art technique while achieving the 95%-ile latency target for latency-sensitive applications.

关键词： Quality of Service Energy Consumption Machine Learning Consolidated Execution

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Automatic Resource Scheduling with Latency Hiding for parallel Stencil applications on GPGPU Clusters

Automatic Resource Scheduling with Latency Hiding for Parall...

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26th ieee international parallel and distributed processing symposium (IPDPS) / Workshop on High Performance Data Intensive Computing

作者： Maeda, Kumiko Murase, Masana Doi, Munehiro Komatsu, Hideaki Noda, Shigeho Himeno, Ryutaro IBM Japan Ltd IBM Res Tokyo Tokyo Japan IBM Japan Ltd Syst & Technol Grp Tokyo Japan RIKEN Adv Ctr Comp & Commun Saitama Japan

ISBN: (纸本)9780769546759

Overlapping computations and communication is a key to accelerating stencil applications on parallel computers, especially for GPU clusters. However, such programming is a time-consuming part of the stencil application development. To address this problem, we developed an automatic code generation tool to produce a parallel stencil application with latency hiding automatically from its dataflow model. With this tool, users visually construct the workflows of stencil applications in a dataflow programming model. Our dataflow compiler determines a data decomposition policy for each application, and generates source code that overlaps the stencil computations and communication (MPI and PCIe). We demonstrate two types of overlapping models, a CPU-GPU hybrid execution model and a GPU-only model. We use a CFD benchmark computing 19-point 3D stencils to evaluate our scheduling performance, which results in 1.45 TFLOPS in single precision on a cluster with 64 Tesla C1060 GPUs.

关键词： latency hiding network embedding resource scheduling stencil computations

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Utilizing Hardware Performance Counters to Model and Optimize the Energy and Performance of Large Scale Scientific applications on Power-aware Supercomputers 30

Utilizing Hardware Performance Counters to Model and Optimiz...

引用

30th ieee international parallel and distributed processing symposium (IPDPS)

作者： Wu, Xingfu Taylor, Valerie Texas A&M Univ Dept Comp Sci & Engn College Stn TX 77843 USA

ISBN: (纸本)9781509036820

Hardware performance counters are used as effective proxies to estimate power consumption and runtime. In this paper we present a performance counter-based power and performance modeling and optimization method, and use the method to model four metrics: runtime, system power, CPU power and memory power. the performance counters that compose the models are used to explore some counter-guided optimizations with two large-scale scientific applications: an earthquake simulation and an aerospace application. We demonstrate the use of the method using two power-aware supercomputers, Mira at Argonne National Laboratory and SystemG at Virginia Tech. the counter-guided optimizations result in a reduction in energy by an average of 18.28% on up to 32,768 cores on Mira and 11.28% on up to 128 cores on SystemG for the aerospace application. For the earthquake simulation, the average energy reductions achieved are 48.65% on up to 4,096 cores on Mira and 30.67% on up to 256 cores on SystemG.

关键词： Counter-guided optimization Hardware performance counters Performance modeling Power modeling Power-aware supercomputers

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Refactoring the Molecular Docking Simulation for Heterogeneous, Manycore Processors Systems 15

Refactoring the Molecular Docking Simulation for Heterogeneo...

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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： Chen, Junshi Lin, Han Liang, Weihao Yu, Yang Han, Wenting An, Hong Chen, Yong Liu, Xin Univ Sci & Technol China Sch Comp Sci & Technol Hefei Anhui Peoples R China Texas Tech Univ Dept Comp Sci Lubbock TX 79409 USA Natl Res Ctr Parallel Comp Engn & Technol Beijing Peoples R China

ISBN: (纸本)9781538637906

this paper presents a scalable design and implementation of the molecular docking application DOCK for a large-scale high performance computing system, the Sunway TaihuLight supercomputer, which provisions a heterogeneous, manycore processor architecture that consists of management processing elements (MPEs) and clusters of computing processing elements (CPEs). the key innovation is a novel refactoring of DOCK on the CPEs. Optimization techniques for data redundancy minimization to fit data in cache, software-controlled prefetching into scratchpads, memory access coalescing, software caches, vectorization and loop unrolling are employed to improve the exploitation of the computational resources. For a single docking process, the refactored version using both the MPE and CPE cluster achieved 260x to 402x speedup compared against the original ported version using MPE only. To scale the DOCK to the full Sunway Taihulight system with 10,649,600 cores (including all MPE and CPE cores), we present an MPI communication domain partition scheme as well. For docking 9 million small compounds to a Zika virus target protein, we manage to scale to 131,072 MPEs, and 8,388,608 CPEs, with a total of 8,519,680 cores.

关键词： molecular docking Sunway TaihuLight Supercomputer heterogeneous manycore optimization

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