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

共 16627 条记录，以下是211-220 订阅

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A distributed Computation Offloading Scheduling Framework based on Deep Reinforcement Learning 19

A Distributed Computation Offloading Scheduling Framework ba...

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

作者： Dai, Bin Ren, Tao Niu, Jianwei Hu, Zheyuan Hu, Shucheng Qiu, Meikang Beihang Univ Sch Comp Sci & Engn State Key Lab Virtual Real Technol & Syst Beijing 100191 Peoples R China Beihang Univ Hangzhou Innovat Inst Hangzhou 310051 Peoples R China Zhengzhou Univ Res Inst Ind Technol Sch Informat Engn Zhengzhou 450001 Peoples R China Texas A&M Univ Commerce Dept Comp Sci Commerce TX 75428 USA

ISBN: (纸本)9781665435741

Recent years have witnessed the rapid growth of smart devices and mobile applications. However, mobile applications are typically computation-intensive and delay-sensitive, while User Devices (UDs) are usually resource-limited. Mobile Edge Computing (MEC) has been proposed as a promising paradigm to mitigate the tension, where UDs' tasks could be executed either locally on itself or remotely on the edge server via computation offloading. Lots of efficient computation offloading scheduling approaches have been proposed, whereas most of them are based on centralized scheduling which could face troubles in large-scale MEC. To address the issue, this paper proposes a distributed scheduling framework by leveraging the idea of `centralized training and distributed scheduling'. Furthermore, the Actor-Critic reinforcement learning is adopted to build the framework where the Actor and Critic play the roles of distributed scheduling and centralized training, respectively. Extensive simulations are conducted and the experimental results verify the effectiveness and efficiency of the proposed framework.

关键词： distributed scheduling computation offloading deep reinforcement learning mobile edge computing

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Jobcast - parallel and distributed processing framework Data processing on a cloud style KVS database

Jobcast - Parallel and distributed processing framework Data...

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12th ieee/IPSJ international symposium on applications and the Internet (SAINT) / ieee Annual Signature Conference on Computer Software and applications (COMPSAC)

作者： Nakagawa, Ikuo Nagami, Kenichi Intec Inc Adv Technol Res & Dev Inst Tokyo Japan

ISBN: (纸本)9780769547374;9781467320016

In this paper, we propose a new architecture for parallel and distributed processing framework, "Jobcast", which enables data processing on a cloud style KVS database. Nowadays, lots of KVS (as known as Key Value Store) systems exist which achieve high scalability for data spaces among a huge number of computers. Some of KVS implementations use "consistent hash" algorithm to identify the backend data node to store a pair of key and value. Jobcast also uses consistent hash algorithm for a distribution strategy and has a capability to store key and value pairs into huge number of computers as a KVS system. Furthermore, Jobcast also distributes "jobs" into data nodes for parallel and distributed processing. In this paper, we introduce a basic architecture of Jobcast and evaluate a data processing performance for a typical example.

关键词： component parallel and distributed processing cloud database NoSQL KVS

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Exploration and Design of a Synchronous Message Passing Framework for a CPU-NPU Heterogeneous Architecture 32

Exploration and Design of a Synchronous Message Passing Fram...

引用

32nd ieee international parallel and distributed processing symposium (IPDPS)

作者： Pennefather, Sean Bradshaw, Karen Irwin, Barry Rhodes Univ Dept Comp Sci Grahamstown South Africa

ISBN: (纸本)9781538655559

In this paper we present the development of a framework for communication between an NPU (network processing unit) and CPU through synchronous message passing that is compliant with the synchronous communication events of the CSP formalisms. This framework is designed to be used for passing generic information between application components operating on both architectures and is intended to operate in conjunction with existing datapaths present on the NPU which in turn are responsible for network traffic transmission. An investigation of different message passing topologies is covered before the proposed message passing fabric is presented. As a proof of concept, an initial implementation of the fabric is developed and tested to determine its viability and correctness. Through testing it is shown that the implemented framework operates as intended. However, it is noted the throughput of the exploratory implementation is not considered suitable for high-performance applications and further evaluation is required.

关键词： Heterogeneous Architectures parallel Computing Network Flow Processors

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Fast Convergence to Fairness for Reduced Long Flow Tail Latency in Datacenter Networks 36

Fast Convergence to Fairness for Reduced Long Flow Tail Late...

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36th ieee international parallel and distributed processing symposium (ieee IPDPS)

作者： Snyder, John Lebeck, Alvin R. Duke Univ Dept Comp Sci Durham NC 27706 USA

ISBN: (纸本)9781665481069

Many data-intensive applications, such as distributed deep learning and data analytics, require moving vast amounts of data between compute servers in a distributed system. To meet the demands of these applications, datacenters are adopting Remote Direct Memory Access (RDMA), which has higher bandwidth and lower latency than traditional kernel-based networking. To ensure high performance of RDMA networks, congestion control manages queue depth on switches, and historically focused on moderating queue depth to ensure small flows complete quickly. Unfortunately, one side-effect of many common decisions is that large flows are starved of bandwidth. This negatively impacts the flow completion time (FCT) of large, bandwidth-bound flows, which are integral to the performance of data-intensive applications. The FCT is particularly impacted at the tail, which is increasingly critical for predictable application performance. We identify the root causes of the poor performance for long flows and measure the impact. We then design mechanisms that improve long flow FCT without compromising small flow performance. Our evaluations show that these improvements reduce 99.9% tail FCT of long flows by over 2x.

关键词： distributed processing Protocols Additives distributed databases Tail Bandwidth Throughput

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A New Architecture for Anonymous Use of Services in distributed Computing Networks 15

A New Architecture for Anonymous Use of Services in Distribu...

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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： Ma, Yuxiang Wu, Yulei Ge, Jingguo Li, Jun Chinese Acad Sci Comp Network Informat Ctr Beijing 100190 Peoples R China Chinese Acad Sci Inst Informat Engn Beijing 100195 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Univ Exeter Coll Engn Math & Phys Sci Exeter EX4 4QF Devon England

ISBN: (纸本)9781538637906

With the rapid development of the Internet, applications in distributed processing systems have attracted more and more attention. The privacy protection is one of the most important factors to ensure the security of underlying networks in a distributed computing system. Users expect to use a service (e.g., a computing service) anonymously, while service providers want to make sure that the users are trusted and their behavior can be accountable. Given that these two factors are contradictory, how to provide an efficient solution to achieve trusted anonymous access to the services in distributed computing networks is a challenging task. In a distributed computing system, when a task needs to be computed by a worker (or server), the transmitted data over the underlying network to perform this computing service might include many different contents, and even lots of different flows. To this end, this paper presents a new and efficient architecture to help users use services anonymously in distributed computing networks, without loss of trustworthiness. The experimental results show that the proposed architecture introduces acceptable overheads, and can achieve the goal of balancing anonymity and trust in distributed computing networks.

关键词： Computer architecture Cloud computing Servers Service-oriented architecture Privacy IP networks

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PANDA: Population Automatic Neural distributed Algorithm for Deep Leaning 19

PANDA: Population Automatic Neural Distributed Algorithm for...

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

作者： Wei, Jia Zhang, Xingjun Ji, Zeyu Li, Jingbo Wei, Zheng Xi An Jiao Tong Univ High Peiformance Comp Lab Xian Peoples R China

ISBN: (纸本)9781665435741

Deep neural network models perform very brightly in the field of artificial intelligence, but their success is affected by hyperparameters, and the learning rate schedule is one of the most important hyperparameters, and the search for the learning rate schedule is often time-consuming and computationally resource-intensive. In this paper, we propose a Population Automatic Neural distributed Algorithm (PANDA) based on population joint optimization, which uses distributed data parallel deep neural network training to implement a dynamic learning rate schedule optimization strategy based on the population idea, with almost no loss of test accuracy, PANDA is able to dynamically refine the learning rate schedule during model training instead of following the usual suboptimal strategy. We conducted experiments on typical AlexNet, VGG16, and ResNet18 using the Tianhe-3 supercomputing prototype, and the results show that using PANDA to dynamically update the learning rate greatly reduces the learning rate schedule search time while ensuring close performance with the latest population hyperparameter algorithm, and in our experiments, PANDA lead to at max 123.85x speedup, and the experimental results prove the effectiveness and robustness of PANDA.

关键词： Deep Learning distributed Training Hyperparameter Search Data parallel Population Algorithm Learning Rate Search

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Unobtrusive Support for Asynchronous GUI Operations with Java Annotations 32

Unobtrusive Support for Asynchronous GUI Operations with Jav...

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32nd ieee international parallel and distributed processing symposium (IPDPS)

作者： Mehrabi, Mostafa Giacaman, Nasser Sinnen, Oliver Univ Auckland Dept Elect & Comp Engn Parallel & Reconfigurable Comp Lab Auckland New Zealand

ISBN: (纸本)9781538655559

The complexities involved in parallel programming encourage frameworks to detach programmers from these concerns via higher-level abstraction. The high-performance nature of parallel computing drifts the focus of these programming environments towards facilitating and safeguarding faster computations. Therefore, aspects such as asynchronous graphical user interfaces (GUIs) do not see as much emphasis, even though many applications today depend on concurrent human-computer interactions. The significance of this topic is growing such that facilitating the efficient management of asynchronous GUI operations is currently a virtue, but will soon become necessary for parallel-programming frameworks. This paper discusses an unobtrusive and annotation-based approach for managing different types of asynchronous GUI operations within the layout of familiar sequential code. The proposed solution minimizes the restructuring of sequential code, in order to simplify developing, testing and maintaining GUI-based applications. Furthermore, the paper presents an implementation of the concept for @PT, a parallel programming environment based on Java annotations. The evaluation discussed in this paper suggests that the proposed mechanism is valid, and demonstrates timely and efficient handling of asynchronous GUI operations.

关键词： parallel programming asynchronous GUI responsiveness Java annotations @PT

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parallel Protein Identification Using an FPGA-Based Solution 30

Parallel Protein Identification Using an FPGA-Based Solution

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

作者： Casasopra, Fabiola Bianchi, Gea Durelli, Gianluca C. Santambrogio, Marco D. Politecn Milan Dipartimento Elett Informaz & Bioingn Milan Italy

ISBN: (纸本)9781509036820

The ability to rapidly identify a given protein from small subsamples (i.e. peptides) is at the basis of fundamental applications in the medical field. At the basis of protein identification we have a string matching problem which is computational intensive if we consider that the complexity of the algorithm scales with the length of the string and the number of sweeps of the database that are needed. In this paper we present an improvement for the FPGA-based string matching solution available in the literature improving the amount of parallelism exploited by the solution achieving a 1.63x reduction of the energy needed for the task over the literature and a 5.75x reduction when compared with high-end workstation.

关键词： Field programmable gate arrays (FPGA)

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Markov Fluid Queue Model for Rechargeable Sensor Nodes with Abnormal Death 15

Markov Fluid Queue Model for Rechargeable Sensor Nodes with ...

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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： Zhong, Ping Zhang, Yiwen Gao, Jianliang Zhang, Yiming Yan, Jize Cent S Univ Changsha 410083 Hunan Peoples R China Natl Univ Def Technol Changsha 410073 Hunan Peoples R China Univ Southampton Southampton SO17 1BJ Hants England

ISBN: (纸本)9781538637906

The rechargeable sensor network is promising for various applications. However, improving network performance is challenging, because the energy depletion of the sensor nodes will result in abnormal death of the nodes. In this paper, we propose a hybrid framework to model the abnormal death of the sensor nodes. Based on the Markov fluid queue theory, the model includes three parts, namely utilizing a Markov process to simulate the charging behavior, a queuing model to trace the working mechanism of rechargeable sensor nodes, and a continuous fluid process to indicate the energy level of sensor nodes. The numerical results show that our model can effectively predict the probability of abnormal death and stationary energy consumption of the sensor nodes.

关键词： Wireless rechargeable sensor network Markov fluid queue abnormal death stationary energy consumption

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Early Experience on the Blue Gene/Q Supercomputing System

Early Experience on the Blue Gene/Q Supercomputing System

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ieee 27th international parallel and distributed processing symposium (IPDPS)

作者： Morozov, Vitali Kumaran, Kalyan Vishwanath, Venkatram Meng, Jiayuan Papka, Michael E. Argonne Natl Lab Argonne IL 60439 USA

ISBN: (纸本)9780769549712

The Argonne Leadership Computing Facility (ALCF) is home to Mira, a 10 PF Blue Gene/Q (BG/Q) system. The BG/Q system is the third generation in Blue Gene architecture from IBM and like its predecessors combines system-on-chip technology with a proprietary interconnect (5-D torus). Each compute node has 16 augmented PowerPC A2 processor cores with support for simultaneous multithreading, 4-wide double precision SIMD, and different data prefetching mechanisms. Mira offers several new opportunities for tuning and scaling scientific applications. This paper discusses our early experience with a subset of micro-benchmarks, MPI benchmarks, and a variety of science and engineering applications running at ALCF. Both performance and power are studied and results on BG/Q is compared with its predecessor BG/P. Several lessons gleaned from tuning applications on the BG/Q architecture for better performance and scalability are shared.

关键词： IBM computers application program interfaces multi-threading parallel machines system-on-chip

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