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

共 11314 条记录，以下是591-600 订阅

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An efficient, distributed stochastic gradient descent algorithm for deep-learning applications 46

An efficient, distributed stochastic gradient descent algori...

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46th international conference on parallel processing Workshops (ICPPW)

作者： Cong, Guojing Bhardwaj, Onkar Feng, Minwei IBM TJ Watson Res Ctr 1101 Kitchawan Rd Yorktown Hts NY 10598 USA

ISBN: (纸本)9781538610428

parallel and distributed processing is employed to accelerate training for many deep-learning applications with large models and inputs. As it reduces synchronization and communication overhead by tolerating stale gradient updates, asynchronous stochastic gradient descent (ASGD), derived from stochastic gradient descent (SGD), is widely used. Recent theoretical analyses show ASGD converges with linear asymptotic speedup over SGD. Oftentimes glossed over in theoretical analysis are communication overhead and practical learning rates that are critical to the performance of ASGD. After analyzing the communication performance and convergence behavior of ASGD using the Downpour algorithm as an example, we demonstrate the challenges for ASGD to achieve good practical speedup over SGD. We propose a distributed, bulk-synchronous stochastic gradient descent algorithm that allows for sparse gradient aggregation from individual learners. The communication cost is amortized explicitly by a gradient aggregation interval, and global reductions are used instead of a parameter server for gradient aggregation. We prove its convergence and show that it has superior communication performance and convergence behavior over popular ASGD implementations such as Downpour and EAMSGD for deep-learning applications.

关键词： Convergence Servers Training Stochastic processes Convolution parallel processing Complexity theory

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A novel Optimization Technique for Mastering Energy Consumption in Cloud Data center 15

A novel Optimization Technique for Mastering Energy Consumpt...

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： Ben Maaouia, Omar Fkaier, Hazem Jemni, Mohamed Cerin, Christophe Univ Tunis LATICE ENSIT Tunis Tunisia Univ Tunis El Manar FST Tunis Tunisia Univ Paris 13 LIPN UMR 7030 CNRS Villetaneuse France

ISBN: (纸本)9781538637906

Cloud computing is one of the most popular technologies nowadays because of its wide utilities and various benefits in several IT companies all over the world. However, in front of the increasing users' requests for computing services, cloud providers are encouraged to deploy large data centers, which consumes very large amount of energy and contribute to high operational costs. Among the effects, carbon dioxide emission rate is growing each day due to the huge amount of power consumption. This energy efficiency is an important issue in cloud computing, mainly due to the required electrical power to run these systems and to cool them. Therefore, energy consumption has become a major concern for the widespread deployment of Cloud data centers. The growing importance for parallel applications in the Cloud introduces significant challenges in reducing energy consumption from hosted servers. This paper addresses the problem of placing independent applications on the physical servers (hosts) of a Cloud infrastructure. We proposed a novel heuristic to allocate applications so that total energy consumption is reduced. Our proposal respects various constraints e.g. the machines availability, capability and the duplication of applications. Experiments are illustrated to validate the potential of our approach.

关键词： Resource management for parallel and distributed systems Cloud computing Energy consumption Minimization

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Empirical study of variable granularity and global centralized load balancing algorithms

Empirical study of variable granularity and global centraliz...

引用

Proceedings of the international conference on parallel and distributed processing techniques and applications, PDPTA'04

作者： Kofahi, Najib A. Rahman, Quazi Abidur Department of Information Science King Fahd Univ. Petrol. and Minerals Dhahran 31261 Saudi Arabia

ISBN: (纸本)1932415262

Task migration and load sharing algorithms are two load balancing strategies that are essential in distributed memory multiprocessor as well as in multi-computer environments. Dynamic load balancing is more suitable in heterogeneous systems. Various load sharing and global centralized algorithms have been proposed in the literature. These algorithms demand careful investigation about their suitability in different applications. In this research paper we focus on the performance evaluation of two algorithms implemented on SPMD model based on their controlling parameters. A network of workstations has been chosen and PVM libraries have been used for implementation. Matrix multiplication has been selected as the application. The two algorithms investigated are: variable granularity (guided self scheduling) and one global centralized task migration algorithm.

关键词： distributed computer systems

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A stripped mirroring RAID architecture with distributed sparing

A stripped mirroring RAID architecture with distributed spar...

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Proceedings of the international conference on parallel and distributed processing techniques and applications

作者： Han, Jun-Tak Chang, Tae-Mu Dept. of Computer Engineering Donghae University 119 Jiheung Dong Donghae Kangwondo 240-713 Korea Republic of Dept. of Computer Engineering Dongguk University 26 Phil Dong 3 Junggu Seoul 110-175 Korea Republic of

ISBN: (纸本)1892512416

Redundant arrays of independent disks (RAID) have been widely used for providing a mass storage with high performance and reliability. Among RAID architectures, RAID-1 and RAID-5 are most popular. But RAID-1 means excessive redundancy, and RAID-5 shows poor write performance. Recently SMDA (Stripped Mirroring Disk Array) was proposed to overcome small-write problem of disk array. SMDA stores the original data in two ways, one on a single disk and the other on a plurality of disks in RAID-0 by stripping [2]. In this paper, we propose a new disk array architecture, called distributed Sparing-Stripped Mirroring Disk Array (ds-SMDA), that adds distributed on-line spares to SMDA. With ds-SMDA, we can increase parallelism of small-size read and write operations in the normal state. And ds-SMDA enables us to reduce seek time during the recovery time. Moreover, we can recover from any double disk failures.

关键词： parallel processing systems

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Combining the synchronous protocol with the optimistic time management algorithm (TMA) to improve the latency and the processor idle time

Combining the synchronous protocol with the optimistic time ...

引用

2008 international conference on parallel and distributed processing techniques and applications, PDPTA 2008

作者： Rizvi, Syed S. Riasat, Aasia Computer Science and Engineering Department University of Bridgeport Bridgeport CT United States Department of Computer Science Institute of Business Management Karachi Pakistan

ISBN: (纸本)1601320841

The concept of Global virtual time (GVT) has become an essential element of optimistic time management algorithms (TMA) that provide synchronization in a parallel and distributed computing environment. The performance of this optimistic TMA is optimal since it gives accurate GVT approximation. However, this accurate GVT approximation comes at the expense of slower execution rate which results a high GVT latency. Since this resultant GVT latency is not only high but also widely varied, the multiple processors involve in communication remain idle during that period of time. This paper examines the potential use of tress and butterflies barriers with the Mattern's optimistic TMA [1] using a ring structure. Our Simulation and numerical results verify that the use of tree barriers with the Mattern's GVT structure can significantly improve the latency time and thus increase the overall throughput of the parallel and scalable distributed simulation systems.

关键词： parallel processing systems

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Optimization of Layer-based Scheduling Algorithms for Mixed parallel applications with Precedence Constraints Using Move-blocks

Optimization of Layer-based Scheduling Algorithms for Mixed ...

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17th Euromicro international conference on parallel, distributed and Network-Based processing

作者： Kunis, Raphael Ruenger, Gudula Tech Univ Chemnitz Dept Comp Sci D-09107 Chemnitz Germany

ISBN: (纸本)9780769535449

The efficient scheduling of large mixed parallel applications is challenging. Most existing algorithms utilize scheduling heuristics and approximation algorithms to determine a good schedule as basis for an efficient execution in large scale scientific computing. This paper concentrates on the scheduling of mixed parallel applications represented by task graphs with parallel tasks and precedence constraints between them. Layer-based scheduling algorithms for homogeneous target platforms are improved by adding a move-blocks phase that further reduces the resulting parallel runtime. The layer-based scheduling approach is described and the move-blocks algorithm is introduced in detail. The move-blocks extension provides better scheduling results for small as well as for large problems but has only a small increase in runtime. This is shown by a comparison of the modified and the original algorithms over a wide range of test cases.

关键词： Scheduling

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Scaling Irregular applications through Data Aggregation and Software Multithreading

Scaling Irregular Applications through Data Aggregation and ...

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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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Dynamic Load Balancing and Channel Strategy for Apache Flume Collecting Real-time Data Stream 15

Dynamic Load Balancing and Channel Strategy for Apache Flume...

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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： Shu, Buqing Chen, Haopeng Sun, Meng Shanghai Jiao Tong Univ Sch Software Shanghai Peoples R China

ISBN: (纸本)9781538637906

With the development of information technology, real-time data stream processing(RTDSP) has become a popular research topic. The first step of RTDSP is collecting data, requiring a data collector to receive data from the source and send them to the sink. Apache Flume, a distributed and reliable framework, used for this purpose, has some limitations and drawbacks on load balancing and storage. In this paper, we aim to improve performance and availability for collecting unstable real-time big data stream. So we propose a new load balancing strategy based on the free memory size and a storage strategy of integration memory channel with the multi-file channel to reduce the overhead of disk and network. Finally, the experimental results show that the availability and performance are improved under the condition of a poor network, high availability requirements, intense competition in memory resources and large data size. Specifically, the availability is higher than 99.999%, and the performance can be improved by 10%-50% under different conditions.

关键词： Load management Real-time systems distributed databases Throughput Monitoring Dynamic scheduling Memory management

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A preliminary evaluation of the speedup of a distributed simulator for reliability analysis

A preliminary evaluation of the speedup of a distributed sim...

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Proceedings of the international conference on parallel and distributed processing techniques and applications

作者： Marino, Mario D. Silva, Aldy F. LASB Polytechnic School University of Sao Paulo Sao Paulo Brazil Senac Coll. of Comp. Sci Technol. Production Engineering Department University of Sao Paulo Sao Paulo Brazil

ISBN: (纸本)1892512416

The analysis of reliability consists on using the times to failure and model them through a regression Statistics model. The Weibull distribution model is an example of this. This model allows to find the estimatives of the mean time to failure and the percentual to failure, which are very important ones to evaluate the reliability of products, i.e., to improve their quality. A sequential simulator based on this model was developed. Depending on the input parameters, the simulation time becomes prohibitive. So, this motivated the creation of a distributed version of this simulator, in order to decrease the simulation time. The goal of this paper is to introduce this preliminary version of this simulator and to show its speedup for 5000 replics (number of times of the main loop), 300 iterations of Bootstrap routine and maximum number of 50 iterations (Newton-Raphson).

关键词： distributed computer systems

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An approach of anomaly diagnosis with logs for distributed services in communication network information system 15

An approach of anomaly diagnosis with logs for distributed s...

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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： Sun, Kang Meng, Luo-Ming Guo, Shao-Yong Xu, Si-Ya Wang, Ying Li, Wei-Jian Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China Power Grid Co Ltd Elect Power Dispatching Control Ctr Guangdong Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781538637906

Anomaly diagnosis for distributed service plays an important role in communication network information system. Log analysis is the main method to undertake anomaly detection. In order to reduce the manual detection, we propose an anomaly detection method based on the time-weighted control flaw graph model. The border is split by a discrete degree strategy based on analyzing the time interval distribution and the time weight is selected to be k-means. Experiments show that our algorithm has good precision and recall in anomaly diagnosis. In real-world scenarios, it has a precision of 80% and a recall rate of 65% on average.

关键词： anomaly diagnosis logs distributed services time weight

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