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

共 2573 条记录，以下是51-60 订阅

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Enhanced GPU Resource Utilization through Fairness-aware Task Scheduling 14

Enhanced GPU Resource Utilization Through Fairness-aware Tas...

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13th ieee international symposium on parallel and distributed processing with applications

作者： Tarakji, Ayman Gladis, Alexander Anwar, Tarek Leupers, Rainer Rhein Westfal TH Aachen Res Grp Operating Syst Aachen Germany

ISBN: (纸本)9781467379526

Underutilization as well as oversubscription of processing resources are common problems in current accelerator-based computing systems. Facing these challenges will require intelligent algorithms for scheduling parallel workloads on accelerators. the general aim of this paper is to achieve fair distribution of the tremendous computation power of modern devices among running applications towards enhancing resource utilization. Given a set of real applications, we evaluate our model and explore the advantages of multi-tasking and concurrency on current GPUs.

关键词： GPGPU CUDA OpenCL Scheduling Kepler Heterogeneous Computing

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Load Balancing of Java applications by Forecasting Garbage Collections 13

Load Balancing of Java Applications by Forecasting Garbage C...

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13th ieee international symposium on parallel and distributed Computing (ISPDC)

作者： Portillo-Dominguez, A. Omar Wang, Miao Magoni, Damien Perry, Philip Murphy, John Univ Coll Dublin Sch Comp Sci & Informat Lero Dublin Ireland Univ Bordeaux CNRS LaBRI Bordeaux France

ISBN: (纸本)9781479959198

Modern computer applications, especially at enterprise-level, are commonly deployed with a big number of clustered instances to achieve a higher system performance, in which case single machine based solutions are less cost-effective. However, how to effectively manage these clustered applications has become a new challenge. A common approach is to deploy a front-end load balancer to optimise the workload distribution between each clustered application. Since then, many research efforts have been carried out to study effective load balancing algorithms which can control the workload based on various resource usages such as CPU and memory. the aim of this paper is to propose a new load balancing approach to improve the overall distributed system performance by avoiding potential performance impacts caused by Major Java Garbage Collection. the experimental results have shown that the proposed load balancing algorithm can achieve a significant higher throughput and lower response time compared to the round-robin approach. In addition, the proposed solution only has a small overhead introduced to the distributed system, where unused resources are available to enable other load balancing algorithms together to achieve a better system performance.

关键词： Benchmark testing Iron Java Load management Measurement Prediction algorithms Resource management Benchmark testing Load balancing System performance Java Java programming language Prediction algorithms load management management of resources waste collection Iron distributed Systems Java application Workload

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A speculative parallel intrusion prevention system based on Apache Spark 15

A speculative parallel intrusion prevention system based on ...

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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： Wang, Zhoukai Zhao, Yinliang Wang, Zhaorong Li, Yuxiang Xi An Jiao Tong Univ Dept Comp Sci & Technol Xian Shaanxi Peoples R China

ISBN: (纸本)9781538637906

Intrusion prevention system is the most important and popular tool in information security. It has been widely used to identify potential threats and respond to them swiftly. However, the existing IPS based on regular expression matching is time consuming and do not support large data well, since it scans and processes input linearly. To enhance conventional approach's parallelism and improve its efficiency for processing problems with large-scale data, this paper raised a speculative parallel intrusion prevention system based on Apache Spark. In the proposed system, the input packets are speculatively divided into several chunks, and then distributed into Apache Spark for parallel processing. After processing, the results are collected and evaluated to eliminate incorrect speculations. Experiments show that for large-scale data, by comparing with the conventional approach, the proposed system could markedly shorten the execution time for intrusion prevention. It can be proved that by adopting our novel system, the efficiency of intrusion prevention can be significantly enhanced.

关键词： Intrusion prevention system parallelization Software thread-Level Speculation Apache Spark

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A High-Performance Accelerator for Floating-Point Matrix Multiplication 15

A High-Performance Accelerator for Floating-Point Matrix Mul...

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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： Jia, Xun Wu, Gunning Xie, Xianghui State Key Lab Math Engn & Adv Comp Wuxi 214125 Peoples R China

ISBN: (纸本)9781538637906

Matrix multiplication is a widely-used routine in science and engineering applications. Accelerating this routine is important, because applications with large-scale matrix multiplication are increasingly common, especially in the area of high-performance computing (HPC). However, existing computing platforms including CPU, GPGPU and FPGA suffer from unsatisfactory performance or efficiency for this routine. In this paper, we propose a high-performance accelerator for double-precision floating-point matrix multiplication, and build a performance model for design space exploration based on a memory access scheduling. Impact of architecture parameters on accelerator performance and efficiency are evaluated and analyzed. Experimental results show that our proposed accelerator with 256 processing elements (PEs) can achieve a maximum performance of 767.99 GFLOPS and an efficiency of 99.99% for large-scale matrix multiplication, which is well suited to the requirement of HPC applications.

关键词： matrix multiplication linear array accelerator high-performance architecture

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Classification Framework for the parallel Hash Join with a Performance Analysis on the GPU 15

Classification Framework for the Parallel Hash Join with a P...

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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： Wozniak, Kinga Anna Schikuta, Erich Univ Vienna Fac Comp Sci Vienna Austria

ISBN: (纸本)9781538637906

the hash join operator is one of the most important relational operators in database applications and a prominent research topic in the domain of parallel processing. However, up to date, no consistent algorithm design guidelines for high-performance implementations on parallel platforms have been derived from the available experimental results. In this work we define a taxonomy of the parallel hash join operator landscape and categorize state of the art research accordingly. Moreover, we implement and benchmark three taxonomy types: A sequential implementation on the CPU, a hybrid CPU-GPU implementation as well as a fully parallel version on the GPU. the results show that (1) the hybrid CPU-GPU type outperforms the other two, showcasing the benefits of a good fit between algorithm type and hardware platform choice, (2) the poor end-to-end performance of the GPU-only type highlights the impact of GPU specific synchronization and contention issues that appear with an unfit design choice, (3) parallelization improves runtime by a factor of 2.2X in the end-to-end algorithm, a factor of 83X in the join phase and shows good scaling behavior with increasing number of threads. this proves that the GPU is a valuable co-processor option for computation offloading in database applications. We anticipate this classification framework to be a starting-point for design decisions for parallel big data hash join operators on other heterogeneous systems.

关键词： relational database hash join parallel processing taxonomy graphics processor performance

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Comparison of MPI and Spark for Data Science applications 34

Comparison of MPI and Spark for Data Science Applications

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34th ieee international parallel and distributed processing symposium (IPDPS)

作者： Saxena, Manvi Jha, Shweta Khan, Saba Rodgers, John Lindner, Peggy Gabriel, Edgar Univ Houston Parallel Software Technol Lab Dept Comp Sci Houston TX 77204 USA Univ Houston Dept Informat & Logist Technol Houston TX 77204 USA

ISBN: (纸本)9781728174457

Data Science applications represent a growing fraction of the scientific computing workload, many of them written in Python. the goal of this paper is to compare two popular parallel programming models, namely MPI and Apache Spark for Python based Data Science applications. the paper presents communication and file I/O microbenchmarks to evaluate the MPI support for Python applications, and uses two applications use-cases from Natural Language processing to compare the performance of the MPI and the Spark versions. Our results indicate that the MPI version shows better scalability and performance than the PySpark version of the code. On the other hand, the MPI applications are significantly larger than their PySpark counterparts, and took significantly longer to develop due to the necessity to implement some of the built-in functionality provided by Spark.

关键词： High level languages

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Latency, Power, and Security Optimization in distributed Reconfigurable Embedded Systems 30

Latency, Power, and Security Optimization in Distributed Rec...

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

作者： Nam, Hyunsuk Lysecky, Roman Univ Arizona Dept Elect & Comp Engn Tucson AZ 85721 USA

ISBN: (纸本)9781509036820

distributed embedded systems are increasingly prevalent in numerous applications, and with pervasive network access within these systems, security is also a critical design concern. In this paper, we present a modeling and optimization framework for distributed reconfigurable embedded systems, which maps tasks on a distributed embedded system with the goal of optimizing latency, energy, and/or security across all computing and communication levels. the proposed modeling framework for dataflow applications integrates models for computational latency, security levels for inter-task and intra-task communication, communication latency, and power consumption. We evaluate the proposed methodology using a video-based object detection and tracking application.

关键词： distributed embedded systems security co-design modeling dynamic optimization design space exploration

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Blockchain-based Security Architecture for distributed Cloud Storage 15

Blockchain-based Security Architecture for Distributed Cloud...

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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, Jiaxing Liu, Zhusong Chen, Long Chen, Pinghua Wu, Jigang Guangdong Univ Technol Sch Comp Sci & Technol Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781538637906

With the development of ICT industry, the volume of produced data is experiencing tremendous growth, which motivates more demands of storage capacity. Because of the limited storage capacity of users' terminals, more and more applications prefer to upload data to cloud platforms. However, it is well known that security should not be neglected in existing cloud storage architectures. Motivated by the increasing popularity of emerging blockchain technology, we propose a blockchain-based security architecture for distributed cloud storage. Moreover, we customize a genetic algorithm to solve the file block replica placement problem between multiple users and multiple data centers in the distributed cloud storage environment. Numerical experimental results show that the proposed architecture outperforms the traditional cloud storage architectures in terms of security, with acceptable network transmission delay.

关键词： cloud storage security blockchain architecture distributed

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Scheduling and Resource Management Allocation System Combined with an Economic Model 15

Scheduling and Resource Management Allocation System Combine...

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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： Menouer, Tarek Cerin, Christophe Univ Paris 13 Sorbonne Paris Cite LIPN CNRS UMR 7030 Villetaneuse France

ISBN: (纸本)9781538637906

this paper presents a new scheduling and resource management allocation system based on an economic model related to different classes for SLAs (Service Level Agreements). the goal is to address the problems of companies that manage a private infrastructure of machines, and would like to optimize the scheduling of several requests submitted online by users. Each request is an application which is executed using a set of computing resources. Our economic model has two SLAs classes (a qualitative one and a quantitative one). the qualitative class represents the satisfaction time criteria, i.e. the user waiting time before the execution of its requests. Moreover, the quantitative class represents the number of resources that must be allocated to execute the user request. As a first contribution, our system allocates dynamically, for each selected request, a set of computing cores according to the quantitative SLA class and the load of the parallel machines across the infrastructure. To choose the machine that will execute a selected request, we propose to use a Bin Packing heuristic to minimize the number of used machines and reduce the cost of the infrastructure. As a second contribution, simulations of our system are conducted on Prezi and Google Cloud Data traces and they demonstrate the potential of our approach under different scenario.

关键词： Scheduling and resource management Optimization Performance simulations New economic model

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Twenty Years of Automated Methods for Mapping applications on CGRA 36

Twenty Years of Automated Methods for Mapping Applications o...

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

作者： Martin, Kevin J. M. Univ Bretagne Sud Lab STICC UMR CNRS 6285 Lorient France

ISBN: (纸本)9781665497473

Coarse-Grained Reconfigurable Architectures (CGRAs) emerged about 30 years ago. the very first CGRAs were programmed manually. Fortunately, some compilation approaches appeared rapidly to automate the mapping process. Numerous surveys on these architectures exist. Other surveys also gather the tools and methods, but none of them focuses on the mapping process only. this paper focuses solely on automated methods and techniques for mapping applications on CGRA and covers the last two decades of research. this paper aims at providing the terminology, the problem formulation, and a classification of existing methods. the paper ends with research challenges and trends for the future.

关键词： CGRA Mapping Compilation

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