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

共 2574 条记录，以下是2341-2350 订阅

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Hierarchical Local Storage: Exploiting Flexible User-Data Sharing Between MPI Tasks

Hierarchical Local Storage: Exploiting Flexible User-Data Sh...

引用

international symposium on parallel and distributed processing (IPDPS)

作者： Marc Tchiboukdjian Patrick Carribault Marc Pérache Université de Versailles Saint Quentin en Yvelines France DAM DIF CEA Arpajon France

With the advent of the multicore era, the number of cores per computational node is increasing faster than the amount of memory. this diminishing memory to core ratio sometimes even prevents pure MPI applications to benefit from all cores available on each node. A possible solution is to add a shared memory programming model like Open MP inside the application to share variables between Open MP threads that would otherwise be duplicated for each MPI task. Going to hybrid can thus improve the overall memory consumption, but may be a tedious task on large applications. To allow this data sharing without the overhead of mixing multiple programming models, we propose an MPI extension called Hierarchical Local Storage (HLS) that allows application developers to share common variables between MPI tasks on the same node. HLS is designed as a set of directives that preserve the original parallel semantics of the code and are compatible with C, C++ and Fortran languages and the Open MP programming model. this new mechanism is implemented inside a state-of-the-art MPI 1.3 compliant runtime called MPC. Experiments show that the HLS mechanism can effectively reduce memory consumption of HPC applications. Moreover, by reducing data duplication in the shared cache of modern multicores, the HLS mechanism can also improve performances of memory intensive applications.

关键词： Memory management Multicore processing Instruction sets Programming Semantics Computational modeling Data models

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Implementation of 3D FFTs Across Multiple GPUs in Shared Memory Environments

Implementation of 3D FFTs Across Multiple GPUs in Shared Mem...

引用

ieee international Conference on parallel and distributed Computing, applications and Technologies (PDCAT)

作者： Nimalan Nandapalan Jiri Jaros Alistair P. Rendell Bradley Treeby Research School of Computer Science ANU College of Engineering and Computer Science Australian National University ACT Australia Research School of Engineering ANU College of Engineering and Computer Science Australian National University ACT Australia

ISBN: (纸本)9781467357043

In this paper, a novel implementation of the distributed 3D Fast Fourier Transform (FFT) on a multi-GPU platform using CUDA is presented. the 3D FFT is the core of many simulation methods, thus its fast calculation is critical. the main bottleneck of the distributed 3D FFT is the global data exchange which must be performed. the latest version of CUDA introduces direct GPU-to-GPU transfers using a Unified Virtual Address space (UVA) that provides new possibilities for optimising the communication part of the FFT. Here, we propose different implementations of the distributed 3D FFT, investigate their behaviour, and compare their performance with the single GPU CUFFT and CPU-based FFTW libraries. In particular, we demonstrate the advantage of direct GPU-to-GPU transfers over data exchanges via host main memory. Our preliminary results show that running the distributed 3D FFT with four GPUs can bring a 12% speedup over the single node (CUFFT) while also enabling the calculation of 3D FFTs of larger datasets. Replacing the global data exchange via shared memory with direct GPU-to-GPU transfers reduces the execution time by up to 49%. this clearly shows that direct GPU-to-GPU transfers are the key factor in obtaining good performance on multi-GPU systems.

关键词： Graphics processing units three-dimensional displays Kernel Performance evaluation Bandwidth Educational institutions Engines

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An SMT-Selection Metric to Improve Multithreaded applications' Performance

An SMT-Selection Metric to Improve Multithreaded Application...

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international symposium on parallel and distributed processing (IPDPS)

作者： Justin R. Funston Kaoutar El Maghraoui Joefon Jann Pratap Pattnaik Alexandra Fedorova IBM Thomas J. Watson Research Center USA Simon Fraser University Canada

ISBN: (纸本)9781467309752

Simultaneous multithreading (SMT) increases CPU utilization and application performance in many circumstances, but it can be detrimental when performance is limited by application scalability or when there is significant contention for CPU resources. this paper describes an SMT-selection metric that predicts the change in application performance when the SMT level and number of application threads are varied. this metric is obtained online through hardware performance counters with little overhead, and allows the application or operating system to dynamically choose the best SMT level. We have validated the SMT-selection metric using a variety of benchmarks that capture various application characteristics on two different processor architectures. Our results show that the SMT-selection metric is capable of predicting the best SMT level for a given workload in 90% of the cases. the paper also shows that such a metric can be used with a scheduler or application optimizer to help guide its optimization decisions.

关键词： Benchmark testing Measurement Hardware Instruction sets Context Scalability Pipelines

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SPHINX: a fault-tolerant system for scheduling in dynamic grid environments

SPHINX: a fault-tolerant system for scheduling in dynamic gr...

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international symposium on parallel and distributed processing (IPDPS)

作者： J. In P. Avery R. Cavanaugh L. Chitnis M. Kulkarni S. Ranka University of Florida USA

A grid consists of high-end computational, storage, and network resources that, while known a priori, are dynamic with respect to activity and availability. Efficient scheduling of requests to use grid resources must adapt to this dynamic environment while meeting administrative policies. In this paper, we describe a framework called SPHINX that can administrate grid policies, and schedule complex and data intensive scientific applications. We present experimental results for several scheduling strategies that effectively utilize the monitoring and job-tracking information provided by SPHINX. these results demonstrate that SPHINX can effectively schedule work across a large number of distributed clusters that are owned by multiple units in a virtual organization in a fault-tolerant way in spite of the highly dynamic nature of the grid and complex policy issues. the novelty lies in use of effective monitoring of resources and job execution tracking in making scheduling decisions and fault-tolerance - something that is missed in today's grid environments.

关键词： Fault tolerant systems Dynamic scheduling Grid computing Processor scheduling Application software distributed computing Availability Fault tolerance Resource management Collaborative software

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Application for parallel disks for efficient handling of object-oriented databases

Application for parallel disks for efficient handling of obj...

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international symposium on parallel and distributed processing (IPDPS)

作者： Y.C. Chehadeh A.R. Hurson L.L. Miller S. Pakzad B.N. Jamoussi Department of Computer Science & Engineering Pennsylvania State University University Park PA USA Computer Science Department Iowa State University Ames IA USA

In today's workstation based environment, applications such as design databases, multimedia databases, and knowledge bases do not fit well into the relational data processing framework. the object-oriented data model has been proposed to model and process such complex databases. Due to the nature of the supported applications, object-oriented database systems need efficient mechanisms for the retrieval of complex objects and the navigation along the semantic links among objects. Object clustering and buffering have been suggested as efficient mechanisms for the retrieval of complex objects. However, to improve the efficiency of the aforementioned operations, one has to look at the recent advances in storage technology. this paper is an attempt to investigate the feasibility of using parallel disks for object-oriented databases. It analyzes the conceptual changes needed to map the clustering and buffering schemes proposed on the new underlying architecture. the simulation and performance evaluation of the proposed leveled-clustering and mapping schemes utilizing parallel I/O disks are presented and analyzed.< >

关键词： Object oriented databases Multimedia databases Relational databases Object oriented modeling Workstations Data processing Data models Database systems Information retrieval Navigation

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Generating Performance Models for Irregular applications

Generating Performance Models for Irregular Applications

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international symposium on parallel and distributed processing (IPDPS)

作者： Ryan D. Friese Nathan R. Tallent Abhinav Vishnu Darren J. Kerbyson Adolfy Hoisie Pacific Northwest National Laboratory

Many applications have irregular behavior - e.g., input-dependent solvers, irregular memory accesses, or unbiased branches - that cannot be captured using today's automated performance modeling techniques. We describe new hierarchical critical path analyses for the Palm model generation tool. To obtain a good tradeoff between model accuracy, generality, and generation cost, we combine static and dynamic analysis. To create a model's outer structure, we capture tasks along representative MPI critical paths. We create a histogram of critical tasks with parameterized task arguments and instance counts. To model each task, we identify hot instruction-level paths and model each path based on data flow, data locality, and microarchitectural constraints. We describe application models that generate accurate predictions for strong scaling when varying CPU speed, cache and memory speed, microarchitecture, and (with supervision) input data class. Our models' errors are usually below 8%; and always below 13%.

关键词： Analytical models Histograms Data models Load modeling Computational modeling Synchronization parallel processing

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Integrated Environment for Embedded Control Systems Design

Integrated Environment for Embedded Control Systems Design

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international symposium on parallel and distributed processing (IPDPS)

作者： Roman Bartosinski Zdenek. Hanzalek Petr Struzka Libor Waszniowski Czech Academy of Sci CR Karlovo nám.13 Czech Technical University CR UNIS Ltd Brno CR Czech Republic Karlovo nám.13 Czech Technical University Prague CR Czech Republic

the motivation of our work is to make a design tool for distributed embedded systems compliant with HIS and AUTOSAR. the tool is based on Processor Expert, a component oriented development environment supporting several hundreds of microcontrollers, and Matlab simulink which is the de-facto standard in the rapid prototyping of the control applications but it does not have an adequate HW support. the objective is to provide an integrated development environment for embedded controllers having distributed nature and real-time requirements. therefore we discuss the advantages of using an automatically generated code in the development cycle of the control embedded software. We present a developed block set and processor expert real-time target for Matlab real-time workshop embedded coder. the case study shows a development cycle for a servo control design.

关键词： Control systems Automatic control Embedded system Microcontrollers Standards development Prototypes Application software distributed control Automatic generation control Embedded software

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High-Performance distributed Multi-Model / Multi-Kernel Simulations: A Case-Study in Jungle Computing

High-Performance Distributed Multi-Model / Multi-Kernel Simu...

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ieee international symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Niels Drost Jason Maassen Maarten A.J. van Meersbergen Henri E. Bal F. Inti Pelupessy Simon Portegies Zwart Michael Kliphuis Henk A. Dijkstra Frank J. Seinstra Department of Computer Science VU University Amsterdam Netherlands Leiden Observatory Leiden University Leiden Netherlands Institute for Marine and Atmospheric research Utrecht Department of Physics and Astronomy University of Utrecht Utrecht Netherlands

High-performance scientific applications require more and more compute power. the concurrent use of multiple distributed compute resources is vital for making scientific progress. the resulting distributed system, a so-called Jungle Computing System, is both highly heterogeneous and hierarchical, potentially consisting of grids, clouds, stand-alone machines, clusters, desktop grids, mobile devices, and supercomputers, possibly with accelerators such as GPUs. One striking example of applications that can benefit greatly of Jungle Computing Systems are Multi-Model / Multi-Kernel simulations. In these simulations, multiple models, possibly implemented using different techniques and programming models, are coupled into a single simulation of a physical system. Examples include the domain of computational astrophysics and climate modeling. In this paper we investigate the use of Jungle Computing Systems for such Multi-Model / Multi-Kernel simulations. We make use of the software developed in the Ibis project, which addresses many of the problems faced when running applications on Jungle Computing Systems. We create a prototype Jungle-aware version of AMUSE, an astrophysical simulation framework. We show preliminary experiments with the resulting system, using clusters, grids, stand-alone machines, and GPUs.

关键词： Computational modeling Atmospheric modeling Middleware Couplers Supercomputers Kernel

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Automatic task scheduling/loop unrolling using dedicated RTR controllers in coarse grain reconfigurable architectures

Automatic task scheduling/loop unrolling using dedicated RTR...

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international symposium on parallel and distributed processing (IPDPS)

作者： P. Benoit L. Torres G. Sassatelli M. Robert G. Cambon L.I.R.M.M Montpellier France

When designing a SoC, matching the required performance both in terms of processing power and power consumption tends to become more and more challenging. Moreover, since the range of targeted applications for every single product is growing rapidly, employing reconfigurable accelerators makes more and more sense to this purpose. Coarse grain reconfigurable architectures bring an alternative providing interesting performance/flexibility trade-offs over traditional approaches. this paper presents an original method allowing to efficiently exploit dynamical parallelism at both loop-level and task-level, which remains rarely used. this method called DHM (dynamic hardware multiplexing) is based upon the use of a hardwired controller dedicated to run-time task scheduling and automatic loop unrolling. this paper shows that significant performance improvements can be achieved through combining both intra and inter-task parallelism. Principles and validations are exposed through a case study on a coarse grain reconfigurable architecture.

关键词： Automatic control Reconfigurable architectures parallel processing Hardware Runtime Energy consumption Signal processing Image processing Field programmable gate arrays Dynamic scheduling

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distributed electric field approximation

Distributed electric field approximation

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ieee international symposium on High Performance Computing Systems and applications (HPCS)

作者： D. Trybus Z. Kucerovsky A. Ieta T.E. Doyle University of Western Ontario ONT Canada

Grid or mesh techniques are frequently used to approximate continuous entities that behave in a wave or fluid-like fashion. Partial Differential Equations (PDEs) are usually involved in the description of such entities or processes. distributed parallel computation was used in various computer cluster configurations to calculate PDE solutions of electrostatic field. the study of the efficacy of the selected architecture using mesh techniques was intended. the match between the algorithm and the architecture in achieving maximum computational performance was also investigated. the developed architectures, algorithms, and findings are presented in the paper.

关键词： Grid computing Clustering algorithms Concurrent computing distributed computing Computer architecture Linux Partitioning algorithms Partial differential equations Electrostatics parallel processing

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