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检索条件"任意字段=Proceedings of the eleventh workshop on Parallel and distributed simulation"

共 1191 条记录，以下是31-40 订阅

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Evaluation of Programming Models to Address Load Imbalance on distributed Multi-Core CPUs: A Case Study with Block Low-Rank Factorization

Evaluation of Programming Models to Address Load Imbalance o...

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IEEE/ACM parallel Applications workshop / Alternatives To MPI+X workshop (PAW-ATM)

作者： Pei, Yu Bosilca, George Yamazaki, Ichitaro Ida, Akihiro Dongarra, Jack Univ Tennessee Innovat Comp Lab Knoxville TN 37996 USA Sandia Natl Labs POB 5800 Albuquerque NM 87185 USA Univ Tokyo Informat Technol Ctr Tokyo Japan

ISBN: (纸本)9781728159799

To minimize data movement, many parallel applications statically distribute computational tasks among the processes. However, modern simulations often encounters irregular computational tasks whose computational loads change dynamically at runtime or are data dependent. As a result, load imbalance among the processes at each step of simulation is a natural situation that must be dealt with at the programming level. The de facto parallel programming approach, flat MPI (one process per core), is hardly suitable to manage the lack of balance, imposing significant idle time on the simulation as processes have to wait for the slowest process at each step of simulation. One critical application for many domains is the LU factorization of a large dense matrix stored in the Block Low-Rank (BLR) format. Using the low-rank format can significantly reduce the cost of factorization in many scientific applications, including the boundary element analysis of electrostatic field. However, the partitioning of the matrix based on underlying geometry leads to different sizes of the matrix blocks whose numerical ranks change at each step of factorization, leading to the load imbalance among the processes at each step of factorization. We use BLR LU factorization as a test case to study the programmability and performance of five different programming approaches: (1) flat MPI, (2) Adaptive MPI (Charm++), (3) MPI + OpenMP, (4) parameterized task graph (PTG), and (5) dynamic task discovery (DTD). The last two versions use a task-based paradigm to express the algorithm;we rely on the PaRSEC runtime system to execute the tasks. We first point out programming features needed to efficiently solve this category of problems, hinting at possible alternatives to the MPI+X programming paradigm. We then evaluate the programmability of the different approaches, detailing our experience implementing the algorithm using each of the models. Finally, we show the performance result on the Intel Haswell-

关键词： Factorization

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2nd workshop on Software Challenges to Exascale Computing, SCEC 2018

2nd Workshop on Software Challenges to Exascale Computing, S...

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2nd workshop on Software Challenges to Exascale Computing, SCEC 2018

ISBN: (纸本)9789811377280

The proceedings contain 10 papers. The special focus in this conference is on Software Challenges to Exascale Computing. The topics include: High level file system and parallel I/O optimization of DNS code;Hybrid parallelization of particle in cell monte carlo collision (PIC-MCC) algorithm for simulation of low temperature plasmas;a review of dimensionality reduction in high-dimensional data using multi-core and many-core architecture;Performance analysis of computational neuroscience software NEURON on knights corner many core processors;Overcoming MPI communication overhead for distributed community detection;Analyzing IO usage patterns of user jobs to improve overall HPC system efficiency;scalable software infrastructure for integrating supercomputing with volunteer computing and cloud computing;high-level approaches for leveraging deep-memory hierarchies on modern supercomputers.

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proceedings of EduHPC 2018: workshop on Education for High-Performance Computing, Held in conjunction with SC 2018: The International Conference for High Performance Computing, Networking, Storage and Analysis

Proceedings of EduHPC 2018: Workshop on Education for High-P...

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2018 IEEE/ACM workshop on Education for High-Performance Computing, EduHPC 2018

ISBN: (纸本)9781728101903

The proceedings contain 9 papers. The topics discussed include: teaching HPC systems and parallel programming with small-scale clusters;Jupyter notebooks and user-friendly HPC access;SMPI courseware: teaching distributed-memory computing with MPI in simulation;employing student retention strategies for an introductory GPU programming course;filling the gap between education and industry: evidence-based methods for introducing undergraduate students to HPC;evaluating the wide area classroom after 10,500 HPC students;a one year retrospective on a MOOC in parallel, concurrent, and distributed programming in Java;towards developing a repository of logical errors observed in parallel code for teaching ode correctness;and peachy parallel assignments (EduHPC 2018).

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Peachy parallel Assignments (EduHPC 2018)

Peachy Parallel Assignments (EduHPC 2018)

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IEEE/ACM workshop on Education for High-Performance Computing (EduHPC)

作者： Ayguade, Eduard Alvarez, Lluc Banchelli, Fabio Burtscher, Martin Gonzalez-Escribano, Arturo Gutierrez, Julian Joiner, David A. Kaeli, David Previlon, Fritz Rodriguez-Gutiez, Eduardo Bunde, David P. Univ Politecn Cataluna Barcelona Supercomp Ctr Barcelona Spain Texas State Univ San Marcos TX USA Univ Valladolid Valladolid Spain Northeastern Univ Boston MA 02115 USA Kean Univ Union NJ USA Knox Coll Galesburg IL USA

ISBN: (纸本)9781728101903

Peachy parallel Assignments are a resource for instructors teaching parallel and distributed programming. These are high-quality assignments, previously tested in class, that are readily adoptable. This collection of assignments includes implementing a subset of OpenMP using pthreads, creating an animated fractal, image processing using histogram equalization, simulating a storm of high-energy particles, and solving the wave equation in a variety of settings. All of these come with sample assignment sheets and the necessary starter code.

关键词： parallel computing education High-Performance Computing education parallel programming OpenMP Pthreads CUDA Compiler and runtime systems Fractals Image processing Particle simulation Wave equation Peachy Assignments

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CEUR workshop proceedings

CEUR Workshop Proceedings

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Selected Papers of the 8th International Conference "distributed Computing and Grid-Technologies in Science and Education", GRID 2018

The proceedings contain 122 papers. The topics discussed include: the CMS TIER1 at JINR: five years of operations;CRIC: the information system for LHC distributed computing;the atlas event index and its evolution based on apache kudu storage;big data as the future of information technology;the designing of cloud infrastructure consisting of geographically distributed data centers;multicomponent cluster management system for the computing center at IHEP;RUNNET: infrastructural and service basis of the national research and education network of the Russian Federation;virtual testbed as a case for big data;and properties of the parallel discrete event simulation algorithms on small-world communication networks.

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SMPI Courseware: Teaching distributed-Memory Computing with MPI in simulation

SMPI Courseware: Teaching Distributed-Memory Computing with ...

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IEEE/ACM workshop on Education for High-Performance Computing (EduHPC)

作者： Casanova, Henri Legrand, Arnaud Quinson, Martin Suter, Frederic Univ Hawaii Manoa Informat & Comp Sci Dept Honolulu HI 96822 USA Univ Grenoble Alpes CNRS INRIA INPLIG Grenoble France Univ Rennes 1 CNRS IRISA Lab ENS RennesInria Rennes France ENS Lyon LIP INRIA IN2P3 Comp CtrCNRS Lyon France

ISBN: (纸本)9781728101903

It is typical in High Performance Computing (HPC) courses to give students access to HPC platforms so that they can benefit from hands-on learning opportunities. Using such platforms, however, comes with logistical and pedagogical challenges. For instance, a logistical challenge is that access to representative platforms must be granted to students, which can be difficult for some institutions or course modalities;and a pedagogical challenge is that hands-on learning opportunities are constrained by the configurations of these platforms. A way to address these challenges is to instead simulate program executions on arbitrary HPC platform configurations. In this work we focus on simulation in the specific context of distributed-memory computing and MPI programming education. While using simulation in this context has been explored in previous works, our approach offers two crucial advantages. First, students write standard MPI programs and can both debug and analyze the performance of their programs in simulation mode. Second, large-scale executions can be simulated in short amounts of time on a single standard laptop computer. This is possible thanks to SMPI, an MPI simulator provided as part of SimGrid. After detailing the challenges involved when using HPC platforms for HPC education and providing background information about SMPI, we present SMPI Courseware. SMPI Courseware is a set of in-simulation assignments that can be incorporated into HPC courses to provide students with hands-on experience for distributed-memory computing and MPI programming learning objectives. We describe some these assignments, highlighting how simulation with SMPI enhances the student learning experience.

关键词： High Performance Computing Education parallel Computing Education Message Passing Interface simulation

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Non-collective Scalable Global Network Based on Local Communications 9

Non-collective Scalable Global Network Based on Local Commun...

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9th IEEE/ACM workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (scalA)

作者： Berghoff, Marco Kondov, Ivan Karlsruhe Inst Technol Steinbuch Ctr Comp Karlsruhe Germany

ISBN: (纸本)9781728101767

To efficiently perform collective communications in current high-performance computing systems is a time-consuming task. With future exascale systems, this communication time will be increased further. However, global information is frequently required in various physical models. By exploiting domain knowledge of the model behaviors globally needed information can be distributed more efficiently, using only peer-to-peer communication which spread the information to all processes asynchronous during multiple communication steps. In this article, we introduce a multi-hop based Manhattan Street Network (MSN) for global information exchange and show the conditions under which a local neighbor exchange is sufficient for exchanging distributed information. Besides the MSN, in various models, global information is only needed in a spatially limited region inside the simulation domain. Therefore, a second network is introduced, the local exchange network, to exploit this spatial assumption. Both non-collective global exchange networks are implemented in the massively parallel NAStJA framework. Based on two models, a phase-field model for droplet simulations and the cellular Potts model for biological tissue simulations, we exemplary demonstrate the wide applicability of these networks. Scaling tests of the networks demonstrate a nearly ideal scaling behavior with an efficiency of over 90%. Theoretical prediction of the communication time on future exascale systems shows an enormous advantage of the presented exchange methods of O(1) by exploiting the domain knowledge.

关键词： peer-to-peer communication distributed memory scalable parallel algorithms massive-parallel performance network protocol stencil code phase-field method

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21st International workshop on Job Scheduling Strategies for parallel Processing, JSSPP 2017

21st International Workshop on Job Scheduling Strategies for...

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21st International workshop on Job Scheduling Strategies for parallel Processing, JSSPP 2017

ISBN: (纸本)9783319773971

The proceedings contain 10 papers. The special focus in this conference is on. The topics include: Analysis of Mixed Workloads from Shared Cloud Infrastructure;Tuning EASY-Backfilling Queues;don’t Hurry Be Happy: A Deadline-Based Backfilling Approach;Supporting Real-Time Jobs on the IBM Blue Gene/Q: simulation-Based Study;towards Efficient Resource Allocation for distributed Workflows Under Demand Uncertainties;programmable In Situ System for Iterative Workflows;A Data Structure for Planning Based Workload Management of Heterogeneous HPC Systems;ScSF: A Scheduling simulation Framework.

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Accelerating Octo-Tiger: Stellar Mergers on Intel Knights Landing with HPX 18

Accelerating Octo-Tiger: Stellar Mergers on Intel Knights La...

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International workshop on OpenCL (IWOCL)

作者： Pfander, David Daiss, Gregor Marcello, Dominic Kaiser, Hartmut Pflueger, Dirk Univ Stuttgart Stuttgart Germany Louisiana State Univ Baton Rouge LA 70803 USA

ISBN: (纸本)9781450364393

The optimization of performance of complex simulation codes with high computational demands, such as Octo-Tiger, is an ongoing challenge. Octo-Tiger is an astrophysics code simulating the evolution of star systems based on the fast multipole method using adaptive octrees as the central data structure. Octo-Tiger was implemented using high-level C++ libraries, specifically HPX and Vc, which allows its use on different hardware platforms. Recently, we have demonstrated excellent scalability in a distributed setting. In this paper, we study the node-level performance of Octo-Tiger on an Intel Knights Landing platform. We focus on Octo-Tiger's fast multipole method, as it is the computationally most demanding component. By using HPX and a futurization approach, we can efficiently traverse the adaptive octrees in parallel. On the core-level, threads process sub-grids using multiple 1074-element stencils. In numerical experiments, simulating the time evolution of a rotating star on an Intel Xeon Phi 7250 Knights Landing processor, Octo-Tiger shows good parallel efficiency. For the fast multipole algorithm, we achieved up to 408 GFLOPS, resulting in a speedup of 2x compared to a 24-core Skylake-SP platform, using the same high-level abstractions.

关键词： compute accelerators performance engineering parallel programming models high-level abstractions astrophysical simulations

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Full-wave simulation of the earthquake initiaion process 8

Full-wave simulation of the earthquake initiaion process

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Selected Papers of the 8th International Conference "distributed Computing and Grid-Technologies in Science and Education", GRID 2018

作者： Golubev, V.I. Golubeva, Yu.A. Moscow Institute of Physics and Technology 9 Institytsky Pereylok St. Dolgoprudny Moscow Region141700 Russia

The earthquake process leads to the destruction of building and has a significant influence on human life. Nowadays there is no methods to forecast it with the 100 % precision. Scientists around the world make efforts to invent numerical methods for simulation of the earthquake process. With the rapid development of high-performance computing systems more complex physical and mathematical models may be used. In this paper we describe the experience of full-wave seismic waves simulation in layered inhomogeneous medium The simple earthquake source model was used in 3D case. It allows us to reproduce the anisotropy of the registered seismic signal. The govern system of equations are solved numerically with the grid-characteristic method on structured meshes. To achieve a reasonable computation time, the parallel version of algorithms was applied. The spatial distribution of displacements on the sea surface was successfully simulated. © 2018 Vasily Golubev, Yulia Golubeva.

关键词： Earthquakes

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