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Event-Action Mappings for parallel Tools Infrastructures 21st

Event-Action Mappings for Parallel Tools Infrastructures

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21st international conference on parallel and distributed Computing (Euro-Par)

作者： Hilbrich, Tobias Schulz, Martin Brunst, Holger Protze, Joachim de Supinski, Bronis R. Mueller, Matthias S. Tech Univ Dresden D-01062 Dresden Germany Lawrence Livermore Natl Lab Livermore CA 94551 USA Rhein Westfal TH Aachen D-52056 Aachen Germany JARA High Performance Comp D-52062 Aachen Germany

ISBN: (纸本)9783662480960;9783662480953

The development of applications for High Performance Computing (HPC) systems is a challenging task. Development steps such as optimization, tuning, porting, and debugging often motivate the use of tools, many of which operate at application runtime. Current trends in the HPC community, such as increasing compute core counts and the advent of new programming paradigms challenge the development of applications, as well as the development of runtime tools. parallel tools infrastructures can help to simplify the development and adaption of runtime tools by reducing development time and increasing applicability. They can provide reusable tool components, communication services, and abstractions for scalable tools, which preserve lessons learned from existing tools projects. This paper defines an abstraction for a highly integrated infrastructure, which we implement in a prototype that targets MPI applications. Our abstraction enables an incorporation of common tasks such as instrumentation, i.e., observing application behavior, with existing concepts for tool communication, while at the same time enabling scalability. A formal description of our abstraction allows us to highlight its design and to differentiate it from alternatives, so tool developers have a clear understanding of the high-level approach that our infrastructure follows. Existing prototype tools that are based on this infrastructure demonstrate applicability at 1,024 and 16,384 processes respectively.

关键词： Abstracting

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Coordinating collaborative interactions in web-based mobile applications 15

Coordinating collaborative interactions in web-based mobile ...

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10th ACM international conference on Interactive Tabletops and Surfaces, ITS 2015

作者： Kambona, Kennedy Hoste, Lode Boix, Elisa De Meuter, Wolfgang Software Languages Lab Vrije Universiteit Brussel Brussels Belgium

ISBN: (纸本)9781450338998

Mobile applications for interactive surfaces that utilize the web as a platform now have the ability to provide richer interactions hitherto unrealized by running them on isolated devices. These modern applications can now support proximal and remote collaborative interactions for multiple clients simultaneously connected to each other. Most technologies however currently lack programming language abstractions for coordinating complex interactions, such as to define, detect and combine complex events coming from multiple clients or other software entities. Furthermore, they lack the expressiveness required to support non-trivial levels of collaborative interactions for connected clients. In this paper we identify two software mechanisms that web-based mobile applications should provide to support the development of collaborative interactions: distributed event composition and group coordination. We present the Mingo framework, which provides dedicated coordination programmer constructs for these two mechanisms by blending techniques common in complex event processing and group communication. Consequently, we validate our framework by implementing a mobile drawing application with support for collaborative interactions and evaluate it by comparing it with a related implementation. © Copyright 2015 ACM.

关键词： Websites

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Accelerating Lattice Boltzmann applications with OpenACC 21st

Accelerating Lattice Boltzmann Applications with OpenACC

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21st international conference on parallel and distributed Computing (Euro-Par)

作者： Calore, Enrico Kraus, Jiri Schifano, Sebastiano Fabio Tripiccione, Raffaele Univ Ferrara Dip Fis & Sci Terra I-44100 Ferrara Italy Ist Nazl Fis Nucl Ferrara Italy NVIDIA GmbH Wurselen Germany Univ Ferrara Dip Matemat & Informat I-44100 Ferrara Italy

ISBN: (纸本)9783662480960;9783662480953

An increasingly large number of HPC systems rely on heterogeneous architectures combining traditional multi-core CPUs with power efficient accelerators. Designing efficient applications for these systems has been troublesome in the past as accelerators could usually be programmed only using specific programming languages - such as CUDA - threatening maintainability, portability and correctness. Several new programming environments try to tackle this problem;among them OpenACC offers a high-level approach based on directives. In OpenACC, one annotates existing C, C++ or Fortran codes with compiler directive clauses to mark program regions to offload and run on accelerators and to identify available parallelism. This approach directly addresses code portability, leaving to compilers the support of each different accelerator, but one has to carefully assess the relative costs of potentially portable approach versus computing efficiency. In this paper we address precisely this issue, using as a test-bench a massively parallel Lattice Boltzmann code. We implement and optimize this multi-node code using OpenACC and OpenMPI. We also compare performance with that of the same algorithm written in CUDA, OpenCL and C for GPUs, Xeon-Phi and traditional multi-core CPUs, and characterize through an accurate time model its scaling behavior on a large cluster of GPUs.

关键词： OpenACC OpenMPI Lattice Boltzmann methods Accelerator computing Performance analysis

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Energy-Performance Tradeoffs for HPC applications on Low Power Processors

Energy-Performance Tradeoffs for HPC Applications on Low Pow...

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21st international conference on parallel and distributed Computing (Euro-Par)

作者： Calore, Enrico Schifano, Sebastiano Fabio Tripiccione, Raffaele Univ Ferrara Dipartimento Fis & Sci Terra I-44100 Ferrara Italy INFN Ferrara Italy Univ Ferrara Dipartimento Matemat & Informat I-44100 Ferrara Italy

ISBN: (纸本)9783319273082;9783319273075

Energy efficiency is becoming more and more important in the HPC field;high-end processors are quickly evolving towards more advanced power-saving and power-monitoring technologies. On the other hand, low-power processors, designed for the mobile market, attract interest in the HPC area for their increasing computing capabilities, competitive pricing and low power consumption. In this work we study energy and computing performances of a Tegra K1 mobile processor using an HPC Lattice Boltzmann application as a benchmark. We run this application on the ARM Cortex-A15 CPU and on the GK20A GPU, both available in this processor. Our analysis uses time-accurate measurements, obtained by a simple custom-developed current monitor. We discuss several energy and performance metrics, interesting per se and also in view of a prospective use of these processors in a HPC context.

关键词： Energy efficiency

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A Load-distributed Linpack Implementation for Heterogeneous Clusters 17

A Load-distributed Linpack Implementation for Heterogeneous ...

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2015 IEEE 17th international conference on High Performance Computing and Communications (HPCC)

作者： Rohr, David Lindenstruth, Volker Frankfurt Inst Adv Studies Ruth Moufang Str 1 D-60438 Frankfurt Germany

ISBN: (纸本)9781479989379

In recent years, heterogeneous HPC systems, which combine traditional processors with accelerator cards such as GPUs, have been shown to deliver superior performance and power efficiency. Since different scientific problems pose different demands on the computer architecture, some general purpose supercomputers consist of different types of nodes, where each type is suited best for certain applications. Such clusters with inter-node heterogeneity (different types of nodes) on top of intra-node heterogeneity (different processors inside one node) consist of compute nodes with different compute performances. The standard implementation of the Linpack benchmark, HPL, distributes the workload evenly among all processes and thus cannot exploit the cluster's full potential if the nodes have unequal performance. This paper presents a new feature of our HPL-GPU implementation which allows a balanced fine-tuned workload distribution among all compute nodes taking into account their individual compute capabilities. We present results on some nodes of different speed-grades on the LOEWE-CSC cluster and demonstrate that our implementation can utilize all nodes of a heterogeneous configuration efficiently showing only about 3% granularity loss.

关键词： computer architecture mainframes parallel machines software libraries HPL-GPU implementation LOEWE-CSC cluster Linpack benchmark accelerator cards balanced fine-tuned workload distribution compute nodes general purpose supercomputers heterogeneous HPC systems heterogeneous clusters internode heterogeneity intranode heterogeneity load-distributed Linpack implementation Benchmark testing Graphics processing units Hardware Niobium Standards Supercomputers GPU HPC HPL HPL-GPU Heterogeneous LOEWE-CSC Linpack

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Comparison of Clustering techniques of Multiple Partial Discharge Sources in High Voltage Transformer Windings 11

Comparison of Clustering Techniques of Multiple Partial Disc...

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2015 IEEE 11th international conference on the Properties and applications of Dielectric Materials (ICPADM)

作者： Ali, N. H. Nik Goldsmith, W. Hunter, J. A. Lewin, P. L. Rapisarda, P. Univ Southampton Tony Davies High Voltage Lab Southampton SO9 5NH Hants England Univ Southampton Commun Signal Proc & Control Southampton SO9 5NH Hants England

ISBN: (纸本)9781479989034

Modern high voltage ( HV) insulation systems consist of multiple dielectric media - multi-source partial discharge ( PD) data discrimination is required. The ability to accurately distinguish between the PD signals generated from different sources is seen as a critical function of future diagnostic systems. Two model PD sources were utilized in this investigation to replicate void and surface discharges. The proposed processing technique relies on the assumption that the PD pulses generated from different sources exhibit unique waveform characteristics. Several clustering techniques have been employed to identify and separate multiple PD sources recently. However, for further analysis, the techniques used must produce a significant separation between the clustered data as the phase resolved patterns produced by multiple PD sources overlap - inhibiting automated classification. An experiment has been designed to activate a pair of PD sources and inject the signals simultaneously into an HV transformer winding. After the PD pulses were extracted from the measurement data recorded using two wideband radio frequency current transformers ( RFCTs) positioned at the neutral to earth point and the bushing tap-point to earth. Principle Component Analysis ( PCA) and t-distributed stochastic neighbor embedding ( t-SNE) were applied to the Wavelet Energy ( WE) data and their performance at discriminating between the two PD sources assessed.

关键词： clustering multiple partial discharge transformer winding

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A Data-oriented Method for Scheduling Dependent Tasks on High-density Multi-GPU Systems 17

A Data-oriented Method for Scheduling Dependent Tasks on Hig...

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2015 IEEE 17th international conference on High Performance Computing and Communications (HPCC)

作者： Zhang, Peng Gao, Yuxiang Qiu, Meikang SUNY Stony Brook Dept Biomed Engn Stony Brook NY 11794 USA Cray Inc Cluster Solut Dept San Jose CA USA Pace Univ Dept Comp Sci New York NY 10038 USA

ISBN: (纸本)9781479989379

The rapidly-changing computer architectures, though improving the performance of computers, have been challenging the programming environments for efficiently harnessing the potential of novel architectures. In this area, though the high-density multi-GPU architecture enabled unparalleled performance advantage of dense GPUs in a single server, it has increased the difficulty for scheduling diversified and dependent tasks. We therefore propose a data-oriented method for scheduling dependent tasks for this architecture while providing its implementation. In our method, we model a parallel program as a collection of data-dependent tasks for which data dependencies are managed by an expressive matrix. Accordingly, we develop a hierarchical scheduler infrastructure for our model. In this, a top scheduler is built for querying the data-dependency matrix;three downstream schedulers for queuing computation tasks that are exclusively assigned to processor, accelerator or either;and a multitude of bottom schedulers each for providing a processing element with assigned tasks. We experiment our scheduler for examples of Strassen matrix multiplication and Cholesky matrix inversion algorithms on a computer that has 8 Tesla K40 GPUs. The results show that our method is capable of offering the efficient task parallelism while fulfilling the complex task dependencies. When advanced task-oriented schedulers have been widely designed for distributed systems, a lightweight data-driven scheduler could be an alternative and handy approach that can handle the dependent yet diversified tasks of data-intensive applications for the novel high-density multi-accelerator system.

关键词： data scheduling task scheduling parallel computing heterogeneous multi-GPU systems

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Teaching parallel Programming in Interdisciplinary Studies

Teaching Parallel Programming in Interdisciplinary Studies

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21st international conference on parallel and distributed Computing (Euro-Par)

作者： Cesar, Eduardo Cortes, Ana Espinosa, Antonio Margalef, Tomas Carlos Moure, Juan Sikora, Anna Suppi, Remo Univ Autonoma Barcelona Comp Architecture & Operating Syst Dept Cerdanyola Del Valles 08193 Spain

ISBN: (纸本)9783319273082;9783319273075

Nowadays many fields of science and engineering are evolving by the joint contribution of complementary fields. Computer science, and especially high performance computing, has become a key factor in the development of many research fields, establishing a new paradigm called computational science. Researchers and professionals from many different fields require a knowledge of high performance computing, including parallel programming, to develop a fruitful work in their particular field. So, at Universitat Autonoma of Barcelona, an interdisciplinary master on Modeling for science and engineering was started 5 years ago to provide a deep knowledge on the application of modeling and simulation to graduate students on different fields (Mathematics, Physics, Chemistry, Engineering, Geology, etc.). In this master, parallel Programming appears as a compulsory subject, because it is a key topic for them. The concepts learnt in parallel programming must be applied to real applications. Therefore, a subject on Applied Modelling and Simulation has also been included. In this paper, the experience on teaching parallel programming in such interdisciplinary master is shown.

关键词： parallel programming Message passing Shared memory GPUs MPI OpenMP CUDA

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Performance Impacts with Reliable parallel File Systems at Exascale Level 21st

Performance Impacts with Reliable Parallel File Systems at E...

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21st international conference on parallel and distributed Computing (Euro-Par)

作者： Nou, Ramon Miranda, Alberto Cortes, Toni Barcelona Supercomp Ctr Barcelona Spain Tech Univ Catalonia Barcelona Spain

ISBN: (纸本)9783662480960;9783662480953

The introduction of Exascale storage into production systems will lead to an increase on the number of storage servers needed by parallel file systems. In this scenario, parallel file system designers should move from the current replication configurations to the more space and energy efficient erasure-coded configurations between storage servers. Unfortunately, the current trends on energy efficiency are directed to creating less powerful clients, but a larger number of them (light-weight Exascale nodes), increasing the frequency of write requests and therefore creating more parity update requests. In this paper, we investigate RAID-5 and RAID-6 parity-based reliability organizations in Exascale storage systems. We propose two software mechanisms to improve the performance of write requests. The first mechanism reduces the number of operations to update a parity block, improving the performance of writes up to 200 %. The second mechanism allows applications to notify when reliability is needed by the data, delaying the parity calculation and improving the performance up to a 300 %. Using our proposals, traditional replication schemes can be replaced by reliability models like RAID-5 or RAID-6 without the expected performance loss.

关键词： Reliability

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Towards Increasing the Error Handling Time Window in Large-Scale distributed Systems using Console and Resource Usage Logs 14

Towards Increasing the Error Handling Time Window in Large-S...

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13th IEEE international Symposium on parallel and distributed processing with applications

作者： Gurumdimma, Nentawe Jhumka, Arshad Liakata, Maria Chuah, Edward Browne, James Univ Warwick Dept Comp Sci Coventry CV4 7AL W Midlands England Univ Texas Austin Austin TX 78712 USA

ISBN: (纸本)9781467379526

Resource-intensive applications such as scientific applications require the architecture or system on which they execute to display a very high level of dependability to reduce the impact of faults. Typically, the state of the underlying system is captured through messages that are recorded in a log file, which has been proven useful to system administrators in understanding the root-causes of system failures (and for their subsequent debugging). However, the time window between when the first error message is detected in the log file and time of the ensuing failure may not be large enough to allow the administrators to save the state of the running application, which will result in lost execution time. We thus address this fundamental question: Is it possible to extend this time window? The answer is positive: We show that, by using (i) resource usage logs to track anomalous resource usage and (ii) error logs to identify root-causes of system failures, it is possible to increase the time window, on average, by 50 minutes. These files were those obtained for the Ranger Supercomputer from TACC(1). We achieve this by applying anomaly detection techniques on resource usage data and conducting a root-cause analysis on error log files.

关键词： Anomaly detection Resource usage data Error logs PCA Root-cause analysis large-scale HPC systems

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