Journal: Computing

Abbreviation

Computing

Publisher

Springer

Journal Volumes

ISSN

0010-485X
1436-5057

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Publications 1 - 10 of 13
  • On Optimal Cuts of Hyperrectangles
    Item type: Journal Article
    d'Amore, F.; Nguyen, V.H.; Roos, T.; et al. (1995)
    Computing
  • Multilevel preconditioned augmented Lagrangian techniques for 2nd order mixed problems
    Item type: Journal Article
    Hiptmair, R.; Schiekofer, R.; Wohlmuth, B. (1996)
    Computing
  • On Some Union and Intersection Problems for Polygons with Fixed Orientations
    Item type: Journal Article
    Widmayer, Peter; Wu, Y.F.; Schlag, Martine D.F.; et al. (1986)
    Computing
  • MPI + MPI: a new hybrid approach to parallel programming with MPI plus shared memory
    Item type: Journal Article
    Hoefler, Torsten; Dinan, James; Buntinas, Darius; et al. (2013)
    Computing
  • Sparse Finite Elements for Stochastic Elliptic Problems – Higher Order Moments
    Item type: Journal Article
    Schwab, Christoph; Todor, Radu Alexandru (2003)
    Computing
    We define the higher order moments associated to the stochastic solution of an elliptic BVP in D⊂ℝd with stochastic input data. We prove that the k-th moment solves a deterministic problem in D k⊂ℝdk, for which we discuss well-posedness and regularity. We discretize the deterministic k-th moment problem using sparse grids and, exploiting a spline wavelet basis, we propose an efficient algorithm, of logarithmic-linear complexity, for solving the resulting system.
  • Preface
    Item type: Other Journal Item
    Solin, Pavel; Karban, Pavel; Schnepp, Sascha; et al. (2013)
    Computing
  • Application-oriented ping-pong benchmarking
    Item type: Journal Article
    Schneider, Timo; Gerstenberger, Robert; Hoefler, Torsten (2014)
    Computing
  • Non-reflecting boundary conditions for Maxwell`s equations
    Item type: Journal Article
    Hiptmair, Ralf; Schädle, Achim (2003)
    Computing
  • Visualizing big network traffic data using frequent pattern mining and hypergraphs
    Item type: Journal Article
    Glatz, Eduard; Mavromatidis, Stelios; Ager, Bernhard; et al. (2014)
    Computing
    Visualizing communication logs, like NetFlow records, is extremely useful for numerous tasks that need to analyze network traffic traces, like network planning, performance monitoring, and troubleshooting. Communication logs, however, can be massive, which necessitates designing effective visualization techniques for large data sets. To address this problem, we introduce a novel network traffic visualization scheme based on the key ideas of (1) exploiting frequent itemset mining (FIM) to visualize a succinct set of interesting traffic patterns extracted from large traces of communication logs; and (2) visualizing extracted patterns as hypergraphs that clearly display multi-attribute associations. We demonstrate case studies that support the utility of our visualization scheme and show that it enables the visualization of substantially larger data sets than existing network traffic visualization schemes based on parallel-coordinate plots or graphs. For example, we show that our scheme can easily visualize the patterns of more than 41 million NetFlow records. Previous research has explored using parallel-coordinate plots for visualizing network traffic flows. However, such plots do not scale to data sets with thousands of even millions of flows.
  • Application-oriented ping-pong benchmarking: how to assess the real communication overheads
    Item type: Journal Article
    Schneider, Timo; Gerstenberger, Robert; Hoefler, Torsten (2014)
    Computing
    Moving data between processes has often been discussed as one of the major bottlenecks in parallel computing—there is a large body of research, striving to improve communication latency and bandwidth on different networks, measured with ping-pong benchmarks of different message sizes. In practice, the data to be communicated generally originates from application data structures and needs to be serialized before communicating it over serial network channels. This serialization is often done by explicitly copying the data to communication buffers. The message passing interface (MPI) standard defines derived datatypes to allow zero-copy formulations of non-contiguous data access patterns. However, many applications still choose to implement manual pack/unpack loops, partly because they are more efficient than some MPI implementations. MPI implementers on the other hand do not have good benchmarks that represent important application access patterns. We demonstrate that the data serialization can consume up to 80 % of the total communication overhead for important applications. This indicates that most of the current research on optimizing serial network transfer times may be targeted at the smaller fraction of the communication overhead. To support the scientific community, we extracted the send/recv-buffer access patterns of a representative set of scientific applications to build a benchmark that includes serialization and communication of application data and thus reflects all communication overheads. This can be used like traditional ping-pong benchmarks to determine the holistic communication latency and bandwidth as observed by an application. It supports serialization loops in C and Fortran as well as MPI datatypes for representative application access patterns. Our benchmark, consisting of seven micro-applications, unveils significant performance discrepancies between the MPI datatype implementations of state of the art MPI implementations. Our micro-applications aim to provide a standard benchmark for MPI datatype implementations to guide optimizations similarly to the established benchmarks SPEC CPU and Livermore Loops.
Publications 1 - 10 of 13