Tools for High Performance Computing 2011

1. Front Matter

   Pages i-xvi

   PDF

2. Creating a Tool Set for Optimizing Topology-Aware Node Mappings

   • Martin Schulz, Abhinav Bhatele, Peer-Timo Bremer, Todd Gamblin, Katherine Isaacs, Joshua A. Levine et al.

   Pages 1-12

3. Using Sampling to Understand Parallel Program Performance

   • Nathan R. Tallent, John Mellor-Crummey

   Pages 13-25

4. likwid-bench: An Extensible Microbenchmarking Platform for x86 Multicore Compute Nodes

   • Jan Treibig, Georg Hager, Gerhard Wellein

   Pages 27-36

5. An Open-Source Tool-Chain for Performance Analysis

   • Kevin Coulomb, Augustin Degomme, Mathieu Faverge, François Trahay

   Pages 37-48

6. Debugging CUDA Accelerated Parallel Applications with TotalView

   • Chris Gottbrath, Royd Lüdtke

   Pages 49-61

7. Advanced Memory Checking Frameworks for MPI Parallel Applications in Open MPI

   • Shiqing Fan, Rainer Keller, Michael Resch

   Pages 63-78

8. Score-P: A Joint Performance Measurement Run-Time Infrastructure for Periscope, Scalasca, TAU, and Vampir

   • Andreas Knüpfer, Christian Rössel, Dieter an Mey, Scott Biersdorff, Kai Diethelm, Dominic Eschweiler et al.

   Pages 79-91

9. Trace-Based Performance Analysis for Hardware Accelerators

   • Guido Juckeland

   Pages 93-104

10. Folding: Detailed Analysis with Coarse Sampling

    • Harald Servat, Germán Llort, Judit Giménez, Kevin Huck, Jesús Labarta

    Pages 105-118

11. Advances in the TAU Performance System

    • Allen Malony, Sameer Shende, Wyatt Spear, Chee Wai Lee, Scott Biersdorff

    Pages 119-130

12. Temanejo: Debugging of Thread-Based Task-Parallel Programs in StarSS

    • Rainer Keller, Steffen Brinkmann, José Gracia, Christoph Niethammer

    Pages 131-137

13. HiFlow3: A Hardware-Aware Parallel Finite Element Package

    • H. Anzt, W. Augustin, M. Baumann, T. Gengenbach, T. Hahn, A. Helfrich-Schkarbanenko et al.

    Pages 139-151

14. Back Matter

    Pages 153-154

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The proceedings of the 5th International Workshop on Parallel Tools for High Performance Computing provide an overview on supportive software tools and environments in the fields of System Management, Parallel Debugging and Performance Analysis. In the pursuit to maintain exponential growth for the performance of high performance computers the HPC community is currently targeting Exascale Systems. The initial planning for Exascale already started when the first Petaflop system was delivered. Many challenges need to be addressed to reach the necessary performance. Scalability, energy efficiency and fault-tolerance need to be increased by orders of magnitude. The goal can only be achieved when advanced hardware is combined with a suitable software stack. In fact, the importance of software is rapidly growing. As a result, many international projects focus on the necessary software.

• MPI
• accelerators
• parallel computing
• parallel debugging
• performance tuning
• algorithm analysis and problem complexity

• , Zentrum für Informationsdienste, Technische Universität Dresden, Dresden, Germany

  Holger Brunst, Matthias S. Müller, Wolfgang E. Nagel

• , Höchstleistungsrechenzentrum, Universität Stuttgart, Stuttgart, Germany

  Michael M. Resch

Policies and ethics