Command line tool.

SCOUT

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The development of SCOUT was co-funded by the HBP during the Ramp-up Phase. This page is kept for reference but will no longer be updated.

SCOUT is a structure-aware method for prefetching data along interactive spatial query sequences. Given the user input, which is a spatial range query sequence representing the structure explored (interactively) by the user, and the spatial dataset to be queried, SCOUT reduces the query response time by prefetching the data along the query sequence.

Similarly to FLAT, both the query ranges in the query sequence and the spatial objects should be represented using a minimum bounding rectangle.

SCOUT outperforms the related prefetching techniques (e.g., Straight Line Extrapolation or Hilbert prefetching) with high prefetching accuracy, which is translated to one order of magnitude speedup.

Date of releaseMarch 2015
Version of software1.0
Version of documentation1.0
Software availableCollaboratory, integrated in and part of BBP SDK tool set
Documentationhttp://dias.epfl.ch/op/preview/BrainDB
ResponsibleEPFL-DIAS: Xuesong Lu (xuesong.lu@epfl.ch), Darius Sidlauskas (darius.sidlauskas@epfl.ch)
Requirements & dependenciesLinux, Boost library, BBP SDK
Target system(s)PICO supercomputer

Score-P: HPC Performance Instrumentation and Measurement Tool

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The development of Score-P was co-funded by the HBP during the Ramp-up Phase. This page is kept for reference but will no longer be updated.

Score-P logo

 

The Score-P measurement infrastructure is a highly scalable and easy-to-use tool suite for profiling, event tracing, and online analysis of HPC applications. Score-P is developed under a BSD 3-Clause (Open Source) License and governed by a meritocratic governance model.

Score-P offers the user a maximum of convenience by supporting a number of analysis tools. Currently, it works with Periscope, Scalasca, Vampir, and Tau and is open for other tools. Score-P comes together with the new Open Trace Format Version 2, the Cube4 profiling format and the Opari2 instrumenter.

Score-P is part of a larger set of tools for parallel performance analysis and debugging developed by the “Virtual Institute – High Productivity Supercomputing” (VI-HPS) consortium. Further documentation, training and support are available through VI-HPS.

The new version 1.4.2 provides the following new features (externally funded) as compared to version 1.4 that was part of the HBP-internal Platform Release in M18:

  • Power8, ARM64, and Intel Xeon Phi support
  • Pthread and OpenMP tasking support
  • Prototype OmpSs support
Date of releaseFebruary 2014
Version of software1.4.2
Version of documentation1.x
Software availablehttp://www.score-p.org, Section “Download section”
Documentationhttp://www.score-p.org, Section “Documentation”,
ResponsibleScore-P consortium: support@score-p.org
Requirements & dependenciesSupported OS: Linux
Needs OTF2 1.5.x series, Cube 4.3 series, and OPARI2 1.1.2 software packages (available at same website)
Target system(s)Supercomputers (Cray, IBM BlueGene, Fujitsu K/FX10), Linux Clusters of all kinds, Linux Workstations or Laptops (for test/training)

Scalasca: HPC Performance Trace Analyzer

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The development of Scalasca was co-funded by the HBP during the Ramp-up Phase. This page is kept for reference but will no longer be updated.

Scalasca logo

Scalasca is a software tool that supports the performance optimisation of parallelprograms by measuring and analysing their runtime behaviour. The analysis identifies potential performance bottlenecks – in particular those concerning communication and synchronization – and offers guidance in exploring their causes.

Scalasca targets mainly scientific and engineering applications based on the programming interfaces MPI and OpenMP, including hybrid applications based on a combination of the two. The tool has been specifically designed for use on large-scale systems including IBM Blue Gene and Cray XT, but is also well suited for small- and medium-scale HPC platforms. The software is available for free download under the New BSD open-source license.

Scalasca is part of a larger set of tools for parallel performance analysis and debugging developed by the “Virtual Institute – High Productivity Supercomputing” (VI-HPS) consortium. Further documentation, training and support are available through VI-HPS.

The new version 2.2.2 provides the following new features (externally funded) as compared to version 2.2 that was part of the HBP-internal Platform Release in M18:

  • Power8, ARM64, and Intel Xeon Phi support
  • Pthread and OpenMP tasking support
  • Improved analysis
  • Prototype OmpSs support
Date of releaseJanuary 2015
Version of software2.2.2
Version of documentation2.x
Software availablehttp://www.scalasca.org/software/scalasca-2.x/download.html
Documentationhttp://www.scalasca.org/software/scalasca-2.x/documentation.html
ResponsibleScalasca team: scalasca@fz-juelich.de
Requirements & dependenciesSupported OS: Linux
Needs Score-P v1.2 or newer and Cube library v4.3 software packages
Target system(s)Supercomputers (Cray, IBM BlueGene, Fujitsu K/FX10),w Linux Clusters of all kinds, Linux Workstations or Laptops (for test/training)

FLAT

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The development of FLAT was co-funded by the HBP during the Ramp-up Phase. This page is kept for reference but will no longer be updated.

FLAT is a spatial indexing tool, which enables scalable range queries on (3D) spatial datasets. Given the user input, which should be a query range, and the dataset to be queried, FLAT returns all the objects that intersect with the query range.

In particular, both the query ranges and the spatial objects should be represented using minimum bounding rectangle, which is the geometry approximation bounding the underlying spatial object.

FLAT outperforms the state-of-the-art spatial indexing techniques (e.g. R-trees, grid file) on extremely dense datasets.

Date of releaseMarch 2015
Version of software1.0
Version of documentation1.0
Software availableCollaboratory, integrated and part of BBP SDK tool set
Documentationhttp://dias.epfl.ch/op/preview/BrainDB
ResponsibleEPFL-DIAS: Xuesong Lu (xuesong.lu@epfl.ch), Darius Sidlauskas (darius.sidlauskas@epfl.ch)
Requirements & dependenciesLinux, boost library, BBP SDK
Target system(s)PICO supercomputer

Extrae

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The development of Extrae was co-funded by the HBP during the Ramp-up Phase. This page is kept for reference but will no longer be updated.

Extrae is an instrumentation and measurement system gathering time stamped information of the events of an application. It is the package devoted to generate Paraver trace files for a post-mortem analysis of a code run. It uses different interposition mechanisms to inject probes into the target application in order to gather information about the application performance.

The new version 3.2.1 (3rd November 2015) provides the following new features as compared to version 3.1.0 that was part of the HBP-internal Platform Release in M18:

  • Support for MPI3 immediate collectives
  • Use Intel PEBS to sample memory references.

The new version 3.4.1 (23th September 2016) provides the following new features:

  • Extended Java support through AspectJ and JVMTI
  • Improved CUDA and OpenCL support
  • Improved support for MPI-IO operations
  • Added instrumentation for system I/O and other system calls
  • Added support for OMPT
  • Added support for IBM Platform MPI
  • Added instrumentation for memkind allocations
  • Many other small improvements and bug fixes
Date of release23 September 2016
Version of software3.4.1
Version of documentation3.4.1
Software availablehttps://tools.bsc.es/downloads
Documentationhttps://tools.bsc.es/tools_manuals
Extrae website: https://tools.bsc.es/extrae
ResponsibleBSC Performance Tools Group: tools@bsc.es
Requirements & dependenciesDependencies: libxml2 2.5.0; libunwind for Linux x86/x86-64/IA64/ARM.
Optional: PAPI; DynInst; liberty and libbfd; MPI; OpenMP
Target system(s)Any Unix/Linux system (supercomputers, clusters, servers, workstations, laptops …)