COMP Superscalar

Big Data
Distributed Computing
Programming Models

COMP Superscalar (COMPSs) is a framework which aims to ease the development and execution of applications for distributed infrastructures, such as Clusters, Grids and Clouds.

Software Author: 

Workflows and Distributed Computing Group

Contact:

Jorge Ejarque (jorge [dot] ejarque [at] bsc [dot] es)

Rosa M. Badia (rosa [dot] m [dot] badia [at] bsc [dot] es)

Software Cost: 

COMP Superscalar is distributed under Apache License version 2

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2.1 (Latest Version)

COMP Superscalar version 2.1 (Bougainvillea) Release date: June-2017

Release Notes

New features

  • Runtime:
    • New annotations to simplify tasks that call external binaries
    • Integration with other programming models (MPI, OmpSs,..)
    • Support for Singularity containers in Clusters
    • Extension of the scheduling to support multi-node tasks (MPI apps as tasks)
    • Support for Grid Engine job scheduler in clusters
    • Language flag automatically inferred in runcompss script
    • New schedulers based on tasks’ generation order
    • Core affinity and over-subscribing thread management in multi-core cluster queue scripts (used with MKL libraries, for example)
  •  Python:
    • @local annotation to support simpler data synchronizations in master (requires to install guppy)
    •  Support for args and kwargs parameters as task dependencies
    •  Task versioning support in Python (multiple behaviors of the same task)
    • New Python persistent workers that reduce overhead of Python tasks
    •  Support for task-thread affinity
    • Tracing extended to support for Python user events and HW counters (with known issues)
  • C/C++:
    • Extension of file management API (compss_fopen, compss_ifstream,  compss_ofstream, compss_delete_file)
    • Support for task-thread affinity
  •  Tools:
    • Visualization of not-running tasks in current graph of the COMPSs Monitor

Improvements

  • Improved PyCOMPSs serialization
  • Improvements in cluster job scripts and supercomputers configuration
  • Several bug fixes

 
Known Limitations:

  • When executing Python applications with constraints in the cloud the <InitialVMs> property must be set to 0
  • Tasks that invoke Numpy and MKL may experience issues if tasks use a different number of MKL threads. This is due to the fact that MKL reuses threads in the different calls and it does not change the number of threads from one call to another.

 

Ubuntu x86_64

COMPSs Ubuntu x86_64 repository list. Check Installation manual for details about how to install from the repository

Ubutu noarch

COMPSs Ubuntu noarch repository list. Check Installation manual for details about how to install from the repository

Debian x86_64

COMPSs Debian x86_64 repository list. Check Installation manual for details about how to install from the repository

Debian noarch

COMPSs Debian noarch repository list. Check Installation manual for details about how to install from the repository

CentOS

COMPSs CentOS x86_64 repository. Check Installation manual for details about how to install from the repository

OpenSUSE x86_64

COMPSs OpenSUSE x86_64 repository. Check Installation manual for details about how to install from the repository

OpenSUSE noarch

COMPSs OpenSUSE noarch repository. Check Installation manual for details about how to install from the repository

Read this document before downloading the VM image: COMPSs VM Instructions

COMPSs VM

Old Versions

2.0

1.4

1.3