ScoreP - Revision history

Nina-loseke-fd7a@rwth-aachen.de: Replaced content with "#REDIRECT Score-P"

2019-03-14T14:33:15Z

Replaced content with "#REDIRECT Score-P"

Nina-loseke-fd7a@rwth-aachen.de: Redirected page to Score-P

2019-03-14T14:28:37Z

Redirected page to Score-P

141.30.68.16 at 16:21, 20 November 2017

2017-11-20T16:21:19Z

Frank-winkler-4fd3@tu-dresden.de at 16:20, 20 November 2017

2017-11-20T16:20:23Z

141.30.68.16 at 16:18, 20 November 2017

2017-11-20T16:18:07Z

Frank-winkler-4fd3@tu-dresden.de: Created page with "Score-P is a performance evaluation tool for large scale parallel applications. It provides a measurement infrastructure for profiling, event trace recording, and online analy..."

2017-11-20T16:11:42Z

Created page with "Score-P is a performance evaluation tool for large scale parallel applications. It provides a measurement infrastructure for profiling, event trace recording, and online analy..."

New page

Score-P is a performance evaluation tool for large scale parallel applications. It provides a measurement infrastructure for profiling, event trace recording, and online analysis of High Performance Computing applications. Score-P allows users to instrument and record the behavior of sequential, multi-process (MPI, SHMEM), thread-parallel (OpenMP, Pthreads) and accelerator-based (CUDA, OpenCL) applications as well as hybrid parallel applications. Profile data, in CUBE4 format, can be viewed with CUBE or cube_stat. The Score-P trace files, in OTF2 format, can be visualized using Vampir.

← Older revision		Revision as of 14:33, 14 March 2019
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	#REDIRECT [[Score-P]]		#REDIRECT [[Score-P]]
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−	Score-P is a performance evaluation tool for large scale parallel applications. It provides a measurement infrastructure for profiling, event trace recording, and online analysis of High Performance Computing applications. [http://www.vi-hps.org/projects/score-p/]
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−	Score-P allows users to instrument and record the behavior of sequential, multi-process (MPI, SHMEM), thread-parallel (OpenMP, Pthreads) and accelerator-based (CUDA, OpenCL) applications as well as hybrid parallel applications. Profile data, in CUBE4 format, can be viewed with CUBE. The Score-P trace files, in OTF2 format, can be visualized using Vampir.

← Older revision		Revision as of 14:28, 14 March 2019
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		+	#REDIRECT [[Score-P]]
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	Score-P is a performance evaluation tool for large scale parallel applications. It provides a measurement infrastructure for profiling, event trace recording, and online analysis of High Performance Computing applications. [http://www.vi-hps.org/projects/score-p/]		Score-P is a performance evaluation tool for large scale parallel applications. It provides a measurement infrastructure for profiling, event trace recording, and online analysis of High Performance Computing applications. [http://www.vi-hps.org/projects/score-p/]

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−	Score-P allows users to instrument and record the behavior of sequential, multi-process (MPI, SHMEM), thread-parallel (OpenMP, Pthreads) and accelerator-based (CUDA, OpenCL) applications as well as hybrid parallel applications. Profile data, in CUBE4 format, can be viewed with CUBE ~~or cube_stat~~. The Score-P trace files, in OTF2 format, can be visualized using Vampir.	+	Score-P allows users to instrument and record the behavior of sequential, multi-process (MPI, SHMEM), thread-parallel (OpenMP, Pthreads) and accelerator-based (CUDA, OpenCL) applications as well as hybrid parallel applications. Profile data, in CUBE4 format, can be viewed with CUBE. The Score-P trace files, in OTF2 format, can be visualized using Vampir.

← Older revision		Revision as of 16:20, 20 November 2017
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	Score-P is a performance evaluation tool for large scale parallel applications. It provides a measurement infrastructure for profiling, event trace recording, and online analysis of High Performance Computing applications. [http://www.vi-hps.org/projects/score-p/]		Score-P is a performance evaluation tool for large scale parallel applications. It provides a measurement infrastructure for profiling, event trace recording, and online analysis of High Performance Computing applications. [http://www.vi-hps.org/projects/score-p/]
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	Score-P allows users to instrument and record the behavior of sequential, multi-process (MPI, SHMEM), thread-parallel (OpenMP, Pthreads) and accelerator-based (CUDA, OpenCL) applications as well as hybrid parallel applications. Profile data, in CUBE4 format, can be viewed with CUBE or cube_stat. The Score-P trace files, in OTF2 format, can be visualized using Vampir.		Score-P allows users to instrument and record the behavior of sequential, multi-process (MPI, SHMEM), thread-parallel (OpenMP, Pthreads) and accelerator-based (CUDA, OpenCL) applications as well as hybrid parallel applications. Profile data, in CUBE4 format, can be viewed with CUBE or cube_stat. The Score-P trace files, in OTF2 format, can be visualized using Vampir.

← Older revision		Revision as of 16:18, 20 November 2017
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−	Score-P is a performance evaluation tool for large scale parallel applications. It provides a measurement infrastructure for profiling, event trace recording, and online analysis of High Performance Computing applications. Score-P allows users to instrument and record the behavior of sequential, multi-process (MPI, SHMEM), thread-parallel (OpenMP, Pthreads) and accelerator-based (CUDA, OpenCL) applications as well as hybrid parallel applications. Profile data, in CUBE4 format, can be viewed with CUBE or cube_stat. The Score-P trace files, in OTF2 format, can be visualized using Vampir.	+	Score-P is a performance evaluation tool for large scale parallel applications. It provides a measurement infrastructure for profiling, event trace recording, and online analysis of High Performance Computing applications. [http://www.vi-hps.org/projects/score-p/]
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		+	Score-P allows users to instrument and record the behavior of sequential, multi-process (MPI, SHMEM), thread-parallel (OpenMP, Pthreads) and accelerator-based (CUDA, OpenCL) applications as well as hybrid parallel applications. Profile data, in CUBE4 format, can be viewed with CUBE or cube_stat. The Score-P trace files, in OTF2 format, can be visualized using Vampir.