Difference between revisions of "Scalasca"
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Scalasca is a performance analysis tool specially geared towards investigating parallel programs. It can also be deployed to profile serial applications. | Scalasca is a performance analysis tool specially geared towards investigating parallel programs. It can also be deployed to profile serial applications. | ||
| − | Scalasca can analyse programs written in [[Fortran]], [[C]] and [[C++]] which are parallelised in [[MPI]] and/or [[OpenMP]]. | + | Scalasca can analyse programs written in [[Fortran]], [[C]] and [[C++]], which are parallelised in [[MPI]] and/or [[OpenMP]]. From the output one can learn where a parallel program is spending time. The tool also highlights typical problems associated with parallel programming, such as load imbalance issues in the code. If the hardware performance counter tool [[PAPI]] is installed on a system, this can be integrated into Scalasca. |
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| + | Scalasca comes with a GUI to visualise the results, which aims to conveniently display the performance issues of an application, even if a large number of tasks and threads are deployed. The results can also be analysed with a number of tools provided by other groups, such as e.g.: [[Paraver]]. | ||
== Availability == | == Availability == | ||
Revision as of 15:05, 20 September 2012
Contents
Overview
Scalasca is a performance analysis tool specially geared towards investigating parallel programs. It can also be deployed to profile serial applications.
Scalasca can analyse programs written in Fortran, C and C++, which are parallelised in MPI and/or OpenMP. From the output one can learn where a parallel program is spending time. The tool also highlights typical problems associated with parallel programming, such as load imbalance issues in the code. If the hardware performance counter tool PAPI is installed on a system, this can be integrated into Scalasca.
Scalasca comes with a GUI to visualise the results, which aims to conveniently display the performance issues of an application, even if a large number of tasks and threads are deployed. The results can also be analysed with a number of tools provided by other groups, such as e.g.: Paraver.
Availability
| Resource | Centre | Description |
|---|---|---|
| Alarik | LUNARC | throughput cluster resource of 40 TFLOPS |
| Aurora | LUNARC | throughput/general purpose cluster resource |
| Platon | LUNARC | throughput cluster resource of 26 TFLOPS |
| Triolith | NSC | Capability cluster with 338 TFLOPS peak and 1:2 Infiniband fat-tree |
License
License: Free.
Free but copyright
Experts
These experts have registered specific competence on this subject:
| Field | AE FTE | General activities | ||
|---|---|---|---|---|
| Joachim Hein (LUNARC) | LUNARC | Parallel programming Performance optimisation | 85 | Parallel programming support Performance optimisation HPC training |
