Difference between revisions of "Measurement tools"
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* HPCToolkit: | * HPCToolkit: | ||
* [[Intel_VTune|Intel VTune]]: A performance profiling tool to analyse algorithms and hardware usage for serial and parallel applications | * [[Intel_VTune|Intel VTune]]: A performance profiling tool to analyse algorithms and hardware usage for serial and parallel applications | ||
− | * Scalasca: | + | * [[Scalasca]]: A performance optimisation tool for runtime behaviour measurement and analysis of parallel programs |
− | * [[Score-P]]: Scalable Performance Measurement Infrastructure for Parallel Codes | + | * [[Score-P]]: A Scalable Performance Measurement Infrastructure for Parallel Codes |
Revision as of 12:37, 10 January 2019
Hardware Performance Counter Measurement Tools
Low Level
- Perf: The main interface in the Linux kernel and a corresponding user-space tool to measure hardware counters
- PAPI (Performance-API): A generic API for applications to measure different aspects of the system. For hardware performance counters it uses the perf backend for measurements. Other plugins for GPU and other components exist
- PCM (Performance Counter Monitor): A higher level tool and API that provides common metrics like memory bandwidth and NUMA traffic. The API also provides access to any hardware counter event
- PMU-Tools: A set of Python scripts that use the perf backend
- LIKWID: Command line applications and API to measure hardware events which can use perf as backend but also provides other backends to be independent of the kernel version
High Level
- Vampir: A scalable framework for performance analysis using PAPI as backend
- TAU: Utilities to sample or instrument code for hardware counters and other metrics
- HPCToolkit:
- Intel VTune: A performance profiling tool to analyse algorithms and hardware usage for serial and parallel applications
- Scalasca Trace Tools: A performance optimisation tool for runtime behaviour measurement and analysis of parallel programs
- Score-P: A Scalable Performance Measurement Infrastructure for Parallel Codes