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HPCToolkit is an integrated suite of tools for measurement and analysis of program performance on computers ranging from multicore desktop systems to the nation's largest supercomputers. By using statistical sampling of timers and hardware performance counters, HPCToolkit collects accurate measurements of a program's work, resource consumption, and inefficiency and attributes them to the full calling context in which they occur. HPCToolkit works with multilingual, fully optimized applications that are statically or dynamically linked. Since HPCToolkit uses sampling, measurement has low overhead (1-5%) and scales to large parallel systems. HPCToolkit's presentation tools enable rapid analysis of a program's execution costs, inefficiency, and scaling characteristics both within and across nodes of a parallel system. HPCToolkit supports measurement and analysis of serial codes, threaded codes (e.g. pthreads, OpenMP), MPI, and hybrid (MPI+threads) parallel codes.

The figure below illustrates HPCToolkit's primary components and their relationships.

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Exascale Computing Project (ECP)

HPCToolkit is part of the ECP which is a collaborative effort of two US Department of Energy (DOE) organizations - the Office of Science (DOE-SC) and the National Nuclear Security Administration (NNSA).

In this project, the goal is to extend HPCToolkit with improved capabilities for measurement and analysis of computation, data movement, communication, and I/O at extreme scale. Planned enhancements include improved support for lightweight measurement of massive node-level parallelism using hardware counters, measuring OS activity, recording measurement data efficiently, analyzing performance data in parallel, and integrating code-centric, time-centric, data-centric, and resource-centric views for analysis.

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HPCToolkit is released under the 3-clause BSD license and is available on GitHub/HPCToolkit.

[Page last updated: 2020/12/04]

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