Timemory is a modular API for performance measurements and analysis with a very lightweight overhead. If timemory does not support a particular measurement type or analysis method, user applications can easily create their own component that accomplishes the desired task.
Timemory is implemented as a generic C++14 template library but supports implementation in C, C++, Fortran, CUDA, and Python codes. The design goal of timemory is to create an easy-to-use framework for generating performance measurements and analysis methods which are extremely flexible with respect to both how the data is stored/accumulated and which methods the measurement or analysis supports.
Toolkit for creating new performance analysis tools
Common instrumentation framework
Eliminate need for projects to explicitly support multiple instrumentation frameworks
High performance during data collection
Low overhead when dormant (disabled at runtime)
Zero overhead when disabled at compile time
Support arbitrarily intermixing components:
Instrument measurements of A, B, and C around arbitrary region 1
Instrument measurements of A and C around arbitrary region 1.1 (nested with Section 1)
Instrument measurements of C around arbitrary region 2
Instrument measurements of D around arbitrary region 3
No instrumentation around arbitrary region 4
Intuitive and simple API to use and extend
Support for timemory in external tools¶
Currently, timemory provides compatibility with multiple tools internally but the end goal is for the majority of this to be maintained by the authors of the tool. This will benefits users by provided a single method for using all of their favorite tools and make it extremely easy for them to try out new tools. This will benefit the authors of the tools because there will be a significantly lower the introduction barrier required for users to try out the new tool – if the user is familiar with timemory, the tool can be trivially integrated into either their code or into the profiler.
An external tool can easily provide compatibility with timemory and leverage all of its work creating a low-overhead measurement system in parallel environments, Python extensions, and dynamic instrumentation, by simply providing a header in their source code which defines the interface the tool wants to provide and the tools can add/remove support at will without having to maintain any source code in timemory or worry about version compatability with timemory. Versioning issues do not inherently exist because for several reasons which are detailed the CONTRIBUTING.md documentation.
Timemory is actively developed by NERSC at Lawrence Berkeley National Laboratory
|Jonathan R. Madsen||NERSC||jrmadsen|