Chakra is an open and interoperable graph-based representation of AI/ML workloads focused on enabling and accelerating AI SW/HW co-design. Chakra execution traces represent key operations, such as compute, memory, and communication, data and control dependencies, timing, and resource constraints.
This is a repository of Chakra schema and a complementary set of tools and capabilities to enable the collection, analysis, generation, and adoption of Chakra execution traces by a broad range of simulators, emulators, and replay tools.
Chakra is under active development as a MLCommons research project. Please see MLCommons Chakra Working Group for more details for participating in this effort.
A detailed description of the original motivation and guiding principles can be found here. The paper was published prior to Chakra becoming a MLCommons project. Please cite this repository to refer to the latest Chakra schema and tools.
Check out USER_GUIDE for details.
Chakra is released under the MIT license. Please see the LICENSE.md file for more information.
We actively welcome your pull requests! Please see CONTRIBUTING.md for more info.