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 INSTALL 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.