Timeloop is an infrastructure that aims to provide modeling, mapping and code-generation for Explicitly-Decoupled Data Orchestration (EDDO) architectures, with a focus on for dense- and sparse- tensor algebra workloads. It is built from two modular components:
- A fast analytical model that can emulate a range of EDDO architecture designs and provide performance and energy projections
- A mapper that that searches for an optimal mapping in the space of mappings of a tensor-algebra problem on a given architecture
Timeloop documentation is hosted at https://timeloop.csail.mit.edu/timeloop. The guides there cover installation, usage and examples. For a deeper understanding of Timeloop's internals please read our ISPASS 2019 paper.
New users are strongly encouraged to complete the Timeloop tutorial. Serially walking through the exercises from the tutorial serves as an essential hands-on introduction to the tool.