HeteroCL is a programming infrastructure composed of a Python-based domain-specific language (DSL) and a compilation flow through close collaboration by research groups led by Prof. Zhiru Zhang at Cornell and Prof. Jason Cong at UCLA. The HeteroCL DSL provides a clean abstraction that decouples algorithm specification from three important types of hardware customization in compute, data types, and memory architectures. HeteroCL further captures the interdependence among these techniques, allowing programmers to explore various trade-offs in a systematic and productive manner. In addition, our framework produces highly efficient hardware implementations for a variety of popular workloads by targeting spatial architecture templates such as systolic arrays and stencil with dataflow architectures. There is also an implementation flow via the Merlin Compiler from Falcon Computing.
For more information, please visit: http://heterocl.csl.cornell.edu/
For source code, please visit: https://github.com/cornell-zhang/heterocl
Students: Yi-Hsiang Lai1, Yuze Chi2, Yuwei Hu1, Jie Wang2, Cody Hao Yu2,3, Yuan Zhou1
Faculty: Jason Cong2, Zhiru Zhang1
1Cornell 2UCLA 3Falcon Computing Solutions, Inc.