Machine learning and Optimization-guided Compilers for Heterogeneous Architectures (MOCHA)

The summary for the Machine learning and Optimization-guided Compilers for Heterogeneous Architectures (MOCHA) grant is detailed below. This summary states who is eligible for the grant, how much grant money will be awarded, current and past deadlines, Catalog of Federal Domestic Assistance (CFDA) numbers, and a sampling of similar government grants. Verify the accuracy of the data FederalGrants.com provides by visiting the webpage noted in the Link to Full Announcement section or by contacting the appropriate person listed as the Grant Announcement Contact. If any section is incomplete, please visit the website for the DARPA Information Innovation Office, which is the U.S. government agency offering this grant.

Machine learning and Optimization-guided Compilers for Heterogeneous Architectures (MOCHA): Machine Learning and Optimization-Guided Compilers for Heterogeneous Architectures (MOCHA) seeks to build a new generation of compiler technology to realize the full potential performance of heterogenous architectures. MOCHA will develop data-driven methods, Machine Learning, and advanced optimization techniques to rapidly adapt to new hardware components with little human effort and facilitate optimal allocation of computation to heterogeneous components.