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.
Award Range
Not specified - Not specified
Total Program Funding
Not specified
Number of Awards
Not specified
Matching Requirement
No
Eligible Applicants
Additional Requirements
All responsible sources capable of satisfying the Government's needs may submit a proposal that shall be considered by DARPA. See the Eligibility Information section of the BAA for more information.
Geographic Eligibility
All
Next Deadline
August 22, 2024
Proposal Abstract
Application Opens
August 3, 2024
Application Closes
October 10, 2024
Grantor
U.S. Department of Defense (DARPA - Information Innovation Office)
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