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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.
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.
Agency: Department of Defense
Office: DARPA - Information Innovation Office
Estimated Funding: $2,000,000
Office: DARPA - Information Innovation Office
Estimated Funding: $2,000,000
Obtain Full Opportunity Text:
SAM.gov Contract Opportunities
Additional Information of Eligibility:
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.
Full Opportunity Web Address:
https://sam.gov/opp/66cab3907c5b4cfcafbf102c5bb17eb6/view
Contact:
Agency Email Description:
See Section VII. Agency Contacts within the full opportunity announcement for all other inquires.
Agency Email:
Date Posted:
2024-08-03
Application Due Date:
Archive Date:
2024-10-26
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