Machine learning and Optimization-guided Compilers for Heterogeneous Architectures (MOCHA)
Closed Posted
- Opportunity number
- HR001124S0035
- Agency
-
Defense Advanced Research Projects Agency
Department of Defense
- Applications due
- Award size
- Not on record
Opportunity facts
- Assistance listings
- Funding instrument
- Cooperative Agreement, Procurement Contract
- Category
-
- Science and Technology and other Research and Development
- Eligible applicants
-
- Other
- Full announcement
Opportunity details come from Grants.gov. Updated .
About this opportunity
The Defense Advanced Research Projects Agency (DARPA) is seeking proposals for the Machine Learning and Optimization-Guided Compilers for Heterogeneous Architectures (MOCHA) program. MOCHA aims to develop a new generation of compiler technology that can fully leverage heterogeneous computing architectures, including CPUs, GPUs, and specialized accelerators. Key objectives include reducing the human effort required to adapt compilers to new hardware and improving the performance of compiled code across metrics like throughput, power consumption, and memory footprint. DARPA is accepting proposals that address technical challenges related to compiler front-ends, intermediate representations, performance modeling, and code generation. Proposals will be evaluated based on scientific and technical merit, relevance to DARPA's mission, and cost realism.
The MOCHA program is funded under DARPA's Research and Technology Development grant program (CFDA 12.910). DARPA anticipates making multiple awards in the form of cooperative agreements or procurement contracts, though the total estimated value is not specified. The program will span 36 months, with annual evaluations of increasing complexity. Proposals are due by October 10, 2024, and DARPA encourages the use of open-source software and technologies to facilitate technology transition.
Synopsis
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.
Files
| File | Type | Posted |
|---|---|---|
| HR001124S0035-Amendment-01.pdf | ||
| Associate_Contractor_Agreements__ACA___MOCHA_.docx | DOCX document | |
| Abstract_Instructions_and_Template__MOCHA_CT_BK.docx | DOCX document | |
| DARPA_Standard_Cost_Proposal_Spreadsheet__MOCHA_.xlsx | XLSX spreadsheet | |
| Proposal_Summary_Slide__MOCHA_.pptx | PPTX presentation | |
| Proposal_Instruction_and_Volume_II_Template__Cost___MOCHA_.docx | DOCX document | |
| HR001124S0035.pdf | ||
| Proposal_Instructions_and_Volume_I_Template_for_Technical_and_Management__MOCHA_.docx | DOCX document |
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