HR001124S0022_ScAN_Attachment_B_Abstract_Template.docx
DOCX document 43 KB Posted
- Attached to
- Scalable Analog Neural-networks (ScAN) Federal contract opportunity
- Solicitation number
- HR001124S0022
About this file
This document is an abstract template for the Scalable Analog Neural-networks (ScAN) program solicitation by the Defense Advanced Research Projects Agency (DARPA). The template outlines the requirements for abstract submissions, including page limits, formatting, and required content. Key details include:
The ScAN program is seeking innovative proposals for the research and development of scalable, robust, and power-efficient analog neural network architectures and circuits that can interface directly with analog sensor outputs. Proposers must address technical challenges such as overcoming scaling limitations, performance degradation due to process variations, and device-dependent variations. The abstract must include information on the proposed technical approach, capabilities/management plan, level of effort, and a summary slide. DARPA will provide feedback on whether to submit a full proposal, but a favorable response is not a guarantee of award. Proposals are due by the deadline specified in the Overview Information.
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HR001124S0022: Scalable Analog Neural-networks (ScAN) Program Abstract Instructions and Template
Use of this template is mandatory for all abstract submissions to this BAA. Proposers must include Attachments A (Abstract Summary Slide Template) and B to constitute a full abstract submission. This document must include all components described herein and must be submitted in .pdf, .odx, .doc, or .docx formats. All submissions must be written in English and all pages shall be formatted for printing on 8-1/2 by 11-inch paper with 1-inch margins and font size not smaller than 12 point. Font sizes of 8 or 10 point may be used for figures, tables, and charts.
Abstracts shall not exceed a maximum of 7 pages. Abstracts should be at the UNCLASSIFIED or Controlled Unclassified Information (CUI) level. All proprietary data and information should be appropriately marked.
| Page limit includes: |
| Page limit does NOT include: |
| All figures, tables, charts |
| Abstract Summary Slide |
Cover Letter
Title Page
Table of Contents
Bibliography (Optional)
Technical Papers (Optional, no more than 3)
Proposers are strongly encouraged but not required to submit an abstract before submitting a full proposal. DARPA will respond to abstracts with a statement as to whether DARPA:
a. recommends the proposer submit a full proposal or,
b. does not recommend the proposer submit a full proposal with a rationale for this decision.
Regardless of DARPA’s response to an abstract, proposers may submit a full proposal. DARPA will review all conforming full proposals using the published evaluation criteria and without regard to any comments resulting from the review of an abstract. Proposers should note that a favorable response to an abstract is not a guarantee that a proposal based on the abstract will ultimately be selected for award negotiation. It is DARPA policy to attempt to reply to abstracts within thirty calendar days. These official notifications will be sent via email to the Technical POC and/or Administrative POC identified on the abstract cover sheet.
Abstracts must be submitted per the instructions outlined herein and received by DARPA no later than the due date and time listed in the Overview Information. Abstracts received after this time and date may not be reviewed. Please visit Proposer Instructions and General Terms and Conditions for instructions on how to submit your abstract through the Broad Agency Announcement Tool.
COVER SHEET
[PRIME ORGANIZATION LOGO]
Abstract Title
Proposer Organization
| Technical Point of Contact (POC) |
| Name: |
Mailing Address:
Telephone:
Email:
| Administrative POC |
| Name: |
Mailing Address:
Telephone:
Email:
| Other Team Members (subcontractors and consultants), if known/applicable |
| Technical POC Name: |
Organization:
Technical POC Name:
Organization:
| Estimated Total Cost (Base + Options) |
| $ |
Estimated Period of Performance
Identify any other solicitation(s) to which this concept has been proposed
Table of Contents
| 1. | Goals and Impact | 4 |
| 2. | Technical Approach | 4 |
| 3. | Capabilities/Management Plan | 4 |
| 4. | Level of Effort | 4 |
| 5. | Bibliography | 4 |
| 6. | Summary Slide | 4 |
HR001124S0022 Abstract Source Selection Sensitive – See FAR 2.101 and FAR 3.104
1 | Page
Goals and Impact [Describe what is being proposed and what difference it will make (qualitatively and quantitatively) if successful. Describe the innovative aspects of the project in the context of existing capabilities and approaches, clearly delineating the relationship of this work to any other projects from the past and present.] Technical Approach [Provide answers to the following questions:
· What is the proposed work attempting to accomplish or do?
· How is the work performed today (what is the state of the art or practice), and what are the limitations?
· What is new in your approach, and why do you think it will be successful?
· How would the DoD testing community implement the proposed approach/work?
· How much will it cost (rough order of magnitude), and how long will it take?
Outline and address technical challenges inherent in the approach and possible solutions for overcoming potential problems. Provide appropriate measurable milestones (quantitative if possible) at intermediate stages of the project to demonstrate progress and a plan for achieving the milestones. Proposers must:
· clearly describe the proposed approach without using any jargon;
· provide compelling support for how the proposed approach will overcome or obviate the technical challenges to achieve the ScAN program objectives:
· how the proposed architecture approach will overcome scaling limitations and short-term performance fluctuations, beyond mere extrapolation of academic or toy sized networks, e.g., MNIST digit recognition;
· how the proposed circuit/hardware approach will overcome or mitigate performance (inference accuracy) degradation due to process, voltage, and temperature (PVT) variations, and long-term drifts, especially in large-scale networks, beyond mere extrapolation or bit-resolution reduction arguments;
· how the proposed approach will overcome device-dependent variations with minimal calibrations or model fine-tuning for practical applications;
· provide a concise description of the interaction between hardware and algorithm tasks, especially how the results of each task will inform the development of the other;
· provide estimated computing resource requirements for design and simulation of the proposed architecture, for model training, and for application performance estimation;
· provide estimated fabrication cycle-times and expected number of runs (by phase) for the proposed technology.] Capabilities/Management Plan [Provide a brief summary of the expertise of the team, including subawardees and key personnel. While teaming arrangements do not need to be finalized at the time of abstract submission, mention of potential teaming/collaboration arrangements is highly encouraged. Identify a principal investigator for the project and include a description of the team’s organization, including roles and responsibilities in covering neural network architecture and algorithm development, large-scale analog circuit design and integration, hardware-informed application performance modeling, and image sensor processing.] Level of Effort [Including the names of the key individuals who will be working on the project and their Level of Effort (Equivalent (FTE)), the estimated total labor cost, and estimated materials and Other Direct Costs (ODC).] Bibliography [Provide a brief (no more than 2 page) bibliography of relevant papers, references, reports, etc. All relevant source information should be included; links to this information are not sufficient.] Summary Slide [Provide a summary slide in .PPT format as outlined in Attachment A]
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