NSF award 2501978 · Kennesaw State University Research and Service Foundation

ERI: Effectively Deploying Large AI Models to Edge Systems via Activation Sparsity Compression

Final report due

28 January 2028

in 467 days · The award ends on 30 September 2027.

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Decide about an extension2 Jun 2027in 227 days
award ending 2027-09-30 · Research.gov
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Extension request16 Aug 2027in 302 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice20 Sep 2027in 337 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Jan 2028in 467 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Jan 2028in 467 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Jan 2028in 467 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

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NSF lists this award's end date as 30 September 2027.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 January 2028.

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Award card

Award number: 2501978
Period of support: 1 Oct 2025 – 30 Sep 2027
Amount: $199,324
Awardee: Kennesaw State University Research and Service Foundation, Kennesaw, GA
Program: ERI-Eng. Research Initiation
Directorate: ENG

Abstract

Deploying large AI/ML models on edge devices offers enormous benefits. These benefits include reducing the computational load on supercomputers and data centers, lowering application response time, enhancing data privacy, and elevating device intelligence capabilities. However, due to the limited computing resources of edge devices, running large-scale AI models directly on them presents significant challenges. To…

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