Self-Aware Processing for Adaptive Resource Optimization of Advanced Computing Systems

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-09-C-0538
Agency Tracking Number: 07SB2-0151
Amount: $749,309.00
Phase: Phase II
Program: SBIR
Awards Year: 2009
Solicitation Year: 2007
Solicitation Topic Code: SB072-009
Solicitation Number: 2007.2
Small Business Information
Impact Technologies, LLC
200 Canal View Blvd, Rochester, NY, 14623
DUNS: 073955507
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Irtaza Barlas
 Sr. Technical Specialist
 (404) 526-6188
 irtaza.barlas@impact-tek.com
Business Contact
 Mark Redding
Title: President
Phone: (585) 424-1990
Email: mark.redding@impact-tek.com
Research Institution
N/A
Abstract
Impact Technologies, in collaboration with our partners Raytheon and Georgia Tech, is developing a suite of integrated components of a self-aware processing and adaptive, intelligent control system for next generation computing systems. During the Phase I program, the team developed a flexible architecture that supported development and implementation of organic computing modules. We integrated a suite of cognitive technologies to provide the constituent capabilities for self monitoring and reconfigurable computing, resulting in a self-aware framework that was shown to be capable of balancing system resources, and mission priorities to efficiently and dynamically meet goal driven requirements. The proposed Phase II program will focus on core innovations in three main areas. First, we will re-formulate the architecture and conceptual framework from Phase I into a more specific self-aware processing system prototype for polymorphous computing arrays (PCA) – specifically associated with the MONARCH platform. Second, working with our team member, we will enhance current simulation tools and generate new development tools for the FPCA framework that will enable implementation of the using high-level languages (such as C/C++). Third, we will work with our commercial partners to analyze how we can transition the self-aware concepts developed under Phase II to the exploding multi/many-core industry.

* information listed above is at the time of submission.

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