Operating System Mechanisms for Many-Core Systems

Award Information
Agency:
Department of Defense
Branch
Office of the Secretary of Defense
Amount:
$99,609.00
Award Year:
2012
Program:
STTR
Phase:
Phase I
Contract:
FA8750-12-C-0149
Award Id:
n/a
Agency Tracking Number:
O11B-T04-1005
Solicitation Year:
2011
Solicitation Topic Code:
OSD11-T04
Solicitation Number:
2011.B
Small Business Information
385 Moffett Park Drive, Suite 115, Sunnyvale, CA, 94089-
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
797735883
Principal Investigator:
Sumant Tambe
Lead Research Engineer
(408) 990-7429
sumant@rti.com
Business Contact:
Catherine Mekler
VP Operations
(408) 990-7422
cat@rti.com
Research Institute:
University of North Carolina
Robert Anderson
Room FB112 Brooks Building
CB #3175
Chapel Hill, NC, 27599-3175
(919) 962-1757
Nonprofit college or university
Abstract
As recent technology trends usher us into the many-core era, novel techniques are needed for high-performance applications to exploit massive local concurrency. To position software applications to run faster on machines with more cores requires substantial restructuring of software applications, middleware, and the operating system. Contemporary operating systems are not designed to run on hundreds or thousands of cores. New operating system mechanisms must be developed to handle scheduling, resource sharing, and communication in a many-core system. The solution must help the application developer create concurrent software and must be easy to use. Real-Time Innovations (RTI) and the University of North Carolina (UNC) Real-Time Systems Group are teaming together to create mechanisms for scheduling and communication for many-core systems that is scalable, high-performance, and adaptable. Our solution has three key innovations: a component architecture, a smart scheduler, and a high-throughput communication infrastructure. The component architecture will help developers to partition applications into concurrent components. The smart scheduler will assign components to clusters of cores to efficiently use the underlying processing capacity. Finally, the high-throughput communication infrastructure will optimize data transfer between components. Our solution will be implemented in Data Distribution Service (DDS) middleware to simplify application development.

* information listed above is at the time of submission.

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