Operating System Mechanisms for Many-Core Systems

Award Information
Agency: Department of Defense
Branch: N/A
Contract: FA8750-12-C-0149
Agency Tracking Number: O11B-T04-1005
Amount: $99,609.00
Phase: Phase I
Program: STTR
Awards Year: 2012
Solicitation Year: 2011
Solicitation Topic Code: OSD11-T04
Solicitation Number: 2011.B
Small Business Information
385 Moffett Park Drive, Suite 115, Sunnyvale, CA, 94089-
DUNS: 797735883
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Sumant Tambe
 Lead Research Engineer
 (408) 990-7429
 sumant@rti.com
Business Contact
 Catherine Mekler
Title: VP Operations
Phone: (408) 990-7422
Email: cat@rti.com
Research Institution
 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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