SHF: Small: Discovering New Mapping Strategies and Architectures for Coarse-Grained Reconfigurable Devices Through Crowdsourcing and Data-Driven Techniques

University Of North Texas, Denton TX

Investigators

Abstract

Coarse-grained reconfigurable fabrics have great promise for achieving energy-efficient flexible designs for an application domain. In order to use these fabrics for practical applications, however, there is a great need to develop smart mapping algorithms to implement applications of interest onto these fabrics. This research is focused on discovering new mapping strategies for customized coarse-grained devices through crowd sourcing. The main thrust of the proposed research is to develop a science game to discover better mapping algorithms by making use of human intuition and ability to recognize patterns and opportunities even in complex problems. Players are presented with successively more difficult mapping problems in a game environment, and the vast dataset of players. Moves are analyzed to recognize common patterns used by successful game players. The insights gained from strategic moves humans make while solving problems based on their visual intuition and experience can be used to discover new mapping approaches that are beyond what can be conceived with traditional algorithms. If time permits, architectural innovations will also be investigated by giving players opportunities to make architectural changes in the game environment. New energy-efficient architectures and mapping algorithms that are developed in this research will spur development of a broad range of portable/wearable computing applications critical to health, safety and security, personal multimedia, and aerospace.