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

SHF：小型：通过众包和数据驱动技术发现粗粒度可重构设备的新映射策略和架构

• 批准号: 1117800
• 负责人: Gayatri Mehta
• 金额: $ 17.9万
• 依托单位: University of North Texas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2013-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1117800&HistoricalAwards=false
• 关键词: SHF; Small; Discovering; New; Mapping

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.

粗粒度可重构结构在实现应用领域的节能灵活设计方面具有很大的潜力。然而，为了将这些织物用于实际应用，非常需要开发智能映射算法以将感兴趣的应用实现到这些织物上。这项研究的重点是发现新的映射策略，定制粗粒度的设备，通过众包。拟议研究的主旨是开发一个科学游戏，通过利用人类的直觉和能力，即使在复杂的问题中识别模式和机会，发现更好的映射算法。玩家在游戏环境中遇到越来越困难的映射问题，以及大量的玩家数据集。 分析移动以识别成功游戏玩家使用的常见模式。人类在基于视觉直觉和经验解决问题时所采取的战略行动所获得的洞察力可以用来发现新的映射方法，这些方法超出了传统算法的设想。如果时间允许，还将通过让玩家有机会在游戏环境中进行建筑更改来研究建筑创新。在这项研究中开发的新的节能架构和映射算法将刺激广泛的便携式/可穿戴计算应用的发展，这些应用对健康，安全和安保，个人多媒体和航空航天至关重要。