Organic architectures for self-organising smart pixel sensor chips

自组织智能像素传感器芯片的有机架构

• 批准号: 5453770
• 负责人: Professor Dr.-Ing. Dietmar Fey
• 金额: --
• 依托单位: Chair of Computer Science 3 (Hardware Architectures)
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2005
• 资助国家: 德国
• 起止时间: 2004-12-31 至 2008-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/5453770?language=en
• 关键词: Organic; architectures; self; organising; smart

The goal of the project pursues two directions. First, we want to expand our conceptual work on OC chip architectures and on a tool for the design of controlled emergent computing. Second, meanwhile two of our OC concepts are mature enough to demonstrate them in real applications. The superiority of emergent algorithms based on our OC concept of Marching Pixels (MP) was proven for application-specific designs. Now, these benefits shall be achieved in generic architectures. For that, we developed a programmable parallel architecture tailored for emergent computing, which shall be experimentally verified by realisation as ASIC or FPGA. MP algorithms shall be implemented on that architecture and for comparison purposes also on GPGPU many-core architectures to see if the superiority of emergent computing can also be exploited on such parallel architectures. Furthermore, the MP approach shall be expanded for configuring future nanoarchitectures. For the automatic design of MP behaviour we developed a design framework based on the evolution of Cellular Automata (CA) and Genetic Programming. To improve the quality of the framework’s evolved emergent computing scheme, we will introduce concepts for multi-evolution and eliminating of redundant CA. The generic approach of the tool to design arbitrary emergent control systems is shown for the Chemical Organization theory. The efficiency of an emergent hardwired path planning algorithm from us shall be demonstrated for the mobile robot OSCAR. Finally, our chip architecture shall exploit self-optimising features by using ASoC methods.

该项目的目标追求两个方向。首先，我们想扩展我们在OC芯片架构上的概念工作，并在设计受控的紧急计算的工具上扩展。其次，虽然我们的两个OC概念已经足够成熟，足以在实际应用中证明它们。基于我们的OC概念（MP），新兴算法的优势已被证明是针对应用特定设计的。现在，这些好处应在通用体系结构中实现。为此，我们开发了一种针对紧急计算的可编程并行架构，该体系结构应通过现实验证为ASIC或FPGA。 MP算法应在该体系结构上实施，并在GPGPU多核体系结构上进行比较，以查看是否还可以在此类并行体系结构上探索紧急计算的超级。此外，应扩展MP方法以配置未来的纳米结构。对于MP行为的自动设计，我们根据细胞自动机（CA）和遗传编程的演变开发了一个设计框架。为了提高框架进化的紧急计算方案的质量，我们将介绍多进化和消除冗余CA的概念。对于化学组织理论，显示了设计任意紧急控制系统的工具的通用方法。 Oscar移动机器人应证明来自我们的新兴硬性路径计划算法的效率。最后，我们的芯片架构应使用ASOC方法利用自优化的特征。