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.

该项目的目标有两个方向。首先，我们想要扩展我们在OC芯片架构上的概念性工作，以及一个用于设计受控紧急计算的工具。其次，与此同时，我们的两个OC概念已经足够成熟，可以在实际应用中进行演示。基于我们的移动像素（MP）概念的紧急算法的优越性在特定应用设计中得到了证明。现在，这些好处将在通用体系结构中实现。为此，我们开发了一种为紧急计算量身定制的可编程并行架构，该架构将通过ASIC或FPGA的实现进行实验验证。MP算法将在该架构上实现，并在GPGPU多核架构上进行比较，看看紧急计算的优势是否也可以在这种并行架构上被利用。此外，MP方法应该扩展到配置未来的纳米架构。对于MP行为的自动设计，我们开发了一个基于元胞自动机（CA）进化和遗传规划的设计框架。为了提高框架演化的紧急计算方案的质量，我们将引入多重演化和消除冗余CA的概念。该工具设计任意紧急控制系统的通用方法显示了化学组织理论。我们提出的一种紧急硬连线路径规划算法的有效性将在移动机器人OSCAR上得到验证。最后，我们的芯片架构将利用ASoC方法开发自优化特征。