基于可重构的多并行计算模式视觉识别系统研究

项目名称： 基于可重构的多并行计算模式视觉识别系统研究

项目编号： No.61203251

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 自动化学科

项目作者： 齐志

作者单位： 东南大学

项目金额： 24万元

中文摘要： 目标识别算法是当前嵌入式领域最具应用前景的视觉算法之一，然而设计出既能满足识别算法性能，又能平衡性能与面积、功耗间矛盾的硬件架构仍是未解决的难题。单指令多数据/多指令多数据(SIMD/MIMD)架构因其高能效、低面积、灵活性强的特点而引起关注。然而，识别算法中的高层计算处理的数据结构不规则，包含大量循环中的判断，限制了指令执行的SIMD/MIMD架构充分发挥效率。本项目通过对SIMD/MIMD架构改进和拓展，拟在同一块硬件上分时支持SIMD模式、多SIMD簇模式及可重构模式。主要内容包括：利用可重构的可配置性和灵活性最大限度挖掘并行度，提高高层算法的执行效率；设计支持可重构的NoC网络，实现多计算模式间的快速切换，减小多计算模式的引入对架构性能的影响； 研究适应不同层次计算的数据组织方法，从而缓解识别算法对存储带宽的压力；此外，本项目拟搭建目标识别系统评估平台，探索和评估硬件设计方案。

中文关键词： 可重构计算；硬件加速的识别计算；；；

英文摘要： Computer vision has become as one of the most promising areas of embedded applications. However, balancing the huge computation and communication demands of the algorithms with the stringent size, power and memory resource constaints of embedded platforms have created incredible challenges. Parallelization has emerged as one of the solutions to overcome these challenges. We aim to achieve an efficient embedded image recognition system with robustness to complicated environments containing multiple objects. The proposed solution is an improvement and expansion of conventional SIMD/MIMD architectures. By combining reconfigurable technology with SIMD/MIMD parallel computing models, and taking advantage of the flexibility and configurability of a reconfigurable architecture, we improve the performance on all three different levels of image recognition algorithms at an expense of the minimal hardware resources. In addition, by employing the data organization adaptable to different algorithm levels, the solution can effectively release the pressure on the memory by object recognition algorithms. Implementing hardware and software co-design methodology, an evaluation platform for object recognition system is also very necessary.

英文关键词： reconfigurable computing；hardware accelerated recognition；；；