Towards an Automated Development Environment for Parallel Computing with Reconfigurable Processing Elements

摘要建议：0075792 PI：自适应计算系统（ACS）通过采用可重构技术，将定制硬件的性能和软件的灵活性进行了革命性的结合。 ACS的一个关键特征是可重新配置的处理元件，在当前一代中，该处理元件是现场可编程门阵列（FPGA）芯片。 本研究计画探讨ACS在高效能计算网格中的影响，其中包含工作站丛集、共享记忆体多处理器与快速互连。 套快速估计器设计使用FPGA映射和分区的近似算法。应用了各种算法方法。 一个主要的重点是新的启发式和优化策略，旨在利用新兴的数学技术。 还开发了支持软件工具，重点放在可移植性上。 实现测试平台是围绕基于边缘的分割和各种图像处理应用程序常见的相关问题构建的。

ABSTRACTProposal: 0075792PI: Michael LangstonAn adaptive computing system (ACS) offers a revolutionary combination of the performance of custom hardware and the flexibility of software by employing reconfigurable technology. A key feature of an ACS is the reconfigurable processing element, which, in the current generation, is a Field-Programmable Gate Array (FPGA) chip. This research project investigates the impact of an ACS in the context of a high-performance computational grid with clusters-of-workstations, shared memory multi-processors and rapid interconnects. Suites of fast estimators are devised using approximation algorithms for FPGA mapping and partitioning. An assortment of algorithmic methods is applied. A major focus is on new heuristic and optimization strategies designed to exploit emergent mathematical techniques. Supporting software tools are also developed, with an emphasis placed on portability. Implementation testbeds are built around edge-based segmentation and related problems common to a variety of image processing applications.