论文标题
从性能的角度看粗粒的可重新配置体系结构的调查
A Survey on Coarse-Grained Reconfigurable Architectures from a Performance Perspective
论文作者
论文摘要
随着丹纳德（Dennard）的扩展和摩尔定律的结束，计算机用户和研究人员正在积极探索替代形式的计算形式，以便继续我们享受的性能扩展。在后越野后的替代方案中，更显着和实用的是可重构系统，具有粗粒的可重新配置体系结构（CGRA）似乎能够达到性能和可编程性之间的平衡。在本文中，我们调查了CGRA的景观。我们总结了有关该主题的近三十年文献，特别关注不同的CGRA背后的前提以及它们的发展方式。接下来，我们对可用CGRA的指标进行编译，并分析其性能属性，以了解和发现专门针对高性能计算（HPC）的未来CGRA研究的知识差距和机会。我们发现，将来对CGRA的研究有足够的机会，特别是在大小，功能，对并行编程模型的支持以及评估更复杂的应用程序方面。
With the end of both Dennard's scaling and Moore's law, computer users and researchers are aggressively exploring alternative forms of computing in order to continue the performance scaling that we have come to enjoy. Among the more salient and practical of the post-Moore alternatives are reconfigurable systems, with Coarse-Grained Reconfigurable Architectures (CGRAs) seemingly capable of striking a balance between performance and programmability. In this paper, we survey the landscape of CGRAs. We summarize nearly three decades of literature on the subject, with a particular focus on the premise behind the different CGRAs and how they have evolved. Next, we compile metrics of available CGRAs and analyze their performance properties in order to understand and discover knowledge gaps and opportunities for future CGRA research specialized towards High-Performance Computing (HPC). We find that there are ample opportunities for future research on CGRAs, in particular with respect to size, functionality, support for parallel programming models, and to evaluate more complex applications.
