使用零抑制二值决策图的CGRA映射

Rami Beidas, J. Anderson
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引用次数: 3

摘要

粗粒度可重构阵列(CGRAs)的受限路由网络促使CAD开发人员利用精确的解决方案,如整数线性规划(ILP)来制定和解决映射问题。这种依赖于通用优化器的解决方案尚未显示出可伸缩性。在这项工作中,我们将后期CGRA映射描述为一个解枚举和选择问题,依靠零抑制二进制决策图(zdd)[22]的效率来捕获解空间。对于小到中等规模的问题,可以在几兆字节内捕获每个可能的映射。对于更大的问题,可以列举出数千甚至数百万种解决方案。最后的映射是枚举ZDD的简单线性时间DAG遍历。提出的解决方案在CGRA-ME[6]框架中实现。与过去针对较小CGRA器件的解决方案相比,获得了两个数量级的加速。现在可以使用超出这些解决方案容量的更大的设备。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CGRA Mapping Using Zero-Suppressed Binary Decision Diagrams
The restricted routing networks of coarse-grained reconfigurable arrays (CGRAs) have motivated CAD developers to utilize exact solutions, such as integer linear programming (ILP), in formu-lating and solving the mapping problem. Such so-lutions that rely on general purpose optimizers have not been shown to scale. In this work, we formu-late CGRA mapping as a solution enumeration and selection problem, relying on the efficiency of zero-suppressed binary decision diagrams (ZDDs) [22] to capture the solution space. For small-to-moderate size problems, it is possible to capture every possible map-ping in a few megabytes. For larger problems, thou-sands if not millions of solutions can be enumerated. The final mapping is a simple linear-time DAG traver-sal of the enumeration ZDD. The proposed solution was implemented in the CGRA-ME [6] framework. A speedup of two orders of magnitude was obtained when compared with past solutions targeting smaller CGRA devices. Larger devices beyond the capacity of those solutions are now accessible.
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