Minerva: Automated hardware optimization tool
Minerva: Automated hardware optimization tool
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Minerva：自动化硬件优化工具
DOI：
10.1109/reconfig.2017.8279804
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
K. Gaj
中科院分区：
文献类型：
--
作者：
Farnoud Farahmand;Ahmed Ferozpuri;William Diehl;K. Gaj
确定数字系统最大时钟频率的常用方法是由CAD工具集（如Xilinx Vivado、Xilinx伊势和Intel Quartus Prime）提供的静态时序分析。找到实际的最大时钟频率是困难的，特别是在Xilinx Vivado中，因为工具选项众多，并且要求的时钟频率与工具实现的实际时钟频率之间存在复杂的依赖关系。例如，查找最大频率的二分搜索是繁琐、耗时的，并且通常不能获得正确的结果。在这项研究中，我们介绍了一个自动化的硬件优化工具，称为Minerva。Minerva使用静态时序分析和作者开发的启发式算法确定接近最佳的工具设置，并以最佳吞吐量或吞吐量与面积（TPA）比为目标。我们将Minerva应用于CAESAR加密竞赛中经过认证的密码候选人的硬件基准测试，其中最佳TPA比（没有任何特定的最大时钟频率目标）是选择获胜者的一个度量标准。我们评估RTL设计的29轮2 CAESAR候选人和当前的标准，AES-GCM，在吞吐量和TPA比。与最大频率的二进制搜索相比，我们的结果表明在吞吐量方面提高了25%，在TPA比率方面提高了38%。
A common way of determining the maximum clock frequency of a digital system is static timing analysis provided by CAD toolsets, such as Xilinx Vivado, Xilinx ISE, and Intel Quartus Prime. Finding the actual maximum clock frequency is difficult, especially in Xilinx Vivado, due to the multitude of tool options, and a complex dependence between the requested clock frequency and the actual clock frequency achieved by the tool. For example, a binary search to find maximum frequency is tedious, time-consuming, and often does not obtain the correct result. In this research, we introduce an automated hardware optimization tool called Minerva. Minerva determines the close-to-optimal settings of tools, using static timing analysis and a heuristic algorithm developed by the authors, and targets either optimal throughput or throughput-to-area (TPA) ratio. We apply Minerva to the hardware benchmarking of authenticated cipher candidates competing in the CAESAR cryptographic contest, where best TPA ratio (without any specific target for maximum clock frequency) is one metric by which winners are selected. We evaluate RTL designs of 29 Round 2 CAESAR candidates and the current standard, AES-GCM, in terms of throughput and TPA ratio. Compared to a binary search for maximum frequency, our results demonstrate up to 25% improvement in terms of throughput, and up to 38% improvement in terms of TPA ratio.